DOCTORAL DEGREE IN AEROSPACE SCIENCE AND TECHNOLOGY

• CUMELLES CÉSPEDES, JOEL: System Identification of High-Performance Paraglider-Harness/Pilot Dynamics: From Modelling to Flight Test Data
  
  Author: CUMELLES CÉSPEDES, JOEL
  Programme: DOCTORAL DEGREE IN AEROSPACE SCIENCE AND TECHNOLOGY
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 02/06/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: CASAS PIEDRAFITA, JAIME OSCAR | ORTEGA AGODINO, ENRIQUE
  Thesis abstract: Despite substantial advances in the design, development, and analysis of high-performance paraglider–harness/pilot systems, evaluation methods remain predominantly qualitative and rely heavily on trial-and-error testing. Quantitative in-flight experimental data for these configurations remain scarce, and traditional parafoil–payload models frequently fail to capture the complex geometry, aerodynamic interactions, and dynamic behaviour characteristic of modern high-performance paragliders.This thesis proposes an integrated framework that combines a high-fidelity dynamic model specifically adapted to these systems with a low-cost instrumental platform for model validation using experimental flight data. A nonlinear eight-degrees-of-freedom dynamic model of the high-performance paraglider–harness/pilot system is derived, explicitly incorporating apparent mass effects. Aerodynamic forces and moments are obtained by coupling the model to a computationally efficient horseshoe vortex method solver based on Prandtl’s lifting-line theory and augmented with viscous drag corrections derived from airfoil section polars. This approach enables the direct computation of aerodynamic loads from the actual canopy architecture. Additional refinements are incorporated to improve model fidelity, including a parametric aerodynamic model of the harness/pilot assembly, a generalised aerodynamic drag formulation for the suspension lines, and a distributed representation of brake input along the span and chord.A modular, low-cost, wireless instrumentation platform was developed to support model validation and generate quantitative datasets. This platform integrates distributed accelerometers, gyroscopes, magnetometers, as well as barometric pressure, temperature, and humidity sensors; a GPS module; and a multi-hole probe installed on one of the paraglider suspension lines. The platform was implemented on a commercial high-performance paraglider and evaluated through two dedicated flight-test campaigns.Finally, a system identification approach based on output error methods is implemented to adjust model parameters, enabling comparison of flight data and model predictions across manoeuvres. The results exhibit strong agreement in dynamic response and aerodynamic behaviour, confirming the suitability of the proposed modelling and instrumentation framework. This framework will support future studies of high-performance paraglider–harnesses/pilot systems with quantitative data, thereby enhancing understanding and further development.
  
• SUVORKIN, VLADIMIR: Robust positioning using hybridization of GNSS with other measurements of opportunity
  
  Author: SUVORKIN, VLADIMIR
  Programme: DOCTORAL DEGREE IN AEROSPACE SCIENCE AND TECHNOLOGY
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 21/04/2026
  Reading date: 02/07/2026
  Reading time: 13:00
  Reading place: Sala de Juntes, Edifici B3, Campus Nord
  Thesis director: ROVIRA GARCIA, ADRIÀ | GONZÁLEZ CASADO, GUILLERMO
  Thesis abstract: Achieving robust positioning across ground and UAV platforms remains challenging under multipath, partial satellite visibility, and rapidly changing measurement quality, especially in urban and embedded scenarios. At the same time, modern smartphones and embedded receivers increasingly provide multi-constellation, dual-frequency observations, carrier-phase measurements, and IMU streams that can be exploited for aided positioning.The present thesis addresses these conditions through a robust GNSS/IMU integration framework, evaluated across heterogeneous sensor grades, from navigation-grade platforms to consumer smartphones. The framework is designed not only for offline post-processing, but also for real-time and embedded operation, following a deterministic execution structure suitable for on-board use.The principal conclusions are:First, a unified processing framework has been developed for GNSS/IMU integration using raw, undifferenced, uncombined GNSS observables (code, carrier phase, Doppler) and inertial measurements.Second, a Square-Root Information Filter (SRIF) architecture has been adopted as the estimator core, enabling a numerically robust implementation and a shared software structure across GNSS-only processing, loosely coupled (LC) fusion, and tightly coupled (TC) fusion modes.Third, Allan deviation analysis has been used systematically to identify inertial noise parameters and to configure the process-noise model of the navigation filter across different IMU classes, improving consistency of tuning when detailed manufacturer specifications are incomplete.Fourth, experimental validation on multiple independent datasets, spanning different GNSS conditions and equipment grades, shows that LC fusion provides the most consistent practical gains, especially in continuity and robustness during short GNSS degradations, and often improves typical solution behaviour when inertial data quality is adequate.Fifth, in dense urban conditions with strong multipath and masking, positioning performance remains fundamentally constrained by GNSS measurement quality and correction level; inertial aiding mitigates short-term disruptions but does not eliminate the GNSS-side error ceiling.Finally, the thesis demonstrates a transferable and numerically stable GNSS/IMU integration framework, a reproducible Allan-based methodology for configuring heterogeneous IMUs in the filter, and a realistic path toward robust positioning under practical field conditions.
  

DOCTORAL DEGREE IN APPLIED MATHEMATICS

• GIL RAMS, DÍDAC: Splitting of separatrices in generalized standard maps
  
  Author: GIL RAMS, DÍDAC
  Programme: DOCTORAL DEGREE IN APPLIED MATHEMATICS
  Department: School of Mathematics and Statistics (FME)
  Mode: Normal
  Deposit date: 15/05/2026
  Reading date: 03/07/2026
  Reading time: 16:30
  Reading place: Sala d'Actes de l'FME, Edifici U, Campus Sud Enllaç videoconferència: https://meet.google.com/ghn-dzuh-gte
  Thesis director: MARTIN DE LA TORRE, PAU | BALDOMA BARRACA, INMACULADA CONCEPCION
  Thesis abstract: We consider generalized standard maps, that is, families of area-preserving maps on the plane F:(x,y) = (x+y+f(x;h),y+f(x;h)) with h the perturbative parameter and f fulfilling quite general assumptions. This generalization includes the Chirikov standard map, the Hénon map or the perturbed McMillan map, among others.We study transverse intersections between the invariant manifolds (stable and unstable) associated to a hyperbolic fixed point of F. These intersections give rise to homoclinic orbits related to the hyperbolic fixed point. The existence of these kind of orbits is one of the most celebrated methods to prove the existence of chaotic dynamics in a system. Indeed, the Birkhoff-Smale Homoclinic Theorem ensures that, if there exist transverse intersections between the invariant manifolds of the same invariant object, the system is locally conjugate to a Smale horseshoe with infinite symbols.The classical Melnikov theory is a first order perturbative theory that is often used to measure the intersection angle between the invariant manifolds. However, when the Melnikov function is exponentially small in the perturbative parameter, the first order analysis fails. Despite its exponentially small character, the Melnikov function still provides the correct size of the splitting in some systems. This is not our case, which is singular. To deal with it, we use a complex time matching technic involving the inner equation related to F.In the first part of our work, by considering an small enough perturbative parameter h, we obtain an asymptotic formula for the Lazutkin's invariant, a quantity analogous to the intersection angle between the invariant manifolds, related to the primary homoclinic points of a wide class of maps F. An exponentially small upper bound was obtained by Fontich. Later, we provide an asymptotic formula for a controversial example exponentially bigger than the naïve guess.The leading term of the obtained asymptotic formulas depends on a constant, often called Stokes constant, that comes from the study of the inner equation. The second part of our work contains a general algorithm, based on the study of the inner equation related to F, to compute an interval containing such constants by means of a computer assisted proof in CAPD. Finally, we apply this algorithm to prove that the Stokes constants related to maps F of the form f(x;h)=e f_0(x), with e = 4 sinh^2(h/2) and f_0 a polynomial of degree 2<=d_0<= 970 or trigonometric polynomial of any degree, are different from zero (including the Standard and Hénon maps). We also provide an example of a generalized standard map such that its Stokes constant is zero.
  

DOCTORAL DEGREE IN ARCHITECTURE, ENERGY AND ENVIRONMENT

• SANCLEMENTE CANIZALES, HOLVER: Vivienda y clima en el trópico húmedo: análisis tipológico-bioclimático en Buenaventura
  
  Author: SANCLEMENTE CANIZALES, HOLVER
  Programme: DOCTORAL DEGREE IN ARCHITECTURE, ENERGY AND ENVIRONMENT
  Department: Department of Architectural Technology (TA)
  Mode: Normal
  Deposit date: 03/06/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: LÓPEZ BESORA, JUDIT | COCH ROURA, HELENA
  Thesis abstract: This thesis addresses the critical issue of housing adaptation to the humid tropical climate of Buenaventura, Colombia, a region facing heightened housing challenges due to unsuitable construction models and climate change. Through an approach that transcends simple architectural description, the research focuses on understanding and systematizing spatial housing typologies from a bioclimatic perspective, validating ancestral knowledge against contemporary vulnerabilities.An exhaustive recovery and systematization of 471 housing cases in Buenaventura was conducted, providing an unprecedented empirical body for bioclimatic analysis in the region. The methodology was articulated around the identification and analysis of key passive strategies: natural ventilation (cross and vertical), solar protection (porches and overhangs), and humidity management potential (patios).The main findings establish a robust bioclimatic typological classification that reveals three distinct performance realities. On one hand, the corner house stands out for its inherent potential for cross-ventilation, although it requires optimization of solar control and roof ventilation to achieve comfort. On the other hand, the terraced house with an exterior courtyard validates the efficacy of traditional architecture, confirming the courtyard as a climatic engine or "bioclimatic siphon" essential for hot air suction and central circulation. In contrast, the terraced house without a courtyard is identified as the most bioclimatic vulnerable typology, requiring the forced introduction of an interior "lung" (courtyard or void) to restore ventilation and the chimney effect.The conclusion is compelling: The sustainable and resilient solution for thermal comfort lies in the rigorous validation and optimization of local architectural knowledge. A Bioclimatic Foundation is established, demanding the structural compensation of the high thermal inertia of contemporary materials through High Albedo (white facades) and Structural Solar Control (overhangs/porches). A new paradigm of passive design is proposed that integrates the Double Thermal Action (cross-ventilation + roof convection) and the redefinition of the void space, setting the typology-differentiated design guidelines for future housing in Buenaventura that are efficient, healthy, and culturally relevant.Keywords Humid Tropics, Bioclimatic Design, Natural Ventilation, Housing Typology, Buenaventura, Climate Resilience, Passive Architecture.
  

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

• HAUBENSAK, LUKAS: Optimization and control of multiple fuel cell systems
  
  Author: HAUBENSAK, LUKAS
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Department of Automatic Control (ESAII)
  Mode: Normal
  Deposit date: 28/05/2026
  Reading date: 21/07/2026
  Reading time: 12:00
  Reading place: Aula Capella, Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB),Planta Baixa, Av. Diagonal, 647 08028 Barcelona
  Thesis director: COSTA CASTELLO, RAMON | STRAHL, STEPHAN
  Thesis abstract: Decarbonizing heavy-duty transportation is a pressing challenge in mitigating climate change. Fuel cell electric vehicles offer a promising zero-emission solution that combines the extended range of chemical fuels with the rapid refueling capabilities required by the freight industry. Commercial trucks increasingly adopt multi-stack fuel cell systems to meet power and redundancy demands. However, the commercial viability of these vehicles depends on minimizing the total cost of ownership. This economic metric directly reflects hydrogen fuel consumption and the degradation of all fuel cell stacks and the traction battery.Minimizing this total cost of ownership requires optimal control strategies that balance fuel economy against component longevity. This control problem is challenging due to stiff system dynamics with widely distributed time scales. Conventional rule-based control strategies react to present conditions and fail to anticipate future loads. Consequently, they schedule start-stop transitions poorly, struggle to prevent thermal derating, and cannot adapt to a declining state-of-health.To overcome these limitations, this dissertation develops a computationally tractable and lifetime-adaptive hierarchical model predictive control framework. A Planning Layer solves a multi-horizon mixed-integer problem to optimize the inter-stack power split, start-stop scheduling, and thermal management over the remaining driving route. Simultaneously, a fast-sampled Operational Layer manages constrained air-system dynamics to satisfy power demands while balancing fuel efficiency against electrochemical surface area loss. A closed-loop estimation scheme monitors stack degradation and automatically refits the internal prediction models to maintain controller accuracy.Simulations on standardized driving cycles demonstrate that this hierarchical controller approximates the global optimum. It consumes only 1.3% more hydrogen than an in-hindsight benchmark while maintaining real-time feasibility. Integrated thermal and energy management preconditions the cooling circuit to prevent thermal derating and enables less conservative component sizing. Furthermore, the proposed adaptive controller shifts its operating strategy over the fuel cell stack's lifetime. At the Begin-of-Life, the controller minimizes fuel cell degradation and reduces electrochemical surface area loss by up to 96.8% As the stack ages and voltage sensitivities decrease, the strategy transitions toward minimizing hydrogen consumption.This framework translates physical degradation mechanisms directly into an economic control objective, integrating electrochemical state-of-health into system-level powertrain management. It shows that predictive and integrated control of thermal, fluid, and power dynamics is a prerequisite to exploit the full hardware potential of hybrid multi-stack powertrains. Resolving these conflicts between fuel economy, component longevity, and computational limits lowers the economic barriers to widespread fuel cell electric vehicle adoption.
  
• MARTÍ FLORENCES, MIQUEL: Regression-Based Estimation of Internal Variables in Lithium-Ion Batteries
  
  Author: MARTÍ FLORENCES, MIQUEL
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Department of Automatic Control (ESAII)
  Mode: Normal
  Deposit date: 04/06/2026
  Reading date: 16/07/2026
  Reading time: 16:00
  Reading place: Sala d'Actes de la Facultat de Matemàtiques i Estadística (FME), Campus Diagonal Sud, Carrer de Pau Gargallo, 14, 08028 Barcelona
  Thesis director: COSTA CASTELLO, RAMON | CECILIA PIÑOL, ANDREU
  Thesis abstract: The decarbonisation of energy systems, the increasing penetration of renewable generation, and the electrification of transport have made lithium-ion batteries a key enabling technology in modern power applications. Their versatility and high energy density explain their central role in electric vehicles and stationary energy storage. However, their safe and efficient operation depends on battery-management systems capable of estimating internal quantities that cannot be measured directly, such as state of charge, open-circuit voltage, and relevant electrical parameters. This task is difficult because battery behaviour is nonlinear, operating conditions are variable, and the measurements normally available in practice are limited.This thesis addresses these challenges through a practical estimation framework for real-time battery-management applications. It reviews the main modelling and estimation approaches for lithium-ion batteries and justifies the use of low-order equivalent circuit models as a suitable compromise between physical relevance and online implementability. It also reviews the estimation-theoretic basis required to work under realistic operating conditions, with particular attention to observability and excitation. A central point is that classical recursive estimators often rely on persistent excitation, whereas battery current profiles are usually dictated by operation and may only be informative over finite intervals. To bridge this gap, the thesis adopts novel regression-based tools such as the generalised parameter estimation based observer, dynamic regressor extension and mixing, and non-asymptotic least squares estimators.On this basis, two application-oriented estimation architectures are developed. The first jointly estimates the dominant parameters of a first-order equivalent circuit model and the instantaneous open-circuit voltage from online current and terminal-voltage measurements, and is validated through simulations and experiments. The second extends the plug-and-play perspective to the online identification of parametrised open-circuit-voltage/state-of-charge relations from finite informative intervals. Overall, the thesis shows that useful battery monitoring can be achieved without extensive offline parametrisation campaigns or artificially persistent excitation, thereby supporting more practical battery-management solutions.
  

DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING

• MARANESI, ALESSIA: Elucidating the potential of antimicrobial peptides through biomaterials and advanced in vitro models
  
  Author: MARANESI, ALESSIA
  Programme: DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING
  Department: Department of Materials Science and Engineering (CEM)
  Mode: Normal
  Deposit date: 03/06/2026
  Reading date: 10/07/2026
  Reading time: 11:00
  Reading place: Aula Capella de l'Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB), Av. Diagonal, 647 08028 Barcelona
  Thesis director: FERRARI, ALDO | CERDA CUELLAR, MARTA
  Thesis abstract: Antimicrobial resistance (AMR) represents a major global health challenge, complicating infection management and driving the need for alternatives to conventional antibiotics. AMR is widely recognized as a “One Health” problem, as its causes and consequences span human health, animal systems, and the environment. Implantable medical devices are particularly vulnerable to these complications. Among them, cardiac implantable electronic devices (CIEDs) are highly susceptible to bacterial colonization and biofilm formation, leading to persistent infections, increased patient morbidity, and complex therapeutic interventions. The increasing prevalence of resistant pathogens highlights the limitations of antibiotic-based prevention strategies and underscores the need for innovative approaches.Synthetic antimicrobial peptides (AMPs) have emerged as promising candidates because of their broad-spectrum activity and improved stability. However, their clinical translation remains limited by structural complexity, potential cytotoxicity, and reduced activity under physiological conditions.This thesis focuses on the tetrabranched AMP SET-M33 as a model compound to support its clinical translation in the context of CIEDs. The work combines the study of material–peptide interactions with the development of biomaterial-based delivery systems for local antimicrobial administration. In parallel, an organoid-based screening methodology was developed to provide a physiologically relevant platform for evaluating AMP efficacy and biocompatibility.The first part of the thesis investigates how the physicochemical properties of implant-related materials influence SET-M33 activity. Materials used in CIEDs and their protective envelopes, including titanium, silicon, biosynthesized cellulose, knitted polymeric meshes, and electrospun membranes, were characterized in terms of surface morphology, wettability, and porosity. Peptide transport was quantified through diffusion assays, while antimicrobial efficacy was evaluated using growth inhibition studies against relevant pathogens. Results showed that porous architectures generally favored peptide diffusion, but the balance between diffusion and retention critically determined antimicrobial performance. Biosynthesized cellulose provided the most favorable environment for maintaining peptide activity, whereas other materials either limited peptide availability or reduced efficacy.Based on this findings, the second part of the thesis focused on developing a controlled delivery system for SET-M33 tailored to CIED surfaces. A gelatin methacryloyl (GelMA) hydrogel was engineered as a coating for titanium substrates to encapsulate and release the peptide locally. The system was characterized in terms of peptide loading, release kinetics, degradation, swelling, adhesion, and cytocompatibility. The coating enabled sustained peptide release and strong antibacterial activity, supporting its potential as a localized, antibiotic-free prevention strategy.The third part of the thesis addressed the limitations of conventional preclinical testing of AMP by developing an organoid-based in vitro platform. Organoids were generated and adapted into epithelial monolayers to enable controlled infection and cytotoxicity studies. Experimental conditions were optimized to preserve peptide stability and tissue viability. SET-M33 demonstrated effective antimicrobial activity at tissue-compatible concentrations.Overall, this thesis demonstrates that the efficacy of synthetic AMPs is strongly influenced by interactions with material surfaces and biological systems. By integrating material characterization, controlled delivery strategies, and advanced in vitro models, this work provides a framework for developing AMP-based therapies for implant-associated infections.
  
