DOCTORAL DEGREE IN AEROSPACE SCIENCE AND TECHNOLOGY

• SAMALA, BHANU PRAKASH REDDY: Computational Study of Active Flow Control in Aerodynamic Bodies: from DNS to Machine-Learning Surrogates
  
  Author: SAMALA, BHANU PRAKASH REDDY
  Programme: DOCTORAL DEGREE IN AEROSPACE SCIENCE AND TECHNOLOGY
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 14/10/2026
  Reading date: 27/11/2026
  Reading time: 10:00
  Reading place: Aula 212, 2.ª planta, edificio B4, Campus Nord – UPC.
  Thesis director: MELLIBOVSKY ELSTEIN, FERNANDO PABLO | BERGADÀ GRANYÓ, JOSEP MARIA
  Thesis abstract: This thesis investigates active flow control (AFC) over aerodynamic bodies using high-fidelity direct numerical simulations (DNS) and machine-learning (ML) surrogate models. DNS provides the most accurate description of the flow physics but is feasible only at moderate Reynolds numbers, and the multi-dimensional AFC parameter space renders exhaustive parametric studies computationally prohibitive. The objective of the thesis is to advance the understanding of AFC physics across two canonical aerodynamic configurations, and to develop and evaluate ML methodologies that reduce the computational cost of high-fidelity aerodynamic analysis in industrially relevant settings.First, DNS of the flow around an Ahmed body at Re_L = 6 x 10^4 was performed with steady suction (SS) and steady blowing (SB) through a slit at the upper surface near the slant leading edge. SS reduces the drag coefficient by 8.4%, whereas SB increases it by 17.5%. The reduction under SS is attributed to flow attachment over the slant, a strengthened C-pillar vortex and pressure recovery, while SB leads to premature separation.Second, DNS of periodic zero-net-mass-flux (ZNMF) synthetic jet actuation was performed on a three-dimensional NACA 2412 airfoil at Re = 5000 and angle of attack alpha = 8 degrees, at half (sub-harmonic, SH), the same (natural harmonic, NH) and double (second harmonic, 2H) the natural vortex shedding frequency. All cases improve the lift-to-drag ratio, by 75% (NH), 47% (SH) and 18% (2H). The superior performance of NH actuation is attributed to resonant lock-in between the forcing and the dominant shedding frequency of the baseline flow, which compresses the laminar separation bubble. SH and NH actuation suppress trailing-edge spanwise vortex breakdown and reorganise the flow into quasi-two-dimensional coherent structures.Third, a physics-informed machine learning (PIML) framework was developed to correct the Reynolds stress tensor predicted by Reynolds-Averaged Navier-Stokes (RANS) solvers, using DNS-derived data and Galilean-invariant input features. It was validated on two-dimensional backward-facing step and airfoil configurations at Re ~ 3 x 10^4. Including training data that span the flow regime of the test case is a prerequisite for reliable prediction with the Random Forest algorithm. In its current form, the framework requires flow-physics similarity between training and test domains. The enhanced RANS solution is obtained in approximately one to one and a half hours, against 72 to 96 hours for DNS on four cores.Fourth, a graph-neural-network (GNN) surrogate was implemented to predict drag coefficients and surface pressure and wall shear stress distributions on industrial electric SUV geometries, using graphs derived from decimated CFD surface meshes. It was trained on RANS CFD datasets from two design campaigns comprising 136 simulation variants. Single-vehicle