• RODRÍGUEZ GONZÁLEZ, HELENA: Statistical characterization of laboratory results in pediatric patients for the establishment of reference intervals: a methodological framework for clinical laboratory interpretation
  
  Author: RODRÍGUEZ GONZÁLEZ, HELENA
  Programme: DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING
  Department: Department of Automatic Control (ESAII)
  Mode: Article-based thesis
  Deposit date: 02/06/2026
  Reading date: 09/07/2026
  Reading time: 11:00
  Reading place: Aula Capella de l'Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB). Av. Diagonal, 647, Planta 0, 08028 Barcelona.
  Thesis director: PERERA LLUNA, ALEXANDRE | ARTUCH IRIBERRI, RAFAEL
  Thesis abstract: This doctoral thesis was conducted within the framework of the Laboratory of Inborn Errors of Metabolism at Hospital Sant Joan de Déu and arises from the clinical need to improve the interpretation of biochemical laboratory results in pediatric patients with rare metabolic diseases. In this context, the evaluation of metabolites in blood and cerebrospinal fluid (CSF) in children faces several challenges: a strong age dependency, the influence of multiple physiological and clinical factors, and the lack of true healthy control subjects. These limitations complicate the establishment of reliable reference intervals using traditional approaches based on healthy populations stratified by age groups.The main objective of this thesis is to develop and validate a unified analytical approach to define reference intervals, assess confounding factors—such as medication or inflammation—and characterize metabolic profiles across different pediatric conditions. To this end, several representative use cases affected by these limitations were identified, allowing the applicability of the proposed approach to be evaluated across different types of biomarkers and clinical contexts.As a first use case, CSF neurotransmitters were studied, specifically the metabolites homovanillic acid (HVA) and 5-hydroxyindoleacetic acid (5-HIAA), which are the end products of the dopamine and serotonin pathways, respectively. This scenario presents the additional challenge of the absence of healthy controls, as lumbar puncture is not routinely performed in healthy individuals. Using a cohort of 1,533 pediatric patients, regression models were applied to capture age dependency, and Gaussian mixture models were used to discriminate between deficient and non-deficient populations. This approach enabled the definition of continuous reference intervals that more realistically reflect the biological evolution of these metabolites. It also allowed the correct identification of primary deficiencies and reduced the detection of secondary alterations without clinical correlation.In a second study, the CSF amino acid profile was analyzed in a cohort of 410 pediatric patients, including patients with epilepsy and controls with other neurological disorders. Age-adjusted reference intervals were established, and the impact of antiepileptic medication and clinical variables was assessed using regression models and multivariate analyses. The results revealed a pronounced effect of age and certain pharmacological treatments, particularly on glutamine levels, and enabled the identification of biochemical patterns associated with specific clinical subgroups.Finally, a proof of concept was developed for the establishment of serum copper reference intervals adjusted for age and inflammation, based on a cohort of 1,141 pediatric patients. A multivariate inflammatory index was constructed using partial least squares regression, integrating three acute-phase biomarkers. Incorporation of this index into the model allowed correction for the effect of inflammation on copper levels and improved their clinical interpretation.Overall, these studies demonstrate that the proposed statistical methodology significantly improves the interpretation of pediatric biomarkers, both in cerebrospinal fluid and serum. The developed methodologies reduce false positives, integrate relevant confounding factors, and provide tools that are transferable to other analytes and clinical contexts.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• ASURZA VELIZ, FLAVIO ALEXANDER: Multi-hazard modelling of hydro-geomorphological events for early warning systems. Application to the Val d’Aran (Central Pyrenees, Spain)
  
  Author: ASURZA VELIZ, FLAVIO ALEXANDER
  Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Normal
  Deposit date: 27/05/2026
  Reading date: 15/07/2026
  Reading time: 11:00
  Reading place: UPC Campus Nord, ETSECCPB, C/ Jordi Girona 1-3, edificio C1, Sala 002, Barcelona
  Thesis director: HÜRLIMANN ZIEGLER, MARCEL | DE MEDINA IGLESIAS, VICENTE CÉSAR
  Thesis abstract: Hydro-geomorphological hazards such as floods and rainfall-induced landslides frequently co-occur in mountainous regions, driven by shared meteorological forcing but governed by distinct hydrological and geotechnical mechanisms. Improving their anticipation requires modelling frameworks capable of consistently representing subsurface hydrological conditioning and its interaction with transient triggering processes.This thesis develops and evaluates a physically based, forecast-driven multi-hazard modelling framework for early warning applications in the Upper Garonne River Basin (Val d’Aran, Central Pyrenees, Spain). The research progresses through three interconnected stages. First, an event-based slope stability model is enhanced through a novel multi-objective calibration strategy that explicitly represents both antecedent and final slope stability conditions. Results demonstrate that inadequate representation of subsurface hydrological states leads to physically inconsistent pre-event instability, highlighting the sensitivity of slope response to antecedent moisture conditions.Building on this finding, a continuous distributed hydrological–geotechnical modelling system (SCLAM) is developed to dynamically simulate snowmelt, rainfall–runoff processes, groundwater redistribution, and slope stability within a unified framework. By replacing externally imposed antecedent conditions with internally simulated hydrological states, the model improves physical consistency and identifies Baseflow Excess as a main indicator of destabilizing subsurface conditions.The coupled framework is subsequently extended into a prototype multi-hazard early warning system integrating flood and landslide forecasting under bias-corrected ensemble meteorological forcings. The system operates at 30 m spatial resolution over more than one million grid cells and completes a full forecast-driven multi-hazard simulation cycle in approximately one minute, demonstrating its operational feasibility under real-time constraints. Results show that flood hazard responds primarily to short-term precipitation intensity, whereas landslide hazard is governed by cumulative subsurface conditioning. The asymmetric yet conditionally coupled behaviour of both hazards underscores the necessity of a unified, state-based modelling approach.Overall, this research demonstrates that physically consistent and computationally efficient multi-hazard modelling is feasible for operational early warning in mountainous regions, providing a transferable framework that links improved subsurface representation, hydro-geotechnical coupling, and forecast-driven implementation.
  
• GARCIA RIVERA, JUAN PABLO: ESTUDIO EXPERIMENTAL DE LA CONFLUENCIA DE LOS RÍOS TOLTÉN Y ALLIPÉN (CHILE): RESULTADOS HIDRODINÁMICOS
  
  Author: GARCIA RIVERA, JUAN PABLO
  Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Normal
  Deposit date: 20/05/2026
  Reading date: 28/07/2026
  Reading time: 10:30
  Reading place: UPC Campus Nord, ETSECCPB, C/ Jordi Girona 1-3, edificio C1, Sala 002, Barcelona
  Thesis director: MARTÍN VIDE, JUAN PEDRO | FERRER BOIX, CARLES
  Thesis abstract: This thesis was motivated by the need to understand the hydrodynamic behavior of the confluence of the Toltén and Allipén rivers (Chile), where a bedload measurement campaign was conducted over 90 days in 2013 using a Helley-Smith sampler. During this campaign, gravel and sand transport was recorded with a non-uniform transverse spatial distribution in the measurement section (transect), referred to in this thesis as section 9. However, the lack of simultaneous hydrodynamic measurements prevented the establishment of cause-and-effect relationships between flow and sediment transport distribution.During the field campaign, individual and total flow rates were also recorded, with values ​​between 180 and 900 m³/s. This information served as the basis for developing experimental scenarios in the physical model.The overall objective of this thesis was to understand the hydrodynamic behavior (three-dimensional velocity field) of this confluence in order to identify patterns that can be generalized to confluences with similar characteristics. The physical model was constructed in the Hydraulics Laboratory of the University of Piura (Peru), with a geometric scale of 1:57.9 defined, conditioned by spatial constraints of the model site. The range of flow rates tested in the model varied between 7.7 and 32.8 l/s.The experiments were designed considering different flow combinations, characterized by a Q_tributary/Q_main flow ratio, whose values ​​ranged between 0.33 and 3.97.The experimental campaign included the calibration of triangular weirs for flow control and the definition of boundary conditions through one-dimensional modeling, using information from the prototype.Sixteen cross-sections were measured, with special emphasis on sections 6, 8, 9, and 11, near the reference transect. A total of 1641 three-dimensional velocity measurements (u, v, w) were taken, recorded at 25 Hz for 120 seconds per point, generating more than 3000 data points per measurement.Data processing was performed in Matlab using proprietary algorithms that included correlation and noise filtering (AADV and CADV), application of the Space-Phase Thresholding method, and Wavelet decomposition. The latter allowed the signal to be separated into low-frequency components (pulsations) and high-frequency components (turbulent fluctuations), facilitating a more in-depth analysis of the flow's temporal structure.Additionally, low-frequency pulsations were identified in each measurement; over a 2-minute period, these pulsations were observed to repeat 6 times. The application of dyes visually confirmed these periodic mixing patterns.From the three-dimensional velocity field, different stress components were estimated: Reynolds stress, low-frequency stress, total stress, cross stresses, and near-bottom stresses. The stresses obtained were compared with the critical stress at the onset of movement for a dimensionless Shields parameter of 0.03 (sands and gravels), allowing the identification of potential bed mobilization zones.Finally, the main contribution of this thesis lies in the detailed experimental characterization of the three-dimensional hydrodynamic field at a confluence with morphological unconformity, through the direct measurement of the three instantaneous velocity components and the analysis of their fluctuations. The results obtained provide physical and methodological criteria transferable to the study of river confluences with similar geometric and hydraulic characteristics.
  
• RAHMANI, SAMAN: Scalable error-driven adaptive embedded finite element methods for fluid flow simulations
  
  Author: RAHMANI, SAMAN
  Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Normal
  Deposit date: 09/06/2026
  Reading date: 14/07/2026
  Reading time: 12:00
  Reading place: Sala Zienkiewich (CIMNE) Building C1, UPC - Campus North Gran Capitan S/N 08034 Barcelona
  Thesis director: BAIGES AZNAR, JOAN | PRINCIPE RUBIO, RICARDO JAVIER
  Thesis abstract: Accurate and efficient numerical simulation of fluid flow around complex and moving geometries remains a central challenge in computational fluid dynamics. Traditional domain-fitted mesh approaches require the computational mesh to conform to geometric boundaries, often leading to mesh distortion, costly remeshing, and limited robustness for intricate shapes, thin boundary layers, or large motions. Embedded mesh methods offer an attractive alternative by embedding complex physical domains into simple background meshes, simplifying mesh generation and improving automation and scalability. However, the predominant use of Cartesian background meshes yields uniform spatial accuracy and insufficient resolution in high-error regions, such as boundary layers and strong flow gradients, especially at high Reynolds numbers.This thesis addresses these limitations by developing scalable hybrid strategies that couple embedded formulations with adaptive mesh techniques. Two complementary approaches are employed: the r-method, which improves accuracy through continuous mesh deformation without changing mesh topology, and the h-method, which locally refines or coarsens the mesh based on error indicators. The r-method is first coupled with the embedded finite element method to form the r-EFEM, enabling anisotropic, high-aspect-ratio elements aligned with boundary layers while preserving computational efficiency and parallel scalability. A robust linearization strategy is introduced to efficiently solve the nonlinear mesh optimization problem.To capture localized flow features away from boundary layers, the r-EFEM is further combined with a hierarchical h-refinement strategy with hanging nodes, leading to the proposed r–h EFEM. This hybrid formulation integrates anisotropic boundary-layer resolution via mesh deformation, localized refinement in high-error regions, and geometry-independent discretization within the embedded framework. Hanging-node contributions are incorporated directly into the finite element formulation to preserve conformity and numerical stability, while an error estimator guides adaptive refinement and mesh redistribution.The methods are validated using benchmark problems involving fixed and moving geometries, including high-Reynolds-number flows with thin boundary layers and complex vortex dynamics. The results demonstrate substantial accuracy improvements over standard embedded approaches while maintaining robustness and computational efficiency. In moving-domain simulations, the hybrid framework eliminates remeshing and prevents mesh degradation, enabling stable and scalable transient simulations. This work establishes a unified adaptive framework for accurate embedded finite element simulations in complex and evolving geometries.
  

DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS

• LOPEZ ALVAREZ, CIBRAN: Unveiling correlated charge dynamics and recombination pathways in energy materials via quantum simulations and machine learning
  
  Author: LOPEZ ALVAREZ, CIBRAN
  Programme: DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS
  Department: Department of Physics (FIS)
  Mode: Article-based thesis
  Deposit date: 19/05/2026
  Reading date: 29/06/2026
  Reading time: 10:00
  Reading place: Sala Polivalent de l'edifici A del Campus Diagonal-Besòs
  Thesis director: CAZORLA SILVA, CLAUDIO | SAUCEDO SILVA, EDGARDO ADEMAR
  Thesis abstract: Understanding how atomic-scale mechanisms govern ionic and electronic transport is crucial for the design of next-generation energy materials. Here, we combine first-principles simulations and machine-learning techniques to provide predictive and transferable approaches for modelling and understanding at the atomistic scale solid-state electrolytes and pnictogen chalcohalide (MChX, with M = Bi, Sb; Ch = S, Se; and X = I, Br) photovoltaics.Our first-principles calculations and unsupervised learning investigations revealed that ionic diffusion in solid-state electrolytes is fundamentally governed by correlated motion of multiple ions. These cooperative events are strongly influenced by lattice vibrations, linking ionic conductivity to both vibrational dynamics and elastic properties of the non-diffusive crystal framework. Characteristic correlation lengths, remarkably independent of temperature, were identified, providing new descriptors for the design of fast-ion conductors. In addition, a comprehensive first-principles simulations database and automated analysis tools were developed, offering a scalable platform for understanding ionic transport across diverse material families and compositions.At the same time, first-principles simulations combined with deep learning and device-level modeling identified and experimentally validated MChX-based solid solutions with tunable band-gaps (1.2–2.1 eV) and strong absorption coefficients (up to 66 μm⁻¹), demonstrating the potential of MChX tandems to achieve short-circuit currents exceeding 18 mA/cm². Further ab initio calculations revealed chalcogen vacancies as dominant non-radiative centers in MChX, potentially limiting efficiencies down to 24% in BiSeI. However, targeted anion substitution and synthesis conditions were shown to suppress these detrimental recombination-active centers.Together, the work realised during this doctorate establishes generalizable frameworks that connect atomistic mechanisms to macroscopic device performance. The methodologies introduced here are readily transferable to other families of materials and functional applications, providing a roadmap for the rational design of high-performance, sustainable energy technologies.
  

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

• ROCA NONELL, ALEIX: On the interaction between the Linux kernel and runtime systems
  
  Author: ROCA NONELL, ALEIX
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 27/05/2026
  Reading date: 30/06/2026
  Reading time: 11:00
  Reading place: Sala C6-E106
  Thesis director: AYGUADÉ PARRA, EDUARD | BELTRAN QUEROL, VICENÇ
  Thesis abstract: High-Performance Computing (HPC) underpins scientific discovery and industrial innovation, yet its progress is tightly coupled to how effectively applications exploit modern supercomputers, which consist of thousands of nodes and hundreds of cores. Most supercomputing centers rely on the Linux Kernel at the core of their Operating System (OS). Linux provides applications with the foundation to interface with the capabilities of the underlying hardware, and while it excels in handling sequential and lightly parallel workloads, it might not suffice for highly parallel demands. To bridge the gap between application needs and the OS policy, developers increasingly rely on programming models to express parallelism through fork-join or data-flow dependencies that delegate work distribution to runtime systems. Runtimes simplify parallel programming by hiding Linux complexity and providing user-friendly alternatives that allow developers to focus on their algorithms instead of the underlying OS and hardware details. The coupling between Linux and runtime systems is essential to efficiently map the application's parallel workload to system resources with minimum OS interference and to maximize spatial and temporal locality. This is particularly important as the convergence of HPC, data analytics, and AI is transforming traditional HPC workloads that typically consisted of a single parallelized application into an ecosystem of services that interact with each other, opening new cooperation challenges.This thesis presents a broad exploration of opportunities to tighten the bond between Linux and runtime systems from the I/O, memory, scheduling, and tracing subsystems. We analyze bottlenecks found in real scenarios and design and implement software solutions at both kernel and user level with the aim of improving overall performance, throughput, and latency.On the I/O subsystem, we explore the challenge of integrating blocking operations in runtime systems. Blocking operations are oblivious from the runtime core management perspective and directly affect their capacity to keep cores busy with useful work. Better, seamless detection of such operations has the potential to enable I/O and computation overlapping.On the memory subsystem, we face the challenge of transitioning from traditional homogeneous to heterogeneous memory systems. Traditional systems and applications are designed for homogeneous memory; however, a transparent kernel- or runtime-level solution could enable these applications to exploit the new paradigm without modification.On the process scheduling subsystem, we extensively review the impact of context-switching for fine-grained suspendable tasks. Fine-grained parallel applications are characterized by exposing huge amounts of parallelism while consisting of small computational bursts. These pose a burden to the runtime, which needs to react quickly to keep cores busy with short-lived workloads, and to the kernel, which may need to swap threads on cores. In these cases, the context-switching latency becomes a bottleneck, and improving it can considerably raise performance.Additionally, we analyze the impact of oversubscription on multi-process and multi-runtime workloads. Although these scenarios are usually avoided, the new paradigm powered by the AI adoption makes them increasingly more common. By rethinking the current thread scheduling policies, we can transparently improve performance while maintaining compatibility.Lastly, On the tracing subsystem, we explore the availability of profiling tools for both runtime and kernel and elaborate on the benefits of having a conjoined solution to better understand their interactions, such as the detection of runtime imbalances caused by OS noise.
  
• SHAKESPEAR MILES, HAILEY JOSEPHINE: Multi-Agent Systems for Optical Networks
  
  Author: SHAKESPEAR MILES, HAILEY JOSEPHINE
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 15/05/2026
  Reading date: 09/07/2026
  Reading time: 16:00
  Reading place: Sala de Actos Manuel Martí Recober, FIBC. Jordi Girona, 1-308034 Barcelona
  Thesis director: VELASCO ESTEBAN, LUIS DOMINGO | BARZEGAR, SIMA
  Thesis abstract: Unlike earlier mobile generations, 6G is expected to support a wide range of applications such as immersive communications, remote healthcare, autonomous transportation, and smart cities. These use cases will significantly increase the number of connected devices and impose stringent requirements on bandwidth, latency, reliability, and energy efficiency. As a result, the networks supporting these services will face major challenges in scalability, resource management, and control. In this context, this doctoral thesis investigates the use of Multi-Agent Systems (MAS) as a foundation for next-generation network control. The goal of this thesis is to design and evaluate MAS-based solutions that improve the intelligence, scalability, and energy efficiency of optical networks across both the optical and packet layers.The first objective addresses the optical layer by investigating centralized and distributed MAS-based approaches for dynamic spectrum control in point-to-multipoint (P2MP) connections. A centralized solution based on traffic prediction and integer linear programming computes optimal allocations under near-real-time constraints, achieving high spectrum utilization but introducing synchronization and scalability limitations. To overcome these issues, distributed architectures are proposed in which transponder agents perform decision-making locally. Three strategies are studied: a mixed-strategy gaming model, a distributed deterministic algorithm, and a multi-agent reinforcement learning (MARL) approach. The MARL solution achieves the best overall performance by anticipating traffic variations and allocating capacity proactively, while distributed methods significantly improve scalability and robustness. Communication efficiency is also studied with the MARL approach allowing for asynchronous operation and reducing inter-agent messaging. Results show that distributed MAS can approach centralized performance while avoiding bottlenecks and single points of failure.The second objective focuses on the packet layer, where an extended MAS architecture enables end-to-end near-real-time control of network services (NS) through autonomous flow operation. Routing decisions are driven by telemetry and optimized using Deep Reinforcement Learning (DRL) to minimize delay and operational cost, while agents monitor performance and coordinate with the software-defined networking (SDN) controller. The architecture supports the full lifecycle of a NS, including deployment, dynamic reconfiguration, and handover scenarios. A model-selection approach based on offline training and real-time telemetry is proposed, together with an active probe-testing mechanism and long short-term memory (LSTM) based traffic prediction trained online by flow agents. Simulations demonstrate that transferring of trained models between agents enables accurate predictions and knowledge generation allowing for fast reconfiguration decisions while maintaining QoS over the NS. This MAS architecture provides the foundation for the third objective where experimental results demonstrate reliable QoS maintenance and effective MAS reconfiguration during operation.In conclusion, this thesis shows that MAS combined with learning-based decision-making, predictive analytics, and distributed control provide a flexible and effective framework for managing future networks. The proposed solutions improve scalability, adaptability, and energy efficiency while maintaining strict performance guarantees, establishing MAS as a key enabler for intelligent and autonomous 6G networks.
  
• SORIA PARDOS, VICTOR: Advanced Atomics: Leveraging Memory Hierarchies to Improve Atomic Memory Operations for Next Generation Coherent Manycores
  
  Author: SORIA PARDOS, VICTOR
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 10/06/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: MORETÓ PLANAS, MIQUEL | SUAREZ GRACIA, DARIO
  Thesis abstract: The continuous evolution of multiprocessor and heterogeneous computing systems has led to a dramatic increase in architectural complexity, providing higher throughput and energy efficiency. Such advancements have been boosted by the technological development of chiplet-based architectures, which enable further scaling of transistor count. The downside is that long-standing challenges, such as synchronization and data sharing, continue to worsen. At the heart of synchronization lie atomic memory operations (AMOs), hardware-supported read–modify–write primitives that ensure correctness and coordination among concurrent threads. However, as systems scale toward hundreds of cores, integrate heterogeneous compute engines, and adopt chiplet-based packaging, traditional AMO implementations face serious scalability and latency bottlenecks.This thesis presents a set of architectural and microarchitectural innovations to enhance the efficiency, flexibility, and adaptability of AMOs across future coherent manycore and heterogeneous systems. The thesis addresses three fundamental challenges. First, existing instruction set architectures (ISAs) lack direct support for floating-point atomic operations, forcing programmers to emulate them using compare-and-swap (CAS) loops that degrade performance and increase contention. Second, current AMO implementations employ static policies that determine their execution point, either near the core (in the L1 cache) or far in the memory hierarchy (e.g., at the last-level cache or directory), without adapting to application behavior. Third, far AMOs are typically centralized, meaning that all updates to a memory location are serialized through a single point, creating contention and coherence traffic that limit scalability in chiplet-based and distributed cache architectures.The first contribution extends the Arm architecture with Floating-Point Atomic Memory Operations (FAMOs). FAMOs enable hardware-level atomic operations on floating-point data, removing the need for inefficient CAS-based software constructs. Extensive evaluation across high-performance computing (HPC), graph analytics, and machine learning workloads demonstrates that FAMOs achieve up to 1.58x performance improvement and reduce synchronization latency by over 30%.The second contribution proposes DynAMO, a runtime mechanism that dynamically selects the optimal AMO execution placement based on data locality and reuse patterns. By analyzing temporal reuse and coherence activity, DynAMO predicts whether performing an AMO locally or remotely will minimize latency and data movement. Experimental results show that DynAMO outperforms the best static policy by an average of 1.09x across all workloads, and up to 1.31x in AMO-intensive applications, improving both performance and energy efficiency. The third contribution introduces a new class of delegated and migrating AMOs that eliminate the limitations of centralized far AMOs. Additionally, we propose Delegato, an AMO predictor at the directory level. Delegato allows the coherence directory to delegate the execution of an AMO to the current data owner or migrate the atomic operation to a more suitable cache level, effectively distributing synchronization across the memory hierarchy. Combined with predictive mechanisms that trace locality and reuse, Delegato achieves up to 1.13x speed-up over state-of-the-art approaches while reducing interconnect traffic and cache invalidations in chiplet-based systems.
  

DOCTORAL DEGREE IN EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS

• MOMIN, SAMAR: An AI-Augmented Scalable Framework for High-Resolution Exposure and Seismic Risk Assessment
  
  Author: MOMIN, SAMAR
  Programme: DOCTORAL DEGREE IN EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 13/05/2026
  Reading date: 06/07/2026
  Reading time: 16:00
  Reading place: ETSECCPB.UPC, Campus NordBuilding C1. Classroom: 002C/Jordi Girona, 1-308034 Barcelona
  Thesis director: CARREÑO TIBADUIZA, MARTHA LILIANA
  Thesis abstract: Large-scale high-resolution probabilistic seismic and multi-hazard risk assessments depend critically on how exposure is represented and how appropriately vulnerability functions are assigned to heterogeneous building stocks. While hazard modelling has achieved a high degree of harmonisation and vulnerability modelling has achieved a high level of computational maturity, the exposure–vulnerability interface remains manual, typology-driven and difficult to scale consistently. In Barcelona and across Catalonia, vulnerability functions derived from single buildings or limited samples have frequently been extrapolated across portfolios using coarse classifications. When hazard, exposure and damage-to-loss models are held constant, this practice produces substantial spreads in portfolio loss metrics. It first quantifies that variability through a controlled vulnerability-only sensitivity analysis for Barcelona. Using a consistent probabilistic seismic hazard backbone and unified damage-to-loss mapping, published vulnerability-function sets are interchanged while all other components remain fixed. Results show that Average Annual Loss (AAL) varies from approximately €25.6 million to €348.0 million depending solely on the selected vulnerability dataset, demonstrating order-of-magnitude sensitivity attributable to function assignment. A focused pilot in the Eixample district confirms that detailed, manual reassignment (e.g., corner versus centre block positions) improves local realism but does not scale to city- or regional-level portfolios.To address this structural limitation, the second step moves from ad-hoc assignment toward repeatable and transparent exposure. The thesis develops a geometry-driven exposure structuring workflow through Building Footprint Analysis, Classification and Grouping (BFA/BFC/BFG). High-resolution cadastral building footprints from Catalonia are used to extract dimensions and are transformed into interpretable, reproducible plan-shape classes using previously computed shape metrics to define sides-based classes. Results from comparative analysis of several shape metrics show that simple compactness measures agree on regular rectangles and squares but blur important differences for elongated, irregular and opening-based plans. This reveals redundancy among scalar compactness indices and limited discriminatory power for articulated and opening-based geometries, highlighting the need for an alternative capable of preserving fine-grained distinctions relevant to structural behaviour.The Building Footprint Analysis, Recognition and Classification framework (BFARC-YOLO) builds on this basis to enable scalable AI-augmented exposure classification. Approximately 1.8 million building footprints are rendered as oriented silhouettes and progressively trained using ~0.34% labelled samples. The final model achieves mean average precision (mAP@0.5:0.95) ≈ 0.96 across 44 fine-grained classes. GPU optimisation reduces regional inference time from over 490 hours (CPU baseline) to ~72 hours, demonstrating operational feasibility. Interoperability with the GEM taxonomy enables direct integration into established risk platforms and a lightweight web interface supports auditable batch inference.Rather than developing novel fragility functions, this thesis offers modelling infrastructure. It creates a replicable bridge from cadastral geometry to vulnerability-aligned exposure classification, minimising subjectivity in vulnerability assignment and allowing for scalable, transparent portfolio risk modelling. By reframing exposure as a structured, learning-enabled modelling layer, the study lays the groundwork for future fragility calibration, and next-generation multi-hazard risk assessments for dense and heterogeneous cities, regions, countries and the global scale.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• ROSSI, FRANCESCA: Machine Learning Tools for Power Systems Optimal and Stable Operation
  
  Author: ROSSI, FRANCESCA
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 19/05/2026
  Reading date: 14/07/2026
  Reading time: 11:00
  Reading place: Aula 28.8 Sala Conferències. ETSEIB-UPC
  Thesis director: PRIETO ARAUJO, EDUARDO | GOMIS BELLMUNT, ORIOL
  Thesis abstract: The rapid decarbonization of power systems and the large-scale integration of inverter-based resources (IBRs), high-voltage direct current (HVDC) links, and power-electronics-based technologies are profoundly transforming the dynamic behavior of modern electric grids. These changes introduce new stability challenges, particularly related to small-signal stability, which are not adequately addressed by conventional operational tools. At the same time, system operators face increasing requirements for fast, reliable, and optimal decision-making under highly variable operating conditions.This thesis proposes a comprehensive framework based on machine learning (ML) techniques to support the optimal and stable operation of modern power systems. The core contribution is the development of data-driven surrogate models for small-signal stability assessment and stability performance indicators, enabling their efficient integration into operational decision-making processes. To support this objective, and to address the scarcity of representative training data, an efficient methodology for large-scale synthetic data generation and multidimensional operating space exploration is developed, with particular attention to systems with high penetration of IBRs.Building on these surrogate models, the thesis introduces regression-based small-signal stability constraints that can be embedded into optimization frameworks. In particular, a stability-constrained optimal power flow (SSSC-OPF) formulation is proposed for computing statically feasible and dynamically stable operating points in online operation and operational planning, while a small-signal stability-constrained online feedback optimization (SSSC-OFO) framework is developed to enable continuous, model-free, real-time adjustment of generator dispatch based on measurements.Furthermore, the work addresses the critical role of power electronic converter control by proposing data-driven methods for the selection and assignment of converter control roles in hybrid AC/DC grids. Clustering, dimensionality reduction, and knowledge extraction techniques are employed to identify stability-enhancing control configurations across the system operating space.Finally, a data-driven multi-criteria decision-making framework is presented to support real-time converter control role assignment, combining ML-based performance prediction with operational criteria. Case studies on realistic power system models and academic test systems demonstrate the effectiveness, scalability, and computational advantages of the proposed approaches. Overall, the thesis shows that ML-based tools can significantly enhance the ability of system operators to ensure optimal and small-signal stable operation in future power-electronics-dominated grids.
  

DOCTORAL DEGREE IN ELECTRONIC ENGINEERING

• HERNÁNDEZ URREA, MARC: Design and Implementation of Novel Multiparametric Nonclinical Cardiovascular Assessment Devices Using Only Four Electrodes
  
  Author: HERNÁNDEZ URREA, MARC
  Programme: DOCTORAL DEGREE IN ELECTRONIC ENGINEERING
  Department: Department of Electronic Engineering (EEL)
  Mode: Normal
  Deposit date: 08/05/2026
  Reading date: 09/07/2026
  Reading time: 11:30
  Reading place: sala d'actes de la EETAC (C4-001), campus Baix Llobregat
  Thesis director: CASAS PIEDRAFITA, JAIME OSCAR | CASANELLA ALONSO, RAMON
  Thesis abstract: Cardiovascular diseases remain the leading cause of adverse outcomes and healthcare burden worldwide. The development of extra-hospital cardiovascular (CV) monitoring strategies has become increasingly important, especially after the COVID-19 pandemic exposed healthcare system limitations and the need for alternative screening and monitoring approaches to reduce hospital congestion. Organizations such as the World Health Organization (WHO) highlight that nonclinical devices for cardiovascular disease (CVD) assessment improve treatment adherence, rehabilitation outcomes, survival indices, and contribute to more sustainable healthcare systems. These technologies have also attracted interest from the pharmaceutical industry, as home-based clinical trials and remote patient monitoring provide advantages over traditional trials, including improved adherence, supervision, dose control, and cohort management.Currently, most nonclinical devices rely on electrocardiogram (ECG) or photoplethysmogram (PPG). ECG provides waveform information, time intervals, heart rate (HR), and heart rate variability (HRV), but only electrical heart information. PPG provides arterial pulse wave (APW) morphology, pulse rate (PR), oxygen saturation, and sometimes blood pressure from distal measurements, but only mechanical information limited to superficial arteries. Other systems for deep artery diagnosis, such as SphygmoCor, echocardiography, and cardiac catheterization, remain restricted to clinical environments due to complexity, cost, and need for skilled personnel. Similarly, impedance plethysmogram systems such as impedance cardiography are limited to clinical use, while nonclinical impedance applications are usually restricted to single limbs. Recent advances show that impedance plethysmogram (IPG) measured between limbs can provide information about APW propagation times proximal to the aorta.This thesis presents the design and validation of a novel, easy-to-use cardiovascular assessment device based on simultaneous acquisition of ECG, multiple IPG signals (limb-to-limb and local), and ballistocardiogram (BCG) using only four electrodes in contact with hands or feet and a home weighing scale, together with algorithms to extract cardiovascular health indicators. The device provides information from time intervals between ECG and IPG signals, such as pulse arrival time (PAT), including proximal information from limb-to-limb IPG and distal information from local IPG measurements. These measurements are combined to estimate pulse transit time (PTT), related to arterial elasticity. The combination of hand-to-hand and foot-to-foot IPG PAT enables estimation of a surrogate of aortic PTT (aPTT), typically obtained from carotid–femoral PTT (cf-PTT) using tonometry, a marker associated with ageing and cardiovascular health. The device also enables respiration extraction from limb-to-limb IPG signals without additional sensors.The system was validated through measurement campaigns using reference instruments such as impedance cardiography and tonometry. The devices showed adequate signal-to-noise ratio (SNR: 41 dB and 22 dB) and acceptable CMRR (55 dB and 25 dB). Comparative studies showed good agreement with impedance plethysmography (r > 0.90). Tonometric PAT and PTT estimations agreed with IPG-derived parameters. Wrist-to-wrist IPG PAT correlated with carotid PAT (r = 0.85), and foot-to-foot IPG PAT with femoral PAT (r = 0.86). IPG-derived carotid–femoral PTT showed moderate correlation with tonometer-based cf-PTT (r = 0.67).These results validate the proposed instrumentation and methodology, demonstrating reliable extraction of clinically relevant cardiovascular timing parameters. Overall, a compact system combining ECG and limb-to-limb IPG enables acquisition of relevant proximal and distal arterial information for nonclinical cardiovascular assessment.
  
• VILELLA VEGA, MANEL: Enhanced modulation strategies for a high-efficiency energy conversion system for electric vehicles
  
  Author: VILELLA VEGA, MANEL
  Programme: DOCTORAL DEGREE IN ELECTRONIC ENGINEERING
  Department: Department of Electronic Engineering (EEL)
  Mode: Normal
  Deposit date: 22/04/2026
  Reading date: 28/07/2026
  Reading time: 11:00
  Reading place: Sala de Conferències (TR1-085), campus de Terrassa
  Thesis director: ZARAGOZA BERTOMEU, JORDI | BERBEL ARTAL, NÉSTOR
  Thesis abstract: The global transition toward electric vehicles (EVs) has intensified the demand for high-efficiency power electronics. On-Board chargers (OBCs) and bidirectional energy conversion systems are essential to manage the flow between the grid and the vehicle battery. These systems must be compact, lightweight, and capable of high-power density to satisfy modern automotive requirements. In this context, isolated bidirectional DC-DC conversion, specifically the Dual Active Bridge (DAB) converter, has emerged as a key technology due to its inherent galvanic isolation and high performance. To achieve high power density and efficiency, this research utilizes WBG semiconductors, specifically GaN devices, which allow for higher switching frequencies compared to traditional silicon.The primary objective of this doctoral work is to optimise control and modulation techniques to exploit the full potential of GaN semiconductors while mitigating high-frequency operation challenges, such as parasitic effects, thermal management, and EMI. The research is structured around four main contributions.First, the thesis experimentally evaluates a GaN-based non-resonant DAB converter, analysing the trade-offs between switching frequency, efficiency, and EMI. It demonstrates that increasing the switching frequency up to 200 kHz maintains high efficiency while enabling a significant reduction in the size of passive components without compromising electromagnetic compatibility.Secondly, a mathematical quantification of the steady-state DC current in non-resonant DAB converters is introduced. The formulation, which accounts for semiconductor resistance variations and timing mismatches, is validated experimentally and coupled with a closed-loop voltage compensation control strategy to effectively mitigate these parasitic DC currents.Thirdly, a variable frequency modulation is developed to reduce transient surge currents during start-up and load variations. Finally, the thesis explores the modular series-parallel connection of converters to scale the system for different EV battery voltages.
  

DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING

• CUESTA I MOTA, DÍDAC: Desenvolupament de tecnologies electroquímiques per a l’obtenció d’hidrogen en el tractament d’efluents industrials tèxtils
  
  Author: CUESTA I MOTA, DÍDAC
  Programme: DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 12/05/2026
  Reading date: 14/07/2026
  Reading time: 11:00
  Reading place: Place: ETSECCPBUPC, Campus NordBuilding C1. Classroom: 002C/Jordi Girona, 1-308034 Barcelona
  Thesis director: LOPEZ GRIMAU, VICTOR | CANALS CASALS, LLUC
  Thesis abstract: In the current context of climate emergency and water stress, the textile industry faces the challenge of reducing its high water consumption and its greenhouse gas emissions. This thesis investigates the feasibility of an innovative electrochemical system capable of simultaneously performing the purification of complex waste effluents and the production of hydrogen, thus integrating wastewater treatment with the generation of an energy vector without direct CO2 emissions.The study identifies dye effluents with reactive dyes and mercerizing effluents as the most suitable for the integration of a dual system, thanks to their high conductivity and alkalinity. While mercerizing effluents act as an ideal electrolyte for alkaline electrolysis due to their 20% NaOH content, dye effluents contain recalcitrant azoic reactive dyes that cannot be removed by conventional biological methods, but are highly sensitive to electrochemical oxidation.One of the pillars of the thesis is the design and validation of a sandwich-type bi-compartmentalized electrochemical cell with an anion exchange membrane (AEM). This configuration allows separating the waste effluent at the anode from the alkaline electrolyte at the cathode, avoiding hydrogen contamination and improving the energy efficiency of the treatment. Experimental results demonstrate a decolorization efficiency higher than 99% for diverse reactive dyes and hydrogen generation with a purity of 98,7%. The optimal configuration that balances energy efficiency, treatment time, and material cost for the treatment is also determined, with a current density of 150 mA/cm2 and a combination of a Ni cathode and an Ir-Ru/MMO or BDD anode depending on whether the effluent contains NaCl or Na2SO4.Furthermore, a computer model has been developed using the eCherry library (Modelica) that allows predicting the behavior of the system with a maximum error of 5% in the expected decolorization and 2,1% in the working voltage.In conclusion, the work demonstrates that electrochemical treatment is not only an effective solution for the decolorization of dye effluents but also becomes a strategic pathway for the circular economy, allowing the energy recovery of hydrogen through blending in boilers, and opening the door to the reuse of water, salts, and alkali.
  

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

• BADAKHSHAN, EHSAN: Thermo-Hydro-Mechanical Modeling of Unsaturated Vegetated Slopes
  
  Author: BADAKHSHAN, EHSAN
  Programme: DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 16/04/2026
  Reading date: 10/07/2026
  Reading time: 12:00
  Reading place: ETSECCPB.UPC, Campus NordBuilding C1. Classroom: 002C/Jordi Girona, 1-308034 Barcelona
  Thesis director: VAUNAT, JEAN
  Thesis abstract: The top layer of soil on a slope is highly dynamic, influenced by atmospheric forces and the presence of vegetation. The vegetation condition plays a crucial role in determining the amount of water transpiration and evaporation from the slope surface, thus affecting slope performance by altering temperature, water content, and pore water pressure within the soil mass. Many numerical models often neglect the vegetation impact on soil performance. To capture these effects, this study employs a finite element model in CODE_BRIGHT that integrates vegetation and climate-driven interactions, aiming to bridge the gap between reality and simulation. A specialized boundary condition is developed to simulate soil–vegetation–atmosphere (SVA) processes with hydraulic hysteresis, linking canopy resistance to solar radiation, vapor pressure deficit, and soil saturation. Model validation using three years of field data from the Agropolis slope in Barcelona shows strong agreement, confirming its ability to reproduce vegetation effects on slope hydrothermal behavior. Results reveal pronounced daily temperature variations in the root zone, higher temperatures on south-facing slopes, and stronger drying under vegetation during hot, dry periods.Parametric analysis identifies leaf area index (LAI), root density, and vegetation fraction as key factors influencing soil moisture. Root density and LAI most strongly affect water retention, dense roots lower summer saturation by up to 40%, while high LAI reduces surface drying by 30%. Vegetation fraction enhances winter storage but intensifies summer drying.To better represent unsaturated soils, a hysteretic soil–water retention model is implemented in CODE_BRIGHT, coupling suction and void ratio changes to improve accuracy in scenarios such as rainfall-induced landslides.Finally, an enhanced Barcelona Basic Model (BBM-VEG) is formulated within a thermo-hydro-mechanical (THM) framework. The model introduces a strain-dependent reinforcement factor (Rpveg), correlated with root mass fraction and activation strain, allowing soil stiffness and strength to evolve dynamically. Validated with triaxial and tensile tests, it accurately captures the mechanical response of rooted soils. Slope simulations under hydraulic (infiltration rates of 0.001–0.003 and 0.0005 kg/s) and thermal (15–60 °C) cycles show that vegetation limits infiltration, enhances evapotranspiration, expands the unsaturated zone, and reduces deformation by up to 70% compared to bare slopes.
  
• NEPAL, ANIMESH: Origins of interface jumps, pinning and hysteresis during cyclic fluid displacements
  
  Author: NEPAL, ANIMESH
  Programme: DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 09/06/2026
  Reading date: 17/07/2026
  Reading time: 10:30
  Reading place: ETSECCPB.UPC, Campus NordBuilding B1. Classroom: 003C/Jordi Girona, 1-308034 Barcelona
  Thesis director: DENTZ, MARCO | HIDALGO GONZÁLEZ, JUAN JOSÉ
  Thesis abstract: Immiscible fluid displacements in porous media is governed by the interplay of capillary forces, pore geometry, wettability, and driving conditions. Under quasistatic conditions, this interplay gives rise to metastable interfacial configurations, abrupt interface rearrangements (Haines jumps), interface pinning, and macroscopic pressure--saturation hysteresis. This thesis develops a pore-scale framework to explain how these phenomena emerge and how they can be predicted. The work combines laboratory experiments, numerical simulations in two and three spatial dimensions, and analytical models derived from hydrostatic--capillary pressure balance and interfacial energy arguments. The investigation progresses from simple geometries representing a single pore (ink-bottle and wavy capillaries) to connected porous media (homogeneous and heterogeneous porous media), allowing direct identification of fundamental mechanisms and their collective effects.In single-pore ink-bottle geometries, the results show that interfacial behavior is controlled by a critical geometric condition: below this threshold, interfaces evolve smoothly, whereas above it, interfaces become unstable and jump, resulting in hysteresis during imbibition and drainage. The occurrence and magnitude of jumps depend systematically on the contact angle, surface tension, and constriction angle, and are accurately captured by theory. The thesis then demonstrates that driving mode is also a primary control parameter by analyzing two different capillaries (ink-bottle and wavy capillary tube). Under pressure-driven cyclic displacement, jumps and hysteresis arise from the loss of interfacial stability. Under volume-driven displacement, however, imposed volume constraints suppress jump transitions, eliminate capillary hysteresis, and force the interface to retrace identical imbibition and drainage paths, while interfacial pinning can still occur. In the volume-driven regime, the fluid can traverse tensile and otherwise inaccessible interfacial configurations that are inaccessible under pressure-driven fluid displacement, confirming that the choice of driving mode can decouple pinning and hysteresis. In wavy capillaries, smooth curvature change prevents interface pinning, but pressure-driven displacement can still trigger interfacial jumps. An energy-based analysis shows that pressure changes drive saddle-node transitions between local energy minima, producing jumps and hysteresis. This yields a simple jump criterion that links contact angle to wavy-capillary geometry. Extending these insights to porous media, the thesis shows that homogeneous pore channels can be represented with wavy-capillaries that reproduce key pressure--saturation signatures, including jumps and hysteresis. In heterogeneous porous media, stronger geometric variability generates intermittent collective rearrangements, also known as Haines jump, hysteresis, and return-point memory during internal cycles, evidencing a rugged energy landscape with history-dependent pathways. Together, these results establish a coherent mechanistic link between pore-scale metastability and macroscopic hysteresis. The framework provides predictive tools for controlling displacement efficiency and energy dissipation in applications such as CO$_2$ sequestration, enhanced oil recovery, microfluidics, and capillary transport in natural and engineered porous media.
  
• RODRIGUEZ AGUIRRE, STEPHANIA MABEL: Assessment of Sediment Production, Connectivity, and Delivery in Mountainous Catchments under Environmental Changes. The Role of Shallow Landslides in the Upper Llobregat Basin (Pre-Pyrenees, Catalonia)
  
  Author: RODRIGUEZ AGUIRRE, STEPHANIA MABEL
  Programme: DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 01/06/2026
  Reading date: 02/07/2026
  Reading time: 10:00
  Reading place: ETSECCPB.UPC, Campus NordBuilding D2. Classroom: 216C/Jordi Girona, 1-308034 Barcelona
  Thesis director: HÜRLIMANN ZIEGLER, MARCEL | DE MEDINA IGLESIAS, VICENTE CÉSAR
  Thesis abstract: Soil erosion in mountainous landscapes is strongly influenced by shallow landslides, particularly during extreme precipitation events. Despite their geomorphic significance, quantitative soil erosion studies often prioritize fine sediment dynamics and agricultural land-use calibrations, thereby underrepresenting the complexity of landslide processes driven by intrinsic slope parameters and external triggering forces. This study examines sediment production and connectivity from shallow landslides under climate change and land-cover transitions. The primary objective aims to quantify sediment mobilization from slope instabilities to fluvial networks, focusing on the Saldes River Basin (102 km²) for model calibration and applying the results to the Upper Llobregat River Basin (504 km²).The quantification approach used a distributed, event-based method with the FSLAM landslide stability model. Projected climate scenarios predict increased extreme precipitation events, resulting in heightened slope mass wasting. Future simulations indicate landslide mobilization rates increase by 10%, peaking at 16% during 20-year rainfall events. These findings underscore the significance of hillslope processes in sediment budget assessments and the role of extreme rainfall in sediment production.To address sediment connectivity, this study introduces the Random Connect (RC) model. The model uses a random-walk framework and applies the Index of Connectivity (IC) to estimate sediment volume fluxes from source areas to channel networks. The input data includes a digital elevation model, IC maps, and sediment source maps derived from shallow landslides. The model outputs consist of raster maps that describe sediment flux. The receive maps show accumulated sediment volumes along transfer paths, and the release maps indicate the source cells contributing sediment to the target river.The RC model application in the Saldes Basin highlighted how land cover affects sediment transport. Field surveys identified sediment hotspots and validated model outputs, incorporating forest cover as a factor in connectivity analyses. This enhanced IC methodology delineated transfer pathways, improving overland flow representation in RC simulations. Validation showed an average annual sediment budget of 1,545 t·km⁻²·year⁻¹, with the model estimating a sediment delivery ratio (SDR) of 0.34. Reservoir SDR values ranged from 0.12 to 0.24, illustrating the impact of connectivity thresholds on reservoir siltation. A detailed LULC analysis in the ULRB shows that steep, sparsely vegetated areas have increased by 43%, leading to more bare soil and sediment sources. Conversely, forested slopes and vegetated areas act as buffers, reducing sediment delivery. However, climate projections suggest intensified rainfall and prolonged droughts may reduce vegetation resilience, reactivating sediment pathways. Results show that sediment production increases by up to 22% during extreme rainfall in future scenarios, while forest expansion can reduce sediment yield by up to 14%. Combined climate and land cover scenarios indicate non-linear responses, with far-future events generating up to 18% more sediment than baseline conditions. The findings enhance understanding of sediment dynamics in reservoir-contributing basins, where traditional monitoring struggles to disentangle geomorphic processes. The study underscores the dual influence of forest recovery and extreme rainfall on sediment production and connectivity. The modelling framework provides a robust tool for sediment budget evaluation, aiding watershed management in erosion-prone mountainous areas.
  

DOCTORAL DEGREE IN MARINE SCIENCES

• GONZÁLEZ MOTOS, SERGIO: Long-term dynamics of marine microbiomes: From communities to populations
  
  Author: GONZÁLEZ MOTOS, SERGIO
  Programme: DOCTORAL DEGREE IN MARINE SCIENCES
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 05/06/2026
  Reading date: 06/07/2026
  Reading time: 10:00
  Reading place: Sala de Actos del Instituto de Ciencias del Mar (ICM) - CSICPg. Marítim de la Barceloneta, 37, Ciutat Vella, 08003 Barcelona
  Thesis director: LOGARES HAURIE, RAMIRO ERNESTO
  Thesis abstract: The surface ocean harbours a vast diversity of microorganisms, including prokaryotes (bacteria and archaea), which are key drivers of global biogeochemical cycles. Understanding how these microorganisms respond to environmental variability requires linking patterns across different biological scales, from community-level to population and strain dynamics, to the molecular consequences of adaptive mutations. Chapter 1 investigates two connected coastal microbiomes in the northwestern Mediterranean Sea: the Blanes Bay Microbial Observatory (BBMO) and the Banyuls Bay Microbial Observatory (SOLA). Using seven years of matching metagenomic data, we quantified seasonal rhythmicity and cross-site synchrony across metabolic functions, genes (ORFs), and taxa (OTUs). We found consistent seasonal rhythmicity within each microbiome across organizational levels, yet synchrony between microbiomes remained low. Focusing on 45 key biogeochemical functions, several remained highly rhythmic and synchronous even when their dominant contributing genes showed weak rhythmicity. These results suggest that functional redundancy and complementary dynamics at lower organizational levels can generate coherent functional dynamics through emergent self-organization.Moving beyond community-level patterns, Chapter 2 extended the analysis to distant ocean basins by comparing genome-resolved populations from BBMO (15 years) and MiCRO, California (10 years). We reconstructed 1,535 MAGs in BBMO and 1,068 MAGs plus 187 SAGs in MiCRO. Although the two sites are far apart, species-level overlap was considerable, with 615 genomes with intraspecific (>95% genome similarity) representatives occurring at both sites, whereas strain-level overlap was much lower, with only 17 BBMO genomes matching 20 MiCRO genomes (>99% genome similarity), revealing strong biogeographic structuring at the strain level. Genomes detected in both locations at higher similarity were more strongly associated with temperate coastal environments and tended to be slightly larger, suggesting niche adaptation to coastal conditions. Seasonal genomic variation was widespread at both sites (~70% genomes), while in MiCRO a Prochlorococcus population also showed ENSO-related increases in pN/pS and abundance during strong El Niño years, indicating that long-term climate oscillations can shape marine microbial populations beyond seasonality.Chapter 3 examined adaptation at the gene and protein levels by identifying positive selection across 1,505 MAGs from BBMO and SOLA. Positively selected genes represented less than 0.01% of the metagenomic repertoire, but several were found in both sites, pointing to non-random selection on common functions. These genes were linked to energy metabolism, stress response, regulation, translation/RNA metabolism, cell surface structures, protein turnover and motility, biofilm and environmental interactions, and exhibited contrasting seasonal patterns consistent with heterogeneous selection across cold and warm periods. Of the positively selected genes shared between BBMO and SOLA, the 70.6% also exhibited elevated pN/pS values in at least a subset of Tara samples, suggesting that many of these genes are subject to positive selection at a broader geographic scale. One key example, the RNA pseudouridine synthase (RluA), showed recurrent substitutions linked by structural modeling to increased local protein flexibility, a plausible mechanism for maintaining activity under cold conditions.
  

DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING

• COLLADO CIPRÉS, VERÓNICA: Hot deformation behaviour of WC–Co cemented carbides
  
  Author: COLLADO CIPRÉS, VERÓNICA
  Programme: DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING
  Department: Department of Materials Science and Engineering (CEM)
  Mode: Article-based thesis
  Deposit date: 03/06/2026
  Reading date: 10/09/2026
  Reading time: 11:30
  Reading place: ESCOLA D'ENGINYERIA BARCELONA ESTC/Eduard Maristany, 16 (08019 Barcelona)EDIFICI A planta 0, SALA D'ACTEShttps://meet.google.com/pcm-czdv-rxr
  Thesis director: LLANES PITARCH, LUIS MIGUEL | GARCÍA, JOSÉ LUIS
  Thesis abstract: This PhD thesis presents a systematic approach to describe, model, and understand the hot deformation behaviour of cemented carbides—composite materials based on tungsten carbide (WC) and cobalt (Co), commonly known as hardmetals—under service-like conditions. The work aims to bridge the gap between traditional room-temperature studies and the complex mechanical demands encountered at elevated temperatures.Hardmetals are used in applications requiring extreme mechanical performance, such as cutting tools, mining equipment, and forming dies. Historically, research has concentrated on their room-temperature properties, mainly hardness and fracture toughness. However, such studies do not capture the complex mechanical behaviour at elevated temperatures, where plastic deformation becomes a dominant wear mechanism.Previous investigations into high-temperature deformation have primarily relied on creep testing, which is conducted under very low strain rates and constant stress. While these studies have helped to identify deformation regimes and mechanisms such as grain boundary sliding and binder infiltration, they do not reflect the dynamic, high-strain-rate conditions experienced during actual service, such as in machining operations. Similarly, research on hot hardness has shown that fine-grained WC structures tend to retain higher hardness at lower temperatures but may soften more rapidly at elevated temperatures—highlighting the need for a deeper understanding of microstructural effects under thermal stress.This thesis addresses these critical knowledge gaps by systematically studying the hot deformation behaviour of WC–Co cemented carbides under service-like conditions, with strain rates ranging from 0.0005 to 0.1 s⁻¹ and temperatures from 700 °C up to 1000 °C. The research unfolds in three interconnected stages. The first study investigates sintered cobalt, the binder phase in WC–Co. Through hot compression testing, the deformation mechanisms were characterised, revealing a creep exponent of n = 5 and an activation energy consistent with self-diffusion in face-centered cubic Co. These findings indicate that deformation is governed by dislocation glide and climb.A physically based constitutive equation was developed to describe the peak stress in WC–Co as the sum of three components: stress carried by the binder, stress accommodated by the WC, and stress arising from the interaction between the two phases. The WC phase exhibited an activation energy of 585 kJ/mol, attributed to W pipe diffusion, and a high stress exponent (n = 19), indicating minimal sensitivity to temperature and strain rate—typical of ceramic materials. The interaction term was modelled using the binder mean free path and carbide skeleton stiffness, revealing its significant influence on overall mechanical resistance.The final study incorporated WC grain size into the constitutive model. Experimental results demonstrated that fine-grained WC structures exhibit higher resistance to plastic deformation at lower temperatures due to grain boundary strengthening. However, this advantage diminishes rapidly at elevated temperatures, where grain boundary sliding and binder infiltration become dominant deformation mechanisms. Coarser WC grains, while less resistant at room temperature, maintain structural integrity more effectively under thermal stress. Microstructural analysis via electron back-scattered diffraction confirmed these trends, highlighting the role of grain boundaries, phase transformations, and interface behaviour.These studies provide a framework for understanding and optimizing the high-temperature mechanical behaviour of WC–Co cemented carbides. By bridging the gap between microstructural characterisation and physical modelling, this thesis advances the field beyond traditional room-temperature and creep-based analyses, offering practical tools for designing hardmetals capable of withstanding extreme service conditions.
  

DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING

• CHÁVEZ PEREDA, ERICK DAVID: Study and identification of mechanical parameters while cutting tissues with vibrating hypodermic needles
  
  Author: CHÁVEZ PEREDA, ERICK DAVID
  Programme: DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING
  Department: Department of Mechanical Engineering (EM)
  Mode: Normal
  Deposit date: 10/06/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: SÁNCHEZ EGEA, ANTONIO JOSÉ
  Thesis abstract: Robot-assisted needle insertion is currently under active development for minimally invasive percutaneous procedures due to its potential for high precision and repeatability. However, despite these advantages, the interaction between the needle and soft tissue inherently causes tissue damage, which can compromise targeting accuracy and overall performance. Friction at the needle–tissue interface is the main factor influencing the degree of damage. Therefore, this thesis investigates and models the role of friction in needle–tissue interaction to identify insertion conditions that minimize tissue damage.The factors influencing friction and tissue damage considered in this study were the needle insertion speed and the vibratory relative motion of the needle. To evaluate their effects in ex vivo turkey breast, selected as the tissue model, two tissue damage criteria were employed: the hole size remaining in the tissue after needle withdrawal and the friction force measured during needle withdrawal. A dynamic friction model of the needle–tissue interaction, based on the Dahl model, was developed using these criteria. First, the influence of insertion speed on tissue damage was investigated through controlled experiments at constant speeds. The model parameters were identified from experimental data using the least-squares method. Subsequently, a model-based optimization was performed to determine the insertion speed that minimizes tissue damage, obtaining an optimal value of 4.4 mm/s. Second, the effect of vibration-assisted insertion on tissue damage was analyzed using the same two damage criteria. A custom-designed vibratory actuator was developed to generate axial oscillations during needle insertion. The dynamic friction model was extended to account for the vibratory relative motion, and the corresponding parameters were identified using the least-squares method. A model-based optimization of the extended model was then carried out to determine the optimal vibration frequency, resulting in an optimal range of 800–1100 Hz. This optimization was performed while keeping the optimal insertion speed fixed. Overall, the combination of an insertion speed of 4.4 mm/s and a vibration frequency of 800–1100 Hz was identified as the optimal condition for minimizing tissue damage in ex vivo turkey breast.This thesis proposes a methodology for optimizing needle insertion parameters in soft tissues, based on fundamental principles of needle–tissue interaction. The developed dynamic friction model can be extended to other soft tissues by applying the same experimental procedure to identify the corresponding interaction parameters. This enables the use of a model-based optimization framework to determine optimal insertion conditions in different case studies.
  

DOCTORAL DEGREE IN NETWORK ENGINEERING

• RAMOS LOPEZ, DANIEL: Contribution to TCP Congestion Control Algorithms and Active Queue Management in PEP-Based Geosynchronous Satellite Networks
  
  Author: RAMOS LOPEZ, DANIEL
  Programme: DOCTORAL DEGREE IN NETWORK ENGINEERING
  Department: Department of Network Engineering (ENTEL)
  Mode: Normal
  Deposit date: 22/05/2026
  Reading date: 10/07/2026
  Reading time: 09:30
  Reading place: aula de Teleensenyament edifici B3, campus nord UPC
  Thesis director: MATA DIAZ, JORGE | ALINS DELGADO, JUAN JOSE
  Thesis abstract: The optimization of Transmission Control Protocol (TCP) congestion control algorithms in geosynchronous satellite networks remains a significant research challenge due to high propagation delays, limited bandwidth and dynamic link conditions in such environments. This thesis presents a comprehensive analysis of various TCP congestion control mechanisms and Active Queue Management (AQM) policies in Performance Enhancing Proxy (PEP) geosynchronous satellite environments.The study evaluates three primary TCP variants CUBIC, YeAH and BBRv1 under different AQM configurations, including TBF, CoDel, FQ-CoDel and FQ-PIE. Using a TCP-Splitting Satellite Emulation Framework (TSEF), we analyze the interaction between these TCP congestion control algorithms and AQM techniques to identify optimal strategies for balancing throughput, latency and fairness. Results indicate that while TCP CUBIC remains a robust option in geosynchronous satellite networks, its effectiveness is enhanced with appropriate AQM policies such as FQ-PIE and FQ-CoDel, specially with ECN enabled. These AQMs demonstrate superior latency management and fair bandwidth allocation among different TCP flows.This research contributes to the ongoing development of satellite communication protocols by offering empirical insights into TCP behavior in satellite environments and providing recommendations for optimizing congestion control and queue management strategies. The findings form the basis for improving real-world satellite internet performance, particularly in applications demanding low-latency and high-throughput connectivity.
  

DOCTORAL DEGREE IN PHOTONICS

• DOSIL GARCÍA, MIGUEL: Optical Spectroscopy of Infrared--Emitting Colloidal Quantum Dots: From Ensemble to Single Particles
  
  Author: DOSIL GARCÍA, MIGUEL
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 10/06/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: KONSTANTATOS, GERASIMOS
  Thesis abstract: Colloidal quantum dots (CQDs) have established themselves as a key technology in optoelectronics due to their high efficiency, versatility, and low manufacturing costs. Their application in light generation has evolved from statistical thermal emission in visible LEDs and fluorescence converters toward more sophisticated sources, such as lasers and quantum light emitters. However, their implementation in the infrared (IR) has proven more complex due to an inherently low photoluminescence quantum yield (PLQY), with efficient applications emerging only recently. Given the growing interest in quantum technologies, single photons in the infrared telecommunications C-band have become a fundamental pillar, a domain where these colloidal technologies offer superior flexibility. Specfifically, CQDs based on Pb chalcogenides and III-V semiconductor alloys bridge the gap between cost and integration thanks to the tunability of their emission properties within this spectral region. This work presents an optical spectroscopy characterization of PbS and InSb CQD dispersions and films, employing steady-state and time-resolved micro-photoluminescence (u-PL) techniques at low temperatures. To this end, the complete design and implementation of the utilized optical system are detailed, including alignment and optimization protocols, as well as the algorithms developed for performing confocal u-PL mapping with micrometric resolution. Power-dependent PL studies on PbS films reveal a collective behavior characterized by a bimolecular recombination regime within a band with an exponential-type density of states (DOS), which contrasts with the excitonic behavior observed in solution. Furthermore, the PLQY of these samples shows a marked linear dependence on size, reaching a maximum of ~30\% for quantum dots with excitonic peaks around 1.5 eV and steadily decreasing toward larger particles. Time-resolved PL measurements indicate the existence of energy transfer mechanisms between CQDs with long diffusion times. Encapsulation tests confirm that oxygen acts as a highly degrading agent, quenching emission after moderate exposure to ambient conditions. InSb CQDs exhibit extreme sensitivity to oxidation, losing their PL within seconds upon contact with air. Temperature-dependent PL measurements further reveal the presence of a surface-associated emission band at cryogenic temperatures, which rapidly disappears upon heating the sample or adding a thin InP shell. Two strategies were explored to reach the single-particle regime. In contrast to the common use of spin-coating, dip-coating of dilute solutions proved effective for obtaining isolated CQDs with controlled areal density, albeit at the cost of significant luminescence degradation; this suggests irreversible damage to the crystal surface due to ligand stripping subsequently oxidating the surface. As an alternative for protecting particles from external agents, PbS CQDs were encapsulated in thick silica shells using a microemulsion method in combination with surface chemistry engineering, succesfully allowing a high yield of single CQD to silica particle. The results presented in this thesis highlight critical limitations in the current implementation of IR-emitting CQDs as quantum light sources, underlining the need to develop new synthesis routes and coating chemistries to improve their optical properties and ensure long-term stability. Additionally, the experiments conducted on films provide relevant perspectives for the optimization of technologies based on infrared CQDs, such as LEDs, photodetectors, or lasers.
  
• HERNANDEZ RUIZ, MARÍA: Cavity-Enhanced, Optically Pumped Magnetometry and its Miniaturization
  
  Author: HERNANDEZ RUIZ, MARÍA
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 26/05/2026
  Reading date: 07/07/2026
  Reading time: 15:00
  Reading place: ICFO Auditorium
  Thesis director: MITCHELL, MORGAN | LUCIVERO, VITO GIOVANNI
  Thesis abstract: This thesis presents the development and experimental implementation towards a miniaturized cavity-enhanced atomic magnetometer designed for high sensitivity and high spatial resolution. The proposed technique relies on a cavity-based optical readout of atomic polarization using the Pound Drever Hall technique.The magnetometer was experimentally realized and characterized, including a design compatible with biological measurements. The magnetometer can operate with one endcap open in a weak shielding environment (only only layer of mu-metal.) The system was applied to the study of magnetotactic bacteria, whose magnetic response arises from the alignment and relaxation dynamics of intracellular magnetosome chains. Time resolved measurements of the magnetic signal were analyzed assuming exponential relaxation. Furthermore, the model was expanded using a stochastic model to detect deviations from exponential behavior associated with sample evaporation.The achieved sensitivity and stability of the magnetometer enabled the reliable detection of magnetic signals on the nanotesla scale, with a sensing characteristic length Lat=1.5 mm. These results demonstrate the potential of cavity-enhanced atomic magnetometry for the investigation of biological magnetic systems. This work establishes a versatile platform for high-sensitivity magnetic measurements and opens promising perspectives for future applications in biophysics and magnetic microscopy.
  
• MORENO ABAJO, ÁLVARO: Optical investigation of 2D materials with in-plane engineering: exciton confinement and chirality sensing
  
  Author: MORENO ABAJO, ÁLVARO
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 11/05/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: KOPPENS, FRANK | RESERBAT-PLANTEY, ANTOINE
  Thesis abstract: Two-dimensional (2D) materials provide a powerful platform for nanoscale engineering and control of geometry and energy landscapes without directly modifying the material, owing to their interfacial nature. This thesis explores how we can harness this potential by introducing in-plane engineering in van der Waals heterostructures. We present two case studies: in one, the exciton dimensionality is reduced using a designed 1D electrostatic trap; in the other, twisting two monolayers yields a chiral configuration that modifies the interaction with other chiral systems. Together, these two parts demonstrate how inplane symmetry breaking (translational and mirror symmetry, respectively) in 2D material platforms enables new modalities of control and sensing.In the first part, we investigate electrostatically defined confinement of intralayer excitons in MoSe2. A p–i–n junction is induced in the monolayer by asymmetric gating, creating a tight 1D potential with an effective exciton confinement length down to 10nm. Combining photoluminescence and reflectance-contrast spectroscopy, we resolve a discrete spectrum of localized states arising from center-of-mass quantization, with linear polarization aligned with the trap geometry, consistent with confinement-enhanced valley-exchange interactions. Importantly for the development of this technique, we show that the confinement potential cannot be understood as a purely electrostatic effect. Illumination reshapes device operation by inducing dissociation-driven photo-doping and Auger-assisted charge extraction, thereby stabilizing a working p–i–n configuration. We resolve photoinduced carrier-redistribution dynamics on the scale of seconds and demonstrate that their dependence on excitation position produces sharp switching between confined and unconfined excitonic responses. A rate-equation description captures the competition between dissociation and Auger processes, highlighting a route to nonlocal optical control of carrier density and, consequently, of the confinement potential. Programmable excitonic potentials that reach the 0D limit could enable quantum technologies such as single-photon sources or optically addressable qubits, and open a route toward strong exciton–exciton interactions and Bose–Hubbard physics.In the second part, we leverage the structural chirality of twisted bilayer graphene (TBG) to realize a novel enantiomeric sensing strategy based on chirality-dependent non-radiative energy transfer. In the presence of TBG, the decay rate of chiral fluorophores is modified depending on handedness matching between molecule and substrate, which we read out by measuring the fluorescence lifetime in time-resolved photoluminescence experiments. The observed asymmetry is statistically tested by spatially resolving the enantioselective contrast, observing a sign reversal upon inversion of the TBG handedness, and exploring the role of the twist angle as a control parameter. We quantify the effect of chirality through a lifetime-based dissymmetry factor that reaches the 1 – 10% level, implying an enhancement of several orders of magnitude compared with the natural optical circular dichroism of both the molecule and TBG. The presented approach is conceptually distinct from schemes that rely on electromagnetic field engineering, and achieves sensitivities down to the single-molecule layer without requiring surface functionalization. This opens the door to developing a platform with tunable, strong chiral light–matter interactions with implications in optics, sensing, and chemistry, including chiral catalysis and homochiral synthesis.
  
• SRIVASTAVA, ANUBHAV KUMAR: Quantum simulations of spin systems for optimal quantum metrology
  
  Author: SRIVASTAVA, ANUBHAV KUMAR
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 01/06/2026
  Reading date: 29/06/2026
  Reading time: 10:30
  Reading place: Mir-Puig Elements
  Thesis director: LEWENSTEIN, MACIEJ | PLODZIEN, MARCIN
  Thesis abstract: Quantum mechanics both constrains and empowers precision measurement: the uncertainty principle imposes fundamental limits on parameter estimation, which quantum resources such as entanglement and superposition can saturate. Quantum metrology develops protocols that exploit non-classical probe states and optimal data processing to surpass the standard quantum limit. In practice, however, realizing this advantage requires solving three problems: designing experimentally feasible many-body probes with near-optimal sensitivity, certifying metrological resources from incomplete measurement data, and implementing optimal readout schemes that remain tractable at scale. This thesis develops a unified framework for all three challenges, combining quantum simulation, convex optimization, and classical-shadow techniques to bring quantum-enhanced metrology closer to experimental reality.The first part addresses quantum thermometry at nano- and sub-nanokelvin scales. Using the quantum Fisher information (QFI) as the sensitivity measure, we show that an experimentally accessible system of spinless fermions in a one-dimensional optical lattice, described by the Rice–Mele (RM) model, realizes a near-optimal local quantum thermometer approaching the fundamental Cramér–Rao bound. We characterize how the topological and trivial regimes, the lattice filling, and a tunable staggered potential control its sensitivity, and show that the probe equilibrates with a coupled bath without perturbing it. We further analyse a global thermometry scheme based on classical-shadow tomography of thermal states, comparing its sample complexity with standard protocols.The second part develops two complementary tools for quantum-enhanced sensing and its certification. We introduce a sensor based on a frustrated Kitaev trimer whose nonlinear spectral response implements a thresholded rectifying detector: for a zero-mean omnidirectional signal, the accumulated phase vanishes below a tunable threshold and, above it, is proportional to the signal's second moment. Entangled multi-trimer configurations attain Heisenberg-limited sensitivity. We then formulate a semidefinite programme (SDP) that computes the minimal QFI compatible with incomplete expectation-value data, yielding rigorous lower bounds without full state tomography. Applied to multi-headed cat states generated by one-axis-twisting dynamics, the SDP certifies metrological usefulness from low-order moments more tightly than conventional squeezing inequalities.The third part addresses the gap between optimal measurement schemes and the measurements achievable on current quantum platforms. The optimal observable saturating the quantum Cramér–Rao bound is generically a highly nonlocal operator whose Pauli weight grows with system size. We introduce Clifford lensing, a framework in which classically simulable Clifford circuits map the optimal observable onto an operator of reduced Pauli weight, refocusing distributed phase information onto fewer qubits. We establish a correspondence between quantum error-correcting codes and interferometric constructions enforcing deterministic phase kickback, and develop metrologically sufficient partial-shadow tomography protocols that preserve the full QFI. The resulting schemes require exponentially fewer samples than naïve shadow estimation and are validated on liquid-state nuclear magnetic resonance (NMR) systems of up to 15 qubits.Together, these results demonstrate that near-optimal quantum metrology is achievable with accessible probes, data-efficient certification, and scalable readout, providing a unified route from fundamental metrological bounds to practical quantum-enhanced sensing.
  

DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS

• QUINTANA ROMERO, DULCE ALITZEL: Synthesis of non-natural amino acids, peptidomimetics, and electrochemical characterization of the structures obtained by self-assembly
  
  Author: QUINTANA ROMERO, DULCE ALITZEL
  Programme: DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS
  Department: Department of Chemical Engineering (EQ)
  Mode: Change of supervisor
  Deposit date: 15/06/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: ALEMAN LLANSO, CARLOS ENRIQUE | BUCCI, RAFFAELLA | GELMI, MARIA LUISA
  Thesis abstract: The use of non-natural amino acids (AAs), such as β-AAs, to produce peptidomimetics is becoming very attractive, as they are sequences with the same biological activity as the natural peptides but with enhanced proteolytic and conformational stability. In addition, the ability of peptidomimetics containing non-coded AAs to self-assemble and self-organize allows their use in wide and variable applications, from nanomedicine to electrochemistry and catalysis, as well as for bioelectronic materials. This versatility of peptidomimetics makes them an exceptional tool for the design of novel materials.This Thesis focuses on the synthesis of peptidomimetics containing non-natural β-AAs. The main inspiration was an unnatural fluorine-substituted β2,3-diarylAA, synthesized for the first time in our laboratory, by a stereoselective Mannich-like reaction. The presence of an additional carbon atom in the β-AA backbone can give rise to four possible stereoisomers. For this reason, it is also feasible to play with the stereochemistry of the β-AA, obtaining different peptidomimetics and accordingly nanostructures. Different non-natural AAs were synthesized, showing the ability of α,β-peptides to self-assemble into different supramolecular structures. This Thesis provides an in-depth analysis of various peptidomimetic applications, aiming to contribute to the understanding of the impact of the molecular design on the corresponding functional performances. Therefore, a rational molecular design can be used to develop advanced peptide-based systems with multifunctional properties.Peptidomimetics were studied from their ability to act as antimicrobial peptides (AMP). Their biological activity was examined towards Gram-positive and Gram-negative bacteria, as well as a bacteriophage virus. The dependence of the antimicrobial activity on stereochemistry, self-assembly, and the chemical nature of the antimicrobial moiety, demonstrated the structure-function relationship of peptidomimetics. Additionally, drug delivery systems were developed by combining peptide–drug coassemblies with carboxymethyl cellulose (CMC) hydrogels for controlled antimicrobial release. The release of curcumin (CUR) as model was analyzed from electrically responsive wound-dressing platforms, demonstrating the effective controlled release of CUR. Furthermore, this Thesis explores the conductive properties of peptidomimetics for the engineering of conductive devices. It was found that the introduction of an electroresponsive peptide in the conducting polymer (CP) PEDOT, has a positive impact in the development of peptide-based electrodes, enhancing conductivity and sensitivity, as well as amplifying the peptide electrical response. PEDOT/peptide electrodes were used as biosensors to detect Nicotinamide Adenine Dinucleotide (NADH), an important biomarker for diagnosing infection diseases. Additionally, multilayered electrodes, where the intermediate peptide film act as dielectrics connecting in parallel the two PEDOT layers, demonstrated effectiveness as electrodes for electrochemical symmetric supercapacitors. In summary, we demonstrated that the incorporation of peptidomimetics in the field of bioelectronics opens new avenues for biomedical applications.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• CHEN, YAOGANG: Multi-Temporal Polarimetric InSAR Deformation Monitoring Considering Spatiotemporal Scattering Variability
  
  Author: CHEN, YAOGANG
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Change of supervisor + Article-based thesis
  Deposit date: 28/05/2026
  Reading date: 26/06/2026
  Reading time: 08:00
  Reading place: Room 214 of the Geosciences Building,
  Thesis director: MALLORQUI FRANQUET, JORDI JOAN | HU, JUN
  Thesis abstract: Interferometric Synthetic Aperture Radar (InSAR) enables millimeter-level measurements of surface deformation over large areas and long time spans, and has become an important tool for geohazard monitoring and infrastructure safety assessment. However, in natural environments with dense vegetation, intensive agricultural activity, or strong surface disturbance, rapid variations in scattering mechanisms often cause severe coherence loss, which significantly limits the accuracy and density of deformation monitoring. By introducing multi-polarization observations, multi-temporal Polarimetric InSAR (MT-PolInSAR) improves InSAR performance in complex low-coherence scenarios. Nevertheless, existing MT-PolInSAR methods still face two major limitations: insufficient consideration of the spatial and temporal variability of scattering mechanisms, and inadequate exploitation of the complementary information in the polarimetric, temporal, and spatial domains within a unified framework.To address these issues, this thesis investigates phase optimization and deformation monitoring for MT-PolInSAR under low-coherence conditions. A systematic methodology is developed by exploiting the redundancy and scattering information contained in polarimetric SAR data, including homogeneous filtering for small datasets, polarimetric phase optimization with spatially varying scattering mechanisms, joint phase optimization in the temporal and polarimetric domains, and sequential near-real-time processing.First, a homogeneous filtering method for MT-PolInSAR small datasets is proposed. By introducing spatial covariance structures and jointly exploiting temporal and polarimetric redundancy, the method improves pixel discrimination and enhances the signal-to-noise ratio. Experiments on simulated data and Barcelona Airport data demonstrate improved phase quality, more stable coherence estimation, and better preservation of spatial structures.Second, an improved polarimetric phase optimization method, termed ImESPO, is proposed to account for spatial variations in scattering mechanisms. Unlike conventional methods, it explicitly considers local scattering heterogeneity during polarimetric projection. Results show that ImESPO achieves more stable coherence gains and phase consistency in heterogeneous areas, improving phase estimation accuracy by more than 20%.Third, a joint phase optimization model combining the temporal and polarimetric dimensions, termed JPTPO, is developed. By jointly modeling both dimensions within a unified statistical framework, the method achieves improved phase consistency and more stable deformation inversion results on both simulated and real datasets.Finally, a near-real-time MT-PolInSAR deformation monitoring method is proposed for rapid-decorrelation scenarios. Applied to landslide monitoring in the Fengjie area of the Three Gorges Reservoir, the proposed method increases measurement density by a factor of four and improves monitoring accuracy from 18.4% to 71.8%, while maintaining near-real-time capability.Overall, this thesis advances the theory and methodology of MT-PolInSAR deformation monitoring in complex low-coherence environments, providing new solutions for high-precision and continuous monitoring of landslides and other geohazards.
  
• JADOON, MUHAMMAD AWAIS: Machine Learning-based Random Access Techniques for Massive Connectivity
  
  Author: JADOON, MUHAMMAD AWAIS
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 08/06/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: NAVARRO RODERO, MÒNICA | PASTORE, ADRIANO
  Thesis abstract: Massive machine-type communication (mMTC) underpins the 5G-and-beyond vision of supporting ultra-dense networks of low-complexity, low-power, battery-operated devices whose traffic characteristics differ significantly from traditional human-type communication, being more sporadic, uncoordinated, and often event-driven. Managing medium access for such a massive number of devices is a central challenge in mMTC. Traditional scheduling or grant-free Random access (RA) approaches often incur excessive signaling overhead, high collision rates, and offer limited adaptability in environments where traffic patterns vary. This necessitates the design of novel medium access schemes that can scale to massive numbers of devices.In this thesis, we employ multi-agent reinforcement learning (MARL) to design distributed grant-free RA policies that accommodate dynamic traffic conditions and provide service to large populations of devices. We first develop a single-channel environment where the devices learn transmission policy using one-bit broadcast feedback and local packet buffer states using the Deep Q-Learning (DQN) algorithm. Although this approach surpasses baseline Exponential Backoff (EB) techniques in terms of throughput and fairness under regular (Poisson) traffic, it relies on a single-agent training framework and does not fully exploit the Centralized Training and Decentralized Execution (CTDE) principle. Recognizing the importance of scalability and effective coordination in large networks, we next adopt advanced MARL algorithms—Value Decomposition Networks (VDN) and QMIX, in which a global Q-value is computed from individual Q-values, thus leveraging global network information during training.To evaluate fairness, we introduce the age of packet (AoP) metric, which quantifies the staleness of untransmitted packets in device buffers. We then extend our models to accommodate bursty and correlated traffic arrivals, demonstrating that the proposed MARL schemes can adapt effectively to sudden device activation or shifting arrival patterns. We also investigate how user identification impacts policy learning and fairness, as devices may dynamically join or leave the network. We show how these design choices can influence fairness and allow devices to leave/join the network. Additionally, we broaden the scope beyond a single channel, incorporating multiple orthogonal resources to highlight the generality of these approaches. Throughout our extensive simulations, all MARL-based methods consistently outperform EB schemes. Our findings underscore the promise of MARL-driven solutions for mMTC and future wireless systems.
  

DOCTORAL DEGREE IN STRUCTURAL ANALYSIS

• GUO, ZHIMING: Study on HTPB propellant passivation, mixing, casting and curing processes by experiment and simulation
  
  Author: GUO, ZHIMING
  Programme: DOCTORAL DEGREE IN STRUCTURAL ANALYSIS
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 11/05/2026
  Reading date: 04/09/2026
  Reading time: 12:00
  Reading place: UPC Campus Nord, ETSECCPB, C/ Jordi Girona 1-3, edificio C1, Sala 002, Barcelona
  Thesis director: ROSSI BERNECOLI, RICCARDO | FU, XIAOLONG
  Thesis abstract: This study investigates the key physical issues involved in the four propellant production steps (passivation, kneading, casting, and curing) through a combination of experimental and numerical simulations.In this experimental study using HTPB propellant ingredients as raw materials, we first investigate the passivation and dehydration (similar to reduced pressure micro-boiling) of this raw material (N-butylnitroxyethylnitramine (BuNENA)). Next, we add other materials (including liquids and granules) to the passivated raw material and mix them in a vertical kneader. The resulting propellant slurry is then cast into a specific mold. Finally, we investigated the solidification of the propellant samples formed in the mold.In this numerical simulation study, First, the passivation process (bubble generation and movement) of the BuNENA material was studied through numerical simulation. Next, the mixing process of the propellant in a vertical kneader was investigated. The uniformity and flow characteristics of the HTPB propellant material were studied under stirring conditions.Finally, the slurry casting process was simulated, and finally, the curing of the cast propellant model was simulated.This paper contains the following research contents:(1) A passivation experimental device was established and experiments were carried out using a principle similar to reduced pressure micro-boiling; in the fluid dynamics simulation model, the Lagrangian framework was applied to track the formation and movement of bubbles, and the bubbles themselves were modeled as rigid spheres subjected to buoyancy and viscous forces. The Euler framework based on variational multiscale (VMS) was used to simulate the fluid around the bubbles. The bubble movement was analyzed. By combining experimental and simulation methods, the passivation process of BuNENA was analyzed in detail, which is of substantial significance in the field of passivation of composite solid propellants.(2) A computational fluid dynamics (CFD) method was used to establish a digital simulation model of the mixing process of the vertical kneader. Changes in various flow field related characteristics of the vertical kneader were analyzed. The mixing performance of the propellant slurry in the kneader was studied by establishing a mixing uniformity index analysis method. The accuracy of the simulation results was verified by real kneading experiments, SEM-EDS and density experiments. (3) The vacuum casting process was optimized by combining experiments and numerical simulations. First, the shear thinning behavior was revealed through rheological tests, and the Herschel-Bulkley model parameters confirmed non-Newtonian fluid characteristics. The variational multi-scale finite element method was used to simulate and analyze the vacuum casting process of HTPB propellant slurry. Second, the flow rate and impact force of droplets under different vacuum pressures were studied by combining real-time image recognition with machine vision and Kalman filtering. (4) Finally, the curing reaction kinetic model of HTPB propellant was studied by the non-isothermal DSC method. The distribution and evolution of the internal temperature and temperature degree of the propellant during the molding process were analyzed using a thermochemical model. The temperature gradient and curing time variation of the propellant curing process were explored by the thermocouple-integrated method.
  

DOCTORAL DEGREE IN SUSTAINABILITY

• ACEVEDO ROCHA, ALFONSO DARÍO: Modelo de gestión para la restauración del suelo dedicados a la actividad ganadera en el departamento de Córdoba, Colombia. Un aporte de la ganadería regenerativa al desarrollo sostenible del territorio- estudios de casos comparativos
  
  Author: ACEVEDO ROCHA, ALFONSO DARÍO
  Programme: DOCTORAL DEGREE IN SUSTAINABILITY
  Department: University Research Institute for Sustainability Science and Technology (IS.UPC)
  Mode: Normal
  Deposit date: 04/06/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: MORATO FARRERAS, JORDI
  Thesis abstract: The impact of livestock farming on soil degradation has been widely discussed, with cattle production being attributed a significant impact both globally and locally. This research, entitled "Management model for the restoration of land used for livestock farming in the department of Córdoba, Colombia. A contribution of regenerative livestock farming to the sustainable development of the territory - Comparative case studies," analyzes the evolution of regenerative livestock farming, especially in Latin America, and adapts a methodology to evaluate the efficiency of this model on the soil using biological and spatial indicators, comparing it with a conventional model on farms in Córdoba. It also evaluates the contribution of these models to the Sustainable Development Goals (SDGs) and proposes a conceptual model for the sustainable management and restoration of livestock soils.An analysis was carried out on the progress of regenerative livestock farming worldwide and in Latin America, finding a significant increase in its adoption since 2018, especially in 2019, when the preservation of biodiversity, water, and soil health began to be valued.Macro indicators of soil condition were defined and 12 farms were selected to analyze conventional and regenerative production models. Edaphic macro and mesofauna were evaluated, satellite images were analyzed, and information on vegetation cover was collected, using biological and spatial indicators to measure the restorative capacity of the models. A SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis was also conducted, concluding that the regenerative model is more efficient in grazing practices, profitability, and biodiversity, allowing for passive restoration of the ecosystem.A methodology was developed to analyze the efficiency of regenerative livestock farming, establishing methods for collecting biotic and spatial data, which facilitates continuous soil diagnosis and monitoring. The study area, the duration of the analysis, the phases of the process, the indicators, and the multitemporal analysis of the plant component were defined using remote sensing and GIS technologies, providing the necessary data for a detailed analysis. It was concluded that regenerative livestock farming is an economical and sustainable low-cost model that improves productivity without agrochemicals and prevents erosion, promoting soil restoration through sustainable practices.This model also contributes to the fulfillment of the SDGs, especially in food security, climate action, and ecosystem restoration, promoting greater biological biodiversity and vegetation cover in the study areas. The results show a positive impact on soil health, vegetation development, and macrofauna, with notable root growth and no degraded soils. Regenerative livestock farming works in harmony with nature, improving the living conditions and health of livestock.Regenerative livestock farming is presented as a key tool for addressing the environmental, social, and productive challenges of livestock farming, restoring soils and ecosystems, and reversing the damage caused by overgrazing and the use of agrochemicals in conventional models. It restores soil fertility, promotes a natural cycle of regeneration, and facilitates the recovery of native species of flora and fauna, increasing the ecosystem's resistance to external disturbances.In terms of species abundance, a total of 763 individuals were quantified between both systems, distributed across 19 taxonomic orders, with 630 individuals in the regenerative model and 133 in the conventional model. The Shannon-Wiener Index (H') under the regenerative model was 2.06, reflecting high biological diversity and efficiency in restoration and long-term sustainability.
  
• RHOUMA, ALI: Operationalizing the Water–Energy–Food–Ecosystems Nexus for the Sustainability Assessment of Mediterranean Farming Systems
  
  Author: RHOUMA, ALI
  Programme: DOCTORAL DEGREE IN SUSTAINABILITY
  Department: University Research Institute for Sustainability Science and Technology (IS.UPC)
  Mode: Normal
  Deposit date: 24/04/2026
  Reading date: 16/07/2026
  Reading time: 12:30
  Reading place: Salón de Grados de la EEABB Campus of Castelldefels
  Thesis director: GIL ROIG, JOSE MARIA | BROUWER, FLOOR
  Thesis abstract: Agricultural systems face increasing pressures from water scarcity, climate change, and environmental degradation, particularly in the Mediterranean region where resource constraints are intensifying. Addressing these interconnected challenges requires integrated analytical approaches capable of capturing the complex interactions between water, energy, food production, and ecosystems. The Water–Energy–Food–Ecosystems Nexus has emerged as a promising framework for supporting sustainable resource management; however, its operationalization at the farm level remains limited. This thesis aims to advance the application of the WEFE Nexus for the sustainability assessment of farming systems by developing an integrated analytical framework and practical evaluation tools.The research adopts a progressive methodological approach. First, water-related sustainability indicators specifically the water footprint and water scarcity footprint are applied to assess the pressures of agricultural production on water resources. These indicators provide an initial understanding of resource use efficiency and highlight critical water-related challenges in farming systems. Building on this foundation, the thesis develops a WEFE Nexus assessment framework based on system dynamics modelling to capture interactions between water use, energy consumption, food production, and ecosystem impacts. The framework is implemented through a user-friendly decision-support tool designed to support sustainability assessments at the farm level.The developed framework is subsequently applied to evaluate WEFE Nexus solutions in agricultural systems, with a particular focus on agroecological practices. By integrating multiple indicators related to resource efficiency, environmental performance, and agricultural productivity, the analysis explores how agroecological approaches influence the performance of farming systems within the WEFE Nexus. The results demonstrate that agroecological practices can improve resource use efficiency, reduce environmental pressures, and enhance the resilience of farming systems.Finally, the outcomes of the WEFE Nexus assessment are translated into key performance indicators linked to the Sustainable Development Goals (SDGs). This step enables the quantification of how WEFE-based agricultural practices contribute to broader sustainability objectives and global development targets. By linking farm-level sustainability assessment with the SDG framework, this research provides a novel methodological contribution for evaluating the sustainability impacts of agricultural practices.This thesis contributes to bridging the gap between WEFE Nexus theory and practical agricultural sustainability assessment. The proposed framework offers a robust approach for evaluating sustainable farming systems and provides valuable insights for policymakers, researchers, and stakeholders seeking to promote resilient and resource-efficient agriculture in the Mediterranean region and beyond.
  
• VILLANUEVA ESCOBEDO, BRENT: Design and Application of an AI-Enabled Adaptive Framework for Assessing Circularity in Socio-Ecological and Technical Systems (SETs) within the WEFE Nexus
  
  Author: VILLANUEVA ESCOBEDO, BRENT
  Programme: DOCTORAL DEGREE IN SUSTAINABILITY
  Department: University Research Institute for Sustainability Science and Technology (IS.UPC)
  Mode: Normal
  Deposit date: 14/04/2026
  Reading date: 17/07/2026
  Reading time: 10:30
  Reading place: UPC ESEIAAT edifici TR1Planta 0 Porta 085
  Thesis director: MORATO FARRERAS, JORDI
  Thesis abstract: Sustainability and circular economy transitions in contemporary socio-environmental systems are increasingly challenged by complexity, uncertainty, and strong interdependencies between natural resources, infrastructures, and governance structures. Traditional sectoral and indicator-based assessment approaches have proven insufficient to capture these interactions, often overlooking systemic trade-offs, emergent behaviors, and context-specific constraints. In response to these limitations, this doctoral thesis develops, applies, and validates integrated, participatory, and adaptive assessment frameworks for sustainability and circularity, grounded in systems thinking and the Water–Energy–Food–Ecosystems (WEFE) Nexus.The thesis is structured as a compendium as follows. The first chapter is the introduction, including the research context of the main concepts, the background and rationale, and the design, starting with the research questions, hypothesis, identification of the research gap, the research lines and objectives. The second chapter, dives into the state of the art of the main concepts, presenting the bibliometric analysis as well as the institutional context and the projects that provided the scene for the applied research. The third chapter is dedicated to the methodology, starting with the global methodology framework and then focusing on the WEFE Nexus and integrated assessment. The fourth chapter, proposes an integrated multi-criteria framework for assessing sustainability and circular economy performance in public water utilities operating in Mediterranean contexts, combining environmental footprints, ecosystem services, governance, and operational performance within a decision-oriented analytical structure. The fifth chapter applies an artificial intelligence (AI)–enabled WEFE Nexus assessment tool to evaluate circular bioeconomy (specifically biochar and agroforestry) highlighting trade-offs, synergies, and context-dependent outcomes under future scenarios in a dynamic way. The sixth chapter consolidates these insights into a transferable methodological framework for participatory, AI-enabled circularity assessment across heterogeneous socio-environmental systems. The seventh chapter is focused on the discussion of the theoretical and the applied research, specifically to proof whether circularity was implemented as a static set of material loops, or if enough evidence is found that circularity was implemented as an emergent system property, resulting from interactions between resource systems, ecosystems, institutions, and stakeholder values in the frame of this thesis. The eighth and final chapter gathers conclusions to measure the degree in which the methodology and its derived applications help integrate multi-criteria decision analysis, participatory processes, artificial intelligence, and digital twin concepts to support transparent, context appropriate and adaptive sustainability assessment. Finally, limitations and future research lines are drawn to set some basic principles for replication and adaptation of the analysis tool in different contexts. Overall, the thesis aims to contribute in advancing the state of the art in sustainability science by operationalizing the WEFE Nexus through AI-enabled and participatory assessment frameworks, bridging the gap between conceptual integration and practical support for decision-making. The obtained results, demonstrate that systemic, adaptive, and governance-aware approaches are essential for informing transitions towards sustainability and circular economy in complex socio-environmental systems with resource constraints
  

DOCTORAL DEGREE IN AEROSPACE SCIENCE AND TECHNOLOGY

• SHAHBAZI, SAEEDEH: Differential Deformation Maps Using EGMS Data
  
  Author: SHAHBAZI, SAEEDEH
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AEROSPACE SCIENCE AND TECHNOLOGY
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 22/06/2026
  Deposit END date: 06/07/2026
  Thesis director: CROSETTO, MICHELE | BARRA, ANNA
  Thesis abstract: Investigating building deformation due to differential settlements is a challenging task, particularly over large areas; however, with the advancement of remote sensing techniques, such investigations have now become feasible. The European Ground Motion Service (EGMS), a component of the Copernicus Land Monitoring Service, represents the largest wide-area Interferometric SAR (InSAR) service ever developed that provides a fully open and free-access data availability. In order to exploit the EGMS results, the challenge lies in finding appropriate methodologies and tools to effectively utilize this wealth of information and create easy-to-read and interpretable maps for building damage assessment and urban risk mitigation procedures. This PhD thesis proposes a methodology and a novel software tool that transform InSAR-based displacement data into comprehensive geospatial maps through a building-scale spatial differential deformation analysis, enabling the identification and classification of urban buildings susceptible to damage due to differential movements. We focus on spatial differential deformation (i.e., the spatial gradient of deformation) for individual buildings, because most of the significant damage to man-made structures/infrastructures is associated with spatial differential deformation. The final output of the proposed methodology is the so-called “Building Differential Deformation Map” (BDD). This methodology is novel because it provides the advantage of enabling wide-area mapping while keeping the building-level details. The procedure requires two input data: InSAR-derived displacement maps, regardless of the data source, as well as a vector map of building footprints.This research illustrates the use of EGMS Basic products to perform a multi-scale analysis, including the metropolitan area of Barcelona, the Catalonia region, and ultimately the Spanish nationwide BDD map. This latter map identifies 2,958 buildings vulnerable to damage due to differential settlements. Given the large spatial extent of the Spanish BDD map, a web-based platform has been developed to facilitate visualization and enhance the accessibility of relevant information for all users. In a further step, to enhance the analysis, additional data have been considered. The BDD map has been combined with deformation velocity, building age, considered as an indicator of vulnerability, and population data to provide an initial assessment of the potential impact on residents. This integration has led to the development of a so-called “Potential Impact Map,” which identifies areas that need prioritized attention and resources for risk mitigation. The robustness of the proposed methodology has been evaluated through a dedicated assessment procedure. This assessment has examined the methodology and its results across different acquisition geometries, demonstrating that the spatial deformation gradient is independent of geometry and across varying time spans. Similarly, validation has been conducted through field surveys to assess building damage, focusing on indicators of differential deformation, such as cracks and fractures in walls and around windows.
  

DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY

• CASTILLO DE LEON DE ROMERO, ROSNERY NAYARITH: Desarrollo de un módulo de celosía para envolvente en clima húmedo tropical (Panamá), mediante hormigón con árido de reciclado de Residuo mixto de la Construcción y Demolición (RCD) y Neumáticos Fuera de Uso (NFU).
  
  Author: CASTILLO DE LEON DE ROMERO, ROSNERY NAYARITH
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY
  Department: Department of Architectural Technology (TA)
  Mode: Article-based thesis
  Deposit date: 22/06/2026
  Deposit END date: 06/07/2026
  Thesis director: BOSCH GONZÁLEZ, MONTSERRAT | PARIS VIVIANA, ORIOL
  Thesis abstract: This doctoral thesis investigates the development of a latticework for building envelopes in humid tropical climates. The module is made from microconcrete that incorporates recycled aggregates derived from mixed Construction and Demolition Waste (CDW) and End-of-Life Tires (ELT), in the form of granulated Crumb Rubber (CR). The study addresses two complementary lines of research: 1) the development and characterization of a microconcrete incorporating recycled aggregate from CDW and ELT, with potential application in small-format latticework facade modules; and 2) the analysis and development of the latticework module and system as a passive envelope strategy.The methodology includes a bibliometric and systematic review of the use of ELT in the development of concretes; two experimental campaigns to characterize the physical, mechanical, thermal, and fire-reaction properties of the material; the development of a taxonomy for parameterizing latticework systems in building energy modeling (BEM) tools; a study of the thermal performance of latticework systems in Panama through on-site monitoring and dynamic simulation; and, finally, the evaluation of a small-scale latticework system manufactured with the developed micro-concrete, verifying its thermal performance.The findings of this study suggest that mixtures incorporating recycled aggregates can be used in building envelopes through self-supporting systems. In the case of the lattice, the mixture that exhibited the most favorable performance among the results obtained was selected. The findings also show thatthe thermal performance of the latticework is influenced by multiple factors, including its intrinsic material characteristics, geometry, percentage of openings, building envelope configuration, and the natural ventilation of the space between the two skins.The thesis concludes that it is possible to advance toward more sustainable façade solutions from a circular economy perspective by integrating high percentages of waste with the design of climate-adapted passive components.
  

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

• URBANIAK, DOMINIK: Autonomous and Collaborative Robotic Systems in 5G Smart Factories
  
  Author: URBANIAK, DOMINIK
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Institute of Industrial and Control Engineering (IOC)
  Mode: Normal
  Deposit date: 23/06/2026
  Deposit END date: 07/07/2026
  Thesis director: ROSELL GRATACOS, JOAN | SUAREZ FEIJOO, RAUL | ROSELL GRATACOS, JOAN | SUAREZ FEIJOO, RAUL | SUPPA, MICHAEL
  Thesis abstract: Autonomous and collaborative mobile manipulators are expected to play a central role in future Smart Factories by enabling flexible, human-centered production. Achieving this vision requires robotic systems that can safely react to dynamic human behavior while efficiently executing complex manipulation tasks. These requirements impose high computational demands on perception, planning, and control, which can exceed the capabilities of mobile robotic platforms. Distributed control architectures leveraging edge computing and wireless communication offer a promising solution by enabling computational offloading. However, their effectiveness depends on tightly coupled and interdisciplinary factors spanning communication, computer vision, and control. Beyond computational offloading, distributed control systems also enable distributed perception by integrating external visual sensors, extending the robot’s perceptual field beyond onboard sensing limitations.This thesis investigates how distributed control architectures for autonomous and collaborative mobile manipulators can be designed to safely and efficiently exploit wireless communication and edge computing in industrial environments. Two complementary architectures are developed and evaluated, differing fundamentally in perception placement, control strategy, and the role of communication latency.The first architecture, an Edge-Enabled system, targets safety-critical collaborative scenarios using onboard RGB-D sensing with optional edge offloading. A complete distributed perception-control loop is implemented over private 5G networks, integrating wireless communication, edge-based image processing, and closed-loop Cartesian velocity control. Extensive simulated and real experiments analyze how sensing rate, image resolution and compression, computation latency, communication technology, and quality-of-service settings jointly affect end-to-end reaction time. The results show that edge computing reduces latency only under specific conditions and that robust safety behavior requires explicit mechanisms to handle jitter and perception failures.The second architecture, an Edge-Dependent system, addresses deliberative manipulation under fixed distributed constraints, where perception and planning are performed externally. A learning-based motion planning framework is introduced that generates smooth, near-optimal, collision-free 3D trajectories with low online computation time using external visual data. Simulation and real-robot experiments demonstrate generalization across obstacle configurations and competitive performance compared to established planning baselines.Together, these contributions clarify when wireless edge computing enhances robotic performance and when it introduces fundamental constraints, providing practical system designs and conceptual insights for distributed robotic control in next-generation industrial environments.
  

DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS

• ALVAREZ GALERA, EDGAR: HELIUM NUCLEATION IN LIQUID ALKALI METALS AND LEAD–LITHIUM ALLOYS
  
  Author: ALVAREZ GALERA, EDGAR
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 25/06/2026
  Deposit END date: 08/07/2026
  Thesis director: MARTÍ RABASSA, JORDI | BATET MIRACLE, LLUIS
  Thesis abstract: In this thesis, the mixing of helium with liquid metals is studied from atomistic and computational perspectives using classical molecular dynamics methods. The main objective is to understand the microscopic mechanisms governing helium nucleation in various liquid metals, with particular emphasis on the lead--lithium eutectic.The obtained results contribute to a better understanding of processes occurring in metal--gas systems, with applications in materials science and nuclear engineering. These mixtures are relatively exotic and have been scarcely studied due to the experimental difficulties associated with handling them. The work compiled in this thesis was motivated by the need to characterize tritium breeding blankets in future nuclear fusion reactors, where free neutrons interact with lithium atoms present in the lead--lithium eutectic alloy. In this process, not only is tritium produced, but helium is also released as a by-product. The reportedly low solubility of helium in various liquid metals suggests a strong tendency towards nanobubble formation within breeder modules. Consequently, understanding the underlying microscopic mechanisms governing helium dissolution, transport, and aggregation is essential for improving the efficiency, reliability, safety, and long-term sustainability of fusion energy conversion systems.Interactions between helium and metal atoms, as well as the physical mechanisms governing noble-gas segregation, were analysed through numerical simulations. Throughout this thesis, the effects induced by thermodynamic conditions (temperature and solvent composition) were investigated. Although the main focus was placed on the lead--lithium eutectic system, the study was not restricted to this composition: various lead/lithium ratios and other pure liquid alkali solvents were also investigated.In the first part of the thesis, interaction models for liquid metals and their mixtures with helium were proposed. At this stage, the effects of tritium on the nucleation process were neglected as a first approximation. Force fields describing all interactions within the mixtures were adapted from interatomic potentials available in the literature. The liquid-metal models incorporated the effective contribution of electron clouds, and the evaluation of thermodynamic, structural, and volumetric properties was used to assess their performance. Additionally, helium was treated, as a second approximation, without explicit electronic contributions. We successfully reproduced many thermophysical properties, thereby partially validating the proposed model. Consequently, the resulting force fields relied on the assumed transferability of interatomic potentials to the thermodynamic conditions investigated in this work.In the second part of the thesis, the most innovative studies are presented. These correspond to the analysis of helium solubilities (Henry’s law constants) in alkali metals and lead--lithium alloys, as well as interfacial tensions and pressure inhomogeneities at their dividing surfaces. Under the assumption that these processes are governed by classical nucleation theory, these two sets of studies allow the determination of the volumetric and interfacial contributions involved in the work of bubble formation. The former is determined by the degree of supersaturation in a mixture in which helium is initially dissolved and is intrinsically linked to solubility. The latter is proportional to the area of the dividing surface, with interfacial tension acting as a multiplicative factor.Finally, for completeness and to obtain a more accurate representation of the mixtures, tritium was included through potential models developed in this work in order to predict the effects of the hydrogen isotope on the previous results.
  
• GANCIO VAZQUEZ, JUAN: Characterizing and detecting changes in complex multidimensional data with permutation entropy
  
  Author: GANCIO VAZQUEZ, JUAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS
  Department: Department of Physics (FIS)
  Mode: Article-based thesis
  Deposit date: 25/06/2026
  Deposit END date: 08/07/2026
  Thesis director:
  Thesis abstract: The analysis of signals obtained from complex dynamical systems is very important, not only from the point of view of many practical and interdisciplinary applications, but also, from the point of view of fundamental science, for elucidating the underlying mechanisms that generate complex behaviors. On one side, large amounts of data are currently used for purposes that have significant impact on society, for example, the detection and prediction of epidemic spreads, the analysis of trends in mobility and transportation networks, weather forecasting, to name a few. On the other side, many of the most challenging scientific endeavors intend to untangle many of these complex systems, such as the global climate and the human brain, and rely on the analysis of the signals that can be extracted from them. The analysis of these signals, even using modern approaches like machine learning and artificial intelligence, is based on the extraction of features that encode the relevant information that one needs for the specific end. One of the possible techniques used to extract features is ordinal analysis, which was proposed more than 20 years ago and looks at the relative ordering of data points to determine different aspects of the systems, like how predictable, complex, or efficient they are. Although it has been extensively applied to a wide variety of systems, and generalized to include additional aspects of the data, as well to extract temporal and spatial features, there are still aspects of its implementation to be addressed. The main goal of this thesis is to demonstrate new applications of ordinal pattern analysis for uncovering temporal and spatial structures in real world complex data. Specifically, I analyze experimental recordings obtained during the turn-on of a complex multimode laser; I analyze EEG signals recorded from healthy subjects in different conditions (eyes open or eyes open) and I analyze and compare sea surface temperature anomalies of two well-known climate datasets, in two important geography regions (El Niño and Gulf Stream). In the first chapter of the results section, I present the experimental analysis of a long cavity semiconductor laser in order to anticipate and identify the threshold bifurcation that occurs during its turn on. In the second chapter of the results section, I present the analysis of brain data obtained from electroencephalograms (EEG): recordings of the brains electrical activity obtained from the scalp in two conditions, the subjects having their eyes open (EO) or their eyes closed (EC). Here I show how the temporal and spatial features perform in the classification between the EO and EC states, and how, for the spatial features, evaluating the correlations with specific orientations can improve this performance. Finally, in the final chapter of the results section, I analyze two datasets of sea surface temperature anomaly, and I show how the spatial features allow the detection of transitions caused by changes in the acquisition and processing methodology of these datasets, showing also how their agreement improves with time. Taken together, the studies carried out in this thesis demonstrate that ordinal analysis offers great flexibility, allowing the selection of different time scales, different spatial scales, or different shapes and orientations of patterns, which allows to obtain relevant features that encapsulate complementary information to characterize complex spatio-temporal data.
  

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

• GARCIA RECASENS, POL: Optimizing efficiency and integrity in collaborative AI systems
  
  Author: GARCIA RECASENS, POL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 22/06/2026
  Deposit END date: 06/07/2026
  Thesis director: BERRAL GARCÍA, JOSEP LLUÍS | TORRES VIÑALS, JORDI
  Thesis abstract: Modern AI systems are increasingly deployed in collaborative settings where multiple users share data, compute or infrastructure. The design of these systems relies on cooperative assumptions that are routinely violated in practice. These violations degrade both efficiency and integrity across the AI lifecycle, wasting computational resources and corrupting system outputs. For example, participants may not contribute honestly to federated training, memory may be over-allocated in service environments shared by multiple users, and in-context examples used for data generation may be biased or adversarially manipulated.This thesis demonstrates that by designing mechanisms that remain effective when cooperative assumptions fail, the AI lifecycle can be adapted to decentralized deployments while remaining robust to misaligned or adversarial participants. We prove this statement through three contributions that target training, serving, and data generation respectively. First, this thesis proposes FRIDA, a framework that repurposes adversarial privacy attacks to detect free-riders in Federated Learning. Rather than relying on indirect statistical signals that advanced free-riders can mimic, FRIDA directly measures evidence of genuine local training. Our evaluation shows that FRIDA detects adaptive free-riders that evade existing feature-based defenses.Second, this thesis characterizes the throughput-latency frontier of Small Language Model serving and identifies that the Pareto-optimal throughput plateau is reachable within a single accelerator. Through low-level GPU profiling, we show that the plateau is caused by DRAM bandwidth saturation within the attention mechanism, not compute saturation as commonly assumed. Based on this finding, we introduce the Batching Configuration Advisor, which recommends batch sizes and memory allocations that respect latency constraints without over-provisioning, freeing resources for concurrent workloads and achieving throughput improvements of up to 33.7\%.Third, this thesis characterizes adversarial in-context bias propagation as a new attack surface in collaborative LLM-based tabular data generation. We show that statistical biases in prompt examples systematically propagate to generated synthetic data, and that a malicious actor can amplify this effect by injecting feature-aligned examples to target specific subgroups without degrading standard utility metrics. We evaluate mitigation strategies including statistical parity constraints and frequency balancing, showing that while they attenuate bias propagation, the sensitivity of LLMs to adversarial in-context examples remains a persistent challenge.These results demonstrate that explicitly accounting for the failure of cooperative assumptions enables meaningfully more efficient and trustworthy AI systems across training, serving, and data generation.
  
• ÁLVAREZ ROBERT, DAVID: On the co-design of runtimes, systems and programming interfaces for HPC
  
  Author: ÁLVAREZ ROBERT, DAVID
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 25/06/2026
  Deposit END date: 08/07/2026
  Thesis director: BELTRAN QUEROL, VICENÇ
  Thesis abstract: High-performance computing (HPC) platforms are evolving towards increasingly complex architectures: many-core CPUs with multi-level NUMA hierarchies, heterogeneity with multiple classes of accelerators and higher-capacity interconnects. The increasing complexity and variety of resources in these machines make it harder for application programmers to use them efficiently and effectively. As a result, many resources in modern HPC clusters remain underutilized, limiting energy efficiency and the potential throughput of the machine.This thesis argues that addressing these challenges requires co-design across the software stack, from runtime mechanisms and programming interfaces to system-level policies. We first study task-based runtimes and identify opportunities to reduce overheads and improve scalability on many-core machines, introducing novel scheduling and dependency-management techniques that maintain throughput under extreme concurrency. We then tackle programmability and performance in heterogeneous systems, proposing runtime and interface support to better overlap data movement, accelerator offloading, and CPU computation.We also make a case for the effective co-design of applications and programming models through the study of an increasingly common application class: iterative data-flow computations, commonly used in simulations, iterative solvers, and AI. Through this study, we propose specific optimizations for this application class, showing how holistic co-design approaches can lead to significant speedups.Finally, we present the nOS-V library with the goal of improving system-wide utilization through application co-scheduling, and we later apply the same methodology to obtain truly interoperable programming models, enabling multiple runtimes and parallel libraries to coexist within a single application with reduced mutual interference.Overall, the contributions of this thesis provide a set of runtime techniques, programming abstractions, and system mechanisms that jointly improve throughput, efficiency, and composability on next-generation HPC systems.
  

DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING

• DENIA BERROCOSO, ANGEL: Towards characterization improvement and design optimization of steel fibre reinforced concrete elements for underground structures: experimental study and non-linear analysis
  
  Author: DENIA BERROCOSO, ANGEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 26/06/2026
  Deposit END date: 09/07/2026
  Thesis director: DE LA FUENTE ANTEQUERA, ALBERTO | MONSERRAT LOPEZ, ANDREA
  Thesis abstract: Underground transport infrastructure has become a defining challenge of modern civil engineering, driven by growing urban demand and the need for efficient, durable solutions. Mechanised tunnelling with Tunnel Boring Machines (TBMs) has become the dominant construction method, and precast segmental linings its primary structural solution. The design of these linings is not governed by global ring behaviour alone. Localised effects at radial joints, including concentrated load transfer during TBM thrust and service stages, confinement under partially loaded contact areas, and internal force redistribution under accidental actions such as fire, frequently determine performance. Capturing these mechanisms accurately in design has direct consequences for material use, construction cost, and structural reliability.Fibre reinforced concrete (FRC) is well established as a structural material for segmental linings, with a solid normative basis and extensive practical application. Its most relevant benefits are: post-cracking ductility for splitting control at joints, crack width limitation under service hoop forces, and residual tensile capacity under fire-induced spalling. At radial joints specifically, the response under concentrated loading is governed by two distinct confinement-like mechanisms: a geometry-related contribution associated with the biaxial compressive stress state developing beneath the loaded area, and a material-related contribution driven by fibre bridging and toughness that stabilises post-peak behaviour and delays cracking. Translating these mechanisms into consistent and optimised structural design remains an open problem where the potential for efficiency gains is significant but validated methodologies linking material characterisation to structural response are still needed.This thesis addresses these challenges through an integrated experimental and numerical programme. The experimental component characterises both confinement-like contributions under partially loaded conditions representative of radial joints, quantifying their dependence on fibre content and loading eccentricity. These results provide the constitutive basis for non-linear finite element models calibrated through inverse analysis and validated against independent experimental data at specimen and structural scale. The validated framework is then applied within a reliability-based design context to assess the structural efficiency achievable when post-cracking behaviour and confinement effects are explicitly accounted for. The fire component extends this framework through sequentially coupled thermo-mechanical analysis with explicit joint modelling and parametric treatment of spalling depth, providing the internal forces at radial joints under the accidental combination and contributing to a verification procedure for this design scenario based on the experimental and numerical framework developed throughout the thesis.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• BORREGO ORPINELL, GERARD: Modelling and Optimal Energy Management of Battery-Based Energy Storage Systems for Transport and Industrial Applications
  
  Author: BORREGO ORPINELL, GERARD
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 16/06/2026
  Deposit END date: 30/06/2026
  Thesis director: DÍAZ GONZÁLEZ, FRANCISCO | CAPÓ LLITERAS, MACIÀ
  Thesis abstract: The global transition toward a more sustainable and low-carbon energy system is driving the electrification of transport and the large-scale integration of renewable energy sources. These transformations are essential to reduce greenhouse gas emissions and mitigate climate change, as highlighted by international initiatives such as the Kyoto Protocol and the Paris Agreement. In this context, energy storage systems play a key role in improving energy flexibility, enabling renewable integration, and supporting the operation of electrified transport systems.Despite the relevance of energy storage systems, the optimal integration and operation of battery-based energy storage systems remain challenging. Batteries are subject to degradation mechanisms that depend strongly on their operating conditions, while different applications impose significantly different power and energy requirements. For instance, electric vehicles require highly dynamic power responses due to frequent acceleration and regenerative braking events, whereas industrial environments often demand sustained power delivery for extended periods. These differences complicate the design and operation of storage systems and highlight the need for advanced modelling and energy management tools.This thesis aims to develop modeling, experimental, and optimization tools for the optimal integration and energy management of battery-based energy storage systems across different stages of their operational lifecycle. The proposed framework enables the digital representation of battery behaviour within different electrical environments and supports the development of energy management strategies that consider both battery limitations and the specific application operational requirements.To support the validation of these approaches, a flexible and cost-effective experimental test bench for hybrid energy storage systems is developed, enabling real-time evaluation of energy management strategies through a hardware-in-the-loop configuration. The proposed methodologies combine system modeling, simulation tools, and advanced control algorithms for energy management, allowing realistic assessment and experimental validation of different storage configurations.The proposed tools are applied to two representative scenarios. In electric traction applications, hybrid energy storage systems combining batteries and supercapacitors are investigated to handle the highly dynamic power profiles of electric vehicles. An optimized dual-level energy management strategy is developed and experimentally validated, achieving significant reductions in battery degradation while maintaining system efficiency and dynamic performance. In addition, the integration of second-life batteries in industrial environments is explored as a circular economy strategy. A digital twin-based framework and multi-objective energy management approach are proposed to assess the combined operation of second-life batteries and photovoltaic generation, considering both economic and environmental criteria.Overall, this work provides novel experimental platforms, modelling tools, and energy management strategies that facilitate the integration of battery-based energy storage systems across different electrical environments, supporting the deployment of more sustainable and flexible energy systems.
  
• MONTALÀ PALAU, MONTSERRAT: Resilience in Power Systems: From Technology to System-Level Perspectives
  
  Author: MONTALÀ PALAU, MONTSERRAT
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 17/06/2026
  Deposit END date: 01/07/2026
  Thesis director: GOMIS BELLMUNT, ORIOL | CHEAH MAÑÉ, MARC
  Thesis abstract: This thesis is structured around a concept that has recently been linked to electrical systems: resilience. These systems have become fundamental for the functioning of modern societies, and, for this reason, it is necessary to continue transforming them while ensuring their proper operation. This thesis addresses the concept of resilience in electrical systems from two complementary perspectives. The first focuses on the development of a methodology, implemented in an open-source tool, that allows the assessment of the power system resilience and the analysis of how the deployment of different technologies can modify it. The second focuses on specific technologies and is articulated around the concept of ramp rate limit. Regarding the first part, the concept of resilience in electrical systems is relatively recent and has emerged to overcome the limitations of the traditional concept of reliability. Resilience aims to consider a wide range of events that may affect the electrical system, including those with low probability but high impact, and to quantify their consequences in energy, social, and economic terms. Although the concept of resilience has been incorporated into new policies, roadmaps, and technological developments, its measurement and quantification remain a challenge.In this context, the development of resilient electrical systems requires both the collection of data on current systems and the identification of possible future events that may affect them. This makes it necessary to have methodologies capable of integrating and evaluating this information in a coordinated manner. To address this challenge, the thesis proposes a methodology that combines traditional tools for the analysis of electrical systems, such as Optimal Power Flows (OPF), with Geographic Information Systems (GIS). In this approach, resilience is quantified in terms of the total energy at risk in a given power system when exposed to specific hazards. This methodology has been implemented in a tool whose objective is to facilitate its use with basic electrical knowledge, so that it can be used by a wide range of users. As for the second part, the ramp rate limit, adopted by several countries, is defined as a strategy to control the speed of variations in the rate of change of active power from generation plants, mainly wind and photovoltaic solar plants. In addition, since renewable plants may operate without dedicated voltage control and at constant power factor, limiting active power variations also slows down reactive power changes, giving the system additional time to activate alternative voltage control resources.Despite its relevance, the implementation of ramp rate limits continues to represent a challenge for the different agents of the electrical system. In this sense, the thesis proposes a methodology that allows system operators to determine the required ramp rate limit based on system parameters such as inertia, damping, and response time constants. Likewise, a methodology is presented for renewable energy plant developers to design installations that comply with these requirements. Since this often involves the incorporation of energy storage systems, the proposed methodology is flexible and allows the exploration of the use of different storage technologies.Each section includes case studies that have allowed for the validation of the robustness of the developed methodologies and tools, showing how different strategies and technologies affect the resilience and stability of the electrical system.Overall, this doctoral thesis makes a significant contribution to the development of resilient electrical systems, aiming to ensure their proper functioning and, in doing so, to support life and essential activities in contemporary societies.
  
• MOSHARI MAMAGHANI, VAHID: Grid-forming converter control for modern high-voltage transmission networks
  
  Author: MOSHARI MAMAGHANI, VAHID
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 17/06/2026
  Deposit END date: 01/07/2026
  Thesis director: GOMIS BELLMUNT, ORIOL | PRIETO ARAUJO, EDUARDO
  Thesis abstract: The voltage source converter (VSC) operating in grid-forming (GFM) mode is one of the promising control approaches for the integration of renewable energy sources in future power systems. GFM technology offers numerous advantages due to its inherent voltage-source behavior, enabling improved system stability as well as support for grid restoration services. Technologies capable of providing GFM functionalities include high voltage direct current (HVDC) systems, flexible alternating current transmission systems (FACTS), power park modules (PPMs), and battery energy storage systems (BESS).In recent years, the GFM control concept has gained significant attention due to its potential benefits in grid stabilization and auxiliary services. Several manufacturers are already offering assets with GFM control capabilities; however, the associated control strategies, limitations, and system-level interactions have yet to be comprehensively addressed in the literature. This work focuses on the application of GFM control to HVDC system and static synchronous compensator (STATCOM) integrated with energy storage.First, detailed electromagnetic transient (EMT) models and control implementations of STATCOMs operating in both GFM and grid-following (GFL) modes are presented, along with a generic synchronous condenser model for comparison. Different configurations of voltage and current control loops are analyzed. A complete converter control scheme, including grid-side and internal energy controllers for the MMC topology, is developed and tuned according to TransnetBW GFM requirements, including AC current and DC voltage limiting functions.The system-level performance is evaluated using a developed 9-bus benchmark grid based on the TransnetBW network. Initial time-domain simulations are conducted to improve and refine the GFM-STATCOM control. The impact of different fault locations on the fault ride-through (FRT) performance of the GFM-STATCOM is analyzed and compared using both time-domain simulations and scanning methods.Finally, based on the experience and results obtained from PSCAD modeling, control tuning, and development of the 9-bus benchmark, a set of conformity tests for GFM-STATCOMs is proposed.
  

DOCTORAL DEGREE IN ELECTRONIC ENGINEERING

• GAMEL, MANSUR MOHAMMED ALI: Development of Epitaxial-free c-Ge Thermophotovoltaic Devices: from Double-Side Towards Interdigitated Back Contacted Structures
  
  Author: GAMEL, MANSUR MOHAMMED ALI
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRONIC ENGINEERING
  Department: Department of Electronic Engineering (EEL)
  Mode: Normal
  Deposit date: 22/06/2026
  Deposit END date: 06/07/2026
  Thesis director: MARTIN GARCIA, ISIDRO | GARIN ESCRIVA, MOISES
  Thesis abstract: Meeting global electricity demand while mitigating climate change requires technologies that overcome renewable intermittency. Thermophotovoltaic (TPV) conversion is a promising solid-state solution for applications including thermal storage and waste heat recovery. Recent TPV devices exceed 40% efficiency, rivaling Stirling and Brayton engines, but they rely on expensive III–V semiconductors and epitaxial growth, limiting economic viability.This thesis focuses on crystalline germanium (c-Ge) as a low-cost alternative absorber and develops non-epitaxial fabrication methods (PECVD, ALD, laser processing) for Ge TPV cells, progressing from double-side contacts to interdigitated back contact (IBC) structures.First, selective contacts for p-type c-Ge are developed. For hole-selective contact, a novel ohmic contact uses a dielectric passivation stack (a-SiCₓ/Al₂O₃/a-SiC) with UV laser processing (355 nm), achieving a spot radius of ~6 µm, recombination velocity 1.7×10³ cm/s, contact resistivity 0.057 mΩ·cm², and >90% sub-bandgap reflectance. For electron-selective contact, we develop n-type nanocrystalline silicon layers (nc-Si(n)) on c-Ge(p) exhibits high conductivity (42 Ω⁻¹ cm⁻¹), low activation energy (0.013 eV), and doping ~1×10²⁰ cm⁻³. A thin amorphous silicon interfacial layer improves passivation but severely impedes carrier transport; thus, nc-Si(n) without this layer is chosen for device integration.Following the development and characterization of the electron- and hole-selective contacts, the second part of this thesis is focused on fabricating c-Ge-based TPV devices. In a systematic study comparing c-Ge substrates with high (2 × 10¹⁶ cm⁻³) and medium (2 × 10¹⁵ cm⁻³) doping levels, each integrated with either a full rear contacted (FRC) or a passivated emitter and rear cell (PERC) architecture. The electrical and optical performance of each design is characterized and the results demonstrate that high substrate doping is essential for minimizing series resistance. However, photon recycling enabled by the PERC architecture emerged as the dominant factor for efficiency enhancement, with the high-doped PERC cell achieving a peak estimated conversion efficiency of 8.41% at an emitter temperature of 1500 K. Finally, a compatible fabrication process was designed, and the first batch of IBC structures was produced with promising results. To improve IBC TPV devices, we propose to incorporate nanotextured black germanium (b-Ge) at the front surface. To do so, we resolve the critical passivation challenge for b-Ge on highly doped substrates, enabling its integration into IBC TPV cells. While standard Al₂O₃ passivation degrades at the required doping levels (>10¹⁵ cm⁻³), an a-SiCₓ(i)/Al₂O₃ stack successfully provides both chemical and field passivation, achieving surface recombination velocities well below 100 cm/s for b-Ge. Device simulations incorporating the passivated b-Ge front surface indicate a superior output power density, surpassing that of state-of-the-art of TPV c-Ge cells.Overall, the results obtained in this thesis demonstrate the first c-Ge-based TPV cell with a non-epitaxial heterojunction, contributing significantly to the advancement of cost-effective TPV technology.
  

DOCTORAL DEGREE IN ENGINEERING, SCIENCES AND TECHNOLOGY EDUCATION

• ROCUTS PABON, SCHWEITZER: Developing and Piloting an Implementation Framework for Transdisciplinary Undergraduate Collaboration, Without Curricular Change: Mathematics as an Integrating Resource and Game-Based Assessment as a Supporting Tool
  
  Author: ROCUTS PABON, SCHWEITZER
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ENGINEERING, SCIENCES AND TECHNOLOGY EDUCATION
  Department: Institute of Education Sciences (ICE)
  Mode: Normal
  Deposit date: 12/06/2026
  Deposit END date: 26/06/2026
  Thesis director: ALIER FORMENT, MARC
  Thesis abstract: Transdisciplinary undergraduate education is widely advocated but rarely implemented within rigid university structures. This doctoral thesis addresses this challenge through a three-iteration Educational Design Research (EDR) study (2023–2024) that developed, piloted, and validated a novel ten-step implementation framework for transdisciplinary collaboration, requiring no curricular changes. The intervention coupled an undergraduate systems engineering course with a medicine course around a shared public-health problem using DANE Multipurpose Survey microdata (n ≈ 600,000). It engaged ≈320 students and 46 external evaluators across six disciplines (engineering, medicine, public health, biomedicine, data analytics, and statistics), guided by three theoretical conjectures: epistemic common ground, productive friction, and assessment as integration signal.Student outputs were classified via the M-I-T scheme (Multidisciplinary, Interdisciplinary, Transdisciplinary), with I/T boundaries operationalized as integration into unified explanatory artifacts. The headline findings are an I-level attainment rate of 86.4%, a T-level rate of 32.1%, and a conditional T|I rate of 37.2% (a key indicator that distinguishes learning that goes beyond expectations from the integration of knowledge). Exploratory GBA (Game-Based Assessment, Iteration 3, n=7 teams) yielded +12.4 pp T-level (43.8% vs. 31.4%) and +9.1 pp T|I (43.5% vs. 34.4%), with 19.75% of students generating deep profiles (in applied math and problem solving), used as boundary input rather than as a selection criterion.The principal contribution is the evidence-based framework (Chapter 7; Figure 7.1), traceable to pilot data (Chapters 5–6; Table 7.1), incorporating mathematics as disciplinary bridge and GBA as peripheral diagnostic (Steps 3, 7; "augment, not replace"). Transferable to engineering–medicine pairings on data-rich problems, it includes entry rules, iteration triggers, skips, and adaptations. A decision checklist supports ethical and equitable use of the GBA, and the framework operationalizes practical outcomes through an instructor–GBA hybrid teaming model.
  

DOCTORAL DEGREE IN NATURAL RESOURCES AND THE ENVIRONMENT

• MORELL LLORENS, JOAN: Development of an integrated biological base process for the recovery of copper from electronic waste: Advances in pre-treatment, aeration intensification, monitoring and electrochemical recovery
  
  Author: MORELL LLORENS, JOAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN NATURAL RESOURCES AND THE ENVIRONMENT
  Department: Department of Mining, Industrial and ICT Engineering (EMIT)
  Mode: Article-based thesis
  Deposit date: 23/06/2026
  Deposit END date: 07/07/2026
  Thesis director: DORADO CASTAÑO, ANTONIO DAVID | GUIMERÀ VILLALBA, XAVIER
  Thesis abstract: The accelerated generation of electronic waste (e-waste) represents both a major environmental challenge and an opportunity for the recovery of valuable metals within a circular economy framework. Among the different recovery technologies, bioleaching has emerged as a promising sustainable alternative due to its low energy requirements and reduced dependence on chemical reagents. In particular, closed-loop bioleaching systems enable the continuous regeneration and reuse of the leaching agent, minimizing reagent consumption and waste generation.This doctoral thesis investigates the technological potential and applicability of closed-loop bioleaching for metal recovery from e-waste through an integrated process engineering approach focused on process intensification, operational simplification, continuous monitoring, and integration of downstream metal recovery. The work is structured around four interconnected stages: (I) ferric iron bioproduction, (II) e-waste preprocessing, (III) metal bioleaching, and (IV) selective metal recovery.The first stage addressed was the biological regeneration of ferric iron, responsible for metal oxidation during bioleaching. Since Fe²⁺ oxidation is often limited by oxygen transfer, an intensive aeration system based on a venturi jet was implemented in a bioreactor containing immobilized Acidithiobacillus ferrooxidans. This system significantly increased dissolved oxygen availability and improved Fe²⁺ oxidation rates by up to 3.5 times compared with conventional systems, facilitating a more continuous and intensified operation.The second stage focused on simplifying e-waste preprocessing while maintaining efficient metal recovery. Conventional preprocessing routes often involve extensive mechanical treatment and manual dismantling operations, increasing operational complexity and processing time. Through the characterization of 850 end-of-life mobile phones after industrial shredding and screening processes, it was demonstrated that simplified mechanical strategies can concentrate valuable metals into accessible fractions suitable for subsequent bioleaching stages.During the bioleaching stage, a non-invasive RGB-Arduino device was developed for real-time monitoring of Fe³⁺ and Cu²⁺ concentrations through optical analysis. The system enabled analyte estimation under highly corrosive conditions without continuous sampling, facilitating process control and reducing waiting times between stages.Finally, the thesis demonstrates the feasibility of direct copper electrowinning from iron-rich leachates without prior iron removal. Although the presence of Fe²⁺ affects current efficiency, copper deposits with purities close to 99.9% were obtained. Furthermore, the remaining Fe²⁺ in solution can be recirculated back to the biological oxidation stage, where it is regenerated to Fe³⁺ and reused as the leaching agent. This strategy closes the iron loop, minimizes reagent consumption, and reduces secondary waste generation.Overall, this thesis contributes to the development of a more compact, efficient, and operationally simplified closed-loop bioleaching process for sustainable urban mining and e-waste recycling.
  
• MULERO JIMÉNEZ, LORENA: Bosc i Sostenibilitat: proposta educativa a l’entorn dels serveis ecosistèmics del bosc i els ODS amb pedagogia de ciència oberta a secundària
  
  Author: MULERO JIMÉNEZ, LORENA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN NATURAL RESOURCES AND THE ENVIRONMENT
  Department: Department of Mining, Industrial and ICT Engineering (EMIT)
  Mode: Normal
  Deposit date: 18/06/2026
  Deposit END date: 02/07/2026
  Thesis director:
  Thesis abstract: We live in a society that normalizes crises. These crises affect the very pillars of civilization, and education is the engine that moves the world. Furthermore, what would become of society and the education of new generations without caring for the environment and nature?This thesis develops a series of actions related to forests and their contribution to sustainability through their connection with the Sustainable Development Goals (SDGs). This is a process of raising awareness among secondary school students regarding their essential role in the journey toward a sustainable and respectful society. Likewise, it analyzes the impact of implementing the "Forest and Sustainability Project," applying the innovative teaching methodology known as Open Science Schooling. The study focuses on how this approach fosters students' awareness of their role as key agents in changing society and steering it toward sustainability.A case study is conducted using teaching materials created and developed within this thesis. The activities are implemented in secondary schools across Catalonia. Additionally, activities are carried out within the framework of the Exploratori dels Recursos de la Natura that aims to promote science and technology among youth and conducts activities addressed to both secondary school teachers and students.
  

DOCTORAL DEGREE IN NETWORK ENGINEERING

• KANJ BONGARD, SEBASTIEN: Contribution to the Systematic Study of Threat Actor Tools and Techniques in Real-World Cyber Incidents
  
  Author: KANJ BONGARD, SEBASTIEN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN NETWORK ENGINEERING
  Department: Department of Network Engineering (ENTEL)
  Mode: Normal
  Deposit date: 22/06/2026
  Deposit END date: 06/07/2026
  Thesis director: PEGUEROLES VALLES, JOSEP RAFEL
  Thesis abstract: Cyber incident response and digital forensics (DFIR) research increas- ingly faces a tension between academic rigor and the operational re- alities of real-world investigations. While academic studies often rely on controlled datasets and synthetic scenarios, practitioners must oper- ate under time pressure, incomplete evidence, and strict confidentiality constraints. This doctoral research addresses that gap through an In- dustrial PhD program conducted in collaboration with Incide Digital Data S.L., which enabled access to real-world incident data and practi- tioner workflows while maintaining a rigorous scientific methodology. The thesis investigates how threat-actor tools, techniques, and behaviours can be systematically analyzed and transformed into reusable, vali- dated, and operationally meaningful artifacts. Three complementary research directions are explored. First, an integrated forensic methodol- ogy is proposed for the analysis of abused legitimate tools and mobile activity, combining tool-centric investigations with structured iOS ac- tivity characterization to support accurate reconstruction, automation, and legally robust analysis in real incident-response contexts. Second, the research develops a Business Email Compromise (BEC)-specific map- ping of Tactics, Techniques, and Procedures using the MITRE ATT&CK framework, addressing limitations of narrative-driven BEC reporting. The proposed matrix is validated against real-world cases and demon- strates improved behavioural comparison, clustering, and defensive alignment. Third, the thesis designs and empirically evaluates a YARA- based detection library targeting malware anti-analysis techniques, with a focus on anti-virtual machine and anti-sandbox behaviour, highlight- ing both the strengths and limits of static detection in operational con- texts. Across these contributions, the thesis demonstrates that behavioural and tool-based indicators provide durable defensive value and that hy- brid analytical pipelines are necessary to address modern evasive threats. 6 By grounding methodological innovation in industrial practice, this work advances DFIR towards more systematic, reproducible, and operationally relevant research, supporting faster investigations and more consistent defensive decision-making.
  

DOCTORAL DEGREE IN NUCLEAR AND IONISING RADIATION ENGINEERING

• TOBAJAS ASENSIO, LUIS MIGUEL: ANÁLISIS DE LA INFORMACIÓN INSTITUCIONAL Y EL TRATAMIENTO DE LA PRENSA DE LOS INCIDENTES NUCLEARES ESPAÑOLES (1989-2009)
  
  Author: TOBAJAS ASENSIO, LUIS MIGUEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN NUCLEAR AND IONISING RADIATION ENGINEERING
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 17/06/2026
  Deposit END date: 01/07/2026
  Thesis director: REVENTOS PUIGJANER, FRANCESC-JOSEP | PONT SORRIBES, CARLES
  Thesis abstract: The general objective of this research is to analyze the safety of the nuclear power plants in Spain during the period between 1989 and 2009, through a comprehensive analysis of institutional information and press coverage of nuclear incidents.The methodology employed includes a mixed qualitative and quantitative model. Scientific production on nuclear incidents has been analysed through technical information databases, academic databases (Wos and Scopus), and newspaper archives.The newspapers ABC, La Vanguardia, and El País were selected based on the criterion of being among the most widely followed newspapers in Spain during the period studied, considering the press as the best means of monitoring incidents at the end of the 1980s.In 1990, following the Chernobyl accident, the INES Scale was introduced, created by the International Atomic Energy Agency (IAEA) and the Nuclear Energy Agency, with the aim of facilitating international communication to the public and the media. This study analyses incidents classified as level two or higher according to IAEA criteria. The results of this work consider the use of the INES Scale in institutional information and in the media.The conclusions allow for a deeper understanding of the treatment of information provided to the public and the media coverage of nuclear incidents. The analysis of lessons learned from the four incidents studied and their follow-up makes it possible to conclude that there have been advances in nuclear safety and in institutional and public information, with the consolidation of the INES Scale in nuclear communication in Spain. However, it is determined that the completion of corrective actions does not reach public opinion despite its relevance.The research provides proposals for improvement with the aim of promoting better communication in the future, including the participation of experts. Communication is one of the most relevant issues in nuclear crises and must be clear, timely, accurate, transparent, and proactive.
  

DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS

• HARO GUTIERREZ, PILAR ADRIANA: CONDUCTIVE AND INTERACTIVE MULTIFUNCTIONAL PLATFORMS FOR BIOMEDICAL APPLICATIONS
  
  Author: HARO GUTIERREZ, PILAR ADRIANA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 23/06/2026
  Deposit END date: 07/07/2026
  Thesis director: ALEMAN LLANSO, CARLOS ENRIQUE | PÉREZ MADRIGAL, MARIA DEL MAR
  Thesis abstract: Despite recent advances in the development of smart biomaterials for tissue engineering and controlled drug delivery, significant limitations still remain regarding the integration of electroactive properties, responsiveness to external stimuli, and adequate biocompatibility within biodegradable and structurally stable platforms. In this context, this doctoral thesis focused on the development and characterization of electroactive and electrosensitive biomaterials based on biodegradable polymers, mainly polylactic acid (PLA), hyaluronic acid (HA), and polycaprolactone (PCL), aimed at applications in tissue engineering, regenerative medicine, and controlled drug delivery systems. Multifunctional scaffolds and membranes capable of responding to external electrical stimuli were designed and fabricated to modulate the sustained release of bioactive compounds, such as lactate and chloramphenicol, with potential applications in cardiac regeneration and wound healing. The developed materials incorporated conductive polymers and hybrid magnetic particles, enabling the production of biocompatible structures with enhanced electroactive, magnetic, and mechanical properties suitable for interacting with biological tissues and dynamically responding to external stimuli.To optimize the performance of these systems, structural and surface modifications were implemented, including plasma treatments, enzyme immobilization, and PCL coatings, which enabled regulation of material degradation, modification of porosity, and adjustment of the release profiles of therapeutic compounds. In particular, the developed scaffolds demonstrated the ability to release lactate in a sustained manner over prolonged periods, reaching different concentrations depending on the temperature and electrostimulation conditions applied. Likewise, chloramphenicol-loaded membranes enabled both passive and electrically induced release while preserving the antimicrobial activity of the antibiotic against bacteria such as Escherichia coli and Staphylococcus aureus.The obtained results demonstrated that the application of electrical stimuli promotes the controlled, progressive, and prolonged release of bioactive molecules, while the integration of conductive and magnetic components improves the functionality and versatility of the biomaterials. Overall, this work demonstrates that the combination of multifunctional materials, structural modification strategies, and electrosensitive systems constitutes an innovative and promising approach for the development of smart platforms capable of responding precisely to specific therapeutic requirements, thereby opening new opportunities for the design of advanced biomedical devices in regenerative medicine and localized drug delivery.As future perspectives, the studies developed in this thesis open the possibility of exploring new electroactive stimulation strategies using more complex and dynamic electrical signals, as well as further advancing the biological validation of the materials through advanced cellular models and even in vivo studies. Furthermore, it may be of interest to evaluate the scalability and reproducibility of some of the most promising systems with a view toward their technological transfer and the development of clinical prototypes.
  

DOCTORAL DEGREE IN STATISTICS AND OPERATIONS RESEARCH

• PUIG DE DOU, IGNACIO: Statistical Activity Tracking: Bayesian Hierarchical Models for Monitoring Customers and Industrial Equipment
  
  Author: PUIG DE DOU, IGNACIO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN STATISTICS AND OPERATIONS RESEARCH
  Department: Department of Statistics and Operations Research (EIO)
  Mode: Article-based thesis
  Deposit date: 12/06/2026
  Deposit END date: 26/06/2026
  Thesis director: PUIG ORIOL, XAVIER
  Thesis abstract: Modern business and industrial environments increasingly rely on continuous monitoring of customers and equipment through operational data streams. Detecting meaningful behavioral changes, such as customer disengagement or early signs of equipment malfunction, is critical for timely intervention. Classical Statistical Process Control (SPC) methods rely on assumptions that are often violated in practice, including homogeneous populations, regular exposure and a clear separation between Phase I and Phase II.This thesis develops Bayesian modeling and methodological solutions for tracking heterogeneous entities, such as customers or remotely operated industrial machines, under these practical constraints. Irregular activity, missing data, evolving operating conditions and the absence of a clean Phase I period are treated as defining features of modern monitoring problems rather than as limitations to be circumvented.The first part of the thesis focuses on customer-activity modeling through a fully Bayesian implementation of the Pareto/NBD model framework. A Bayesian clustering strategy is introduced to group customers with similar purchasing behavior, improving parameter estimation and supporting customer-level revenue forecasting.The second part addresses industrial equipment monitoring using error-count data. Two complementary approaches are proposed. First a mixture-model-based SPC framework for heterogeneous populations when in-control data are not clearly identifiable. Second a fully Bayesian hierarchical model that incorporates operating conditions, stabilizes low-exposure estimates, captures machine-specific behavior and automatically identifies out-of-control observations.Overall, Bayesian inference provides a flexible and principled framework for hierarchical modeling, probabilistic anomaly detection, information sharing across entities and sequential updating as new data become available. The proposed methods extend classical SPC ideas to contemporary business and industrial monitoring settings, offering statistically sound and operationally relevant solutions.
  

DOCTORAL DEGREE IN SUSTAINABILITY

• KHEZRINEJADGHARAEI, MAHDIEH: Sustainability, Resilience, Vulnerability and Climate Change Effects within the Farming Ecosystem in Catalonia
  
  Author: KHEZRINEJADGHARAEI, MAHDIEH
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SUSTAINABILITY
  Department: University Research Institute for Sustainability Science and Technology (IS.UPC)
  Mode: Normal
  Deposit date: 17/06/2026
  Deposit END date: 01/07/2026
  Thesis director: GUESMI, BOUALI | BUYSSE, JEROEN FIRMIN
  Thesis abstract: Agricultural systems worldwide face mounting pressures from climate change, market volatility and resource constraints, making the assessment of sustainability, resilience and vulnerability critical for food security. In Catalonia, these challenges are acute given Mediterranean cropping diversity and recurring climate stressors. This thesis addresses four questions: how to measure farming sustainability and its methodological sensitivity, how sustainability relates to resilience across crops, how vulnerability affects productivity, and how machine learning and economic optimization can guide adaptation.The first chapter examines Catalonia's farming ecosystem holistically. Using factor analysis, we develop a composite index integrating 21 economic, environmental and social indicators from the FADN. Sustainability scores range from 3 to 4, with larger farms outperforming smaller ones economically. Significant differences emerge by economic size and over time, suggesting size-specific interventions targeting smallholder management and adaptation. The methodology offers a practical tool for monitoring sustainability in Mediterranean systems.As a complementary analysis, we test the sensitivity of assessments to five composite index methodologies. Using random effects GLS regression and variance-based sensitivity analysis, we show methodological choices significantly influence outcomes. Expert weighting yields results similar to equal weighting, while factor analysis with min-max normalization is the most theoretically consistent. Principal component analysis offers strong statistical stability but has limitations for quantitative data. This is the first systematic integration of variance-based sensitivity analysis with econometric validation for sustainability indices, providing a robustness framework for evidence-based method selection.The second chapter examines the interplay between sustainability pillars and farm resilience. Using structural equation modelling for cereal, rice, grape and olive farms, we reveal patterns that contradict conventional theory. Economic sustainability strongly drives resilience in cereal, rice and olive farms, while environmental factors predominate in grape farms. Contrary to expectations, social sustainability has negative direct effects on cereal and rice resilience but positive effects on olive farms, challenging assumptions of universal sustainability-resilience synergies. These findings help develop crop-specific strategies.The third chapter assesses climate vulnerability of the four crops through an index combining exposure, sensitivity and adaptive capacity. Using farm-level panel data, we apply a three-stage approach combining the index, correlation analysis and dynamic panel estimation. Olive shows the highest vulnerability, followed by cereal; grape shows the lowest. Lleida exhibits the highest regional vulnerability, Barcelona the lowest. Temperature factors emerge as dominant drivers. System GMM estimation confirms a strong negative relationship between vulnerability and productivity, with long-term impacts exceeding immediate effects.The fourth chapter develops the first integrated framework combining machine learning yield predictions with economic optimization to analyse climate-induced regional specialization and investment prioritization. We employ XGBoost models with multi-period positive mathematical programming under RCP4.5 and RCP8.5. While aggregate profits show minimal variation, specialization patterns shift fundamentally: specialized regions concentrate further while diversified regions maintain climate-resilient portfolios. Returns are significantly higher in water-constrained areas. Diversified regions gain resilience through portfolio effects while specialized regions face amplified vulnerability, indicating adaptation is infrastructure-constrained rather than climate-constrained. This offers a robust planning tool under climate uncertainty.
  

DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE

• BRAU, GRAZIANO: Alejandro Zohn: Vivienda colectiva como proyecto urbano. Valores arquitectónicos en la construcción de lo social
  
  Author: BRAU, GRAZIANO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE
  Department: Department of History and Theory of Architecture and Communication Techniques (THATC)
  Mode: Normal
  Deposit date: 26/06/2026
  Deposit END date: 09/07/2026
  Thesis director: HERNÁNDEZ FALAGÁN, DAVID | MONTANER MARTORELL, JOSE MARIA
  Thesis abstract: The main objective of this research work is to analyze the contribution of the Mexican architect Alejandro Zohn Rosenthal to the field of collective housing. Through the study of his projects, the architectural, urban, and social values present in his housing production are identified.In a contemporary context characterized by mass production disconnected from its urban environment and from the needs of its inhabitants, this research recovers a series of design criteria present in Zohn’s work, whose relevance makes it possible to reconsider alternatives for the construction of more integrated, equitable, and inclusive urban environments.The thesis is structured into five major parts that make it possible to reconstruct, analyze, and critically project the thought and work of Alejandro Zohn in relation to collective housing:The first part corresponds to the methodological introduction, in which the object of study, resources, multiscalar approach, and expected results are established, thus defining the conceptual and operational foundations of the work.The second part constructs the historical, biographical, and disciplinary framework of the research, addressing the architect’s trajectory, the AZA office, and the context of collective housing across different scales and periods.The third part delves into the intellectual and operational dimensions of Zohn’s production through the analysis of projects, writings, and actions related to social housing and theoretical dissemination.The fourth part constitutes the analytical core, where the comparative study of six housing complexes is developed, making it possible to identify design strategies and modes of inhabitation.Finally, the thesis concludes with a synthesis of the results obtained and a critical reflection on the research process and its future projections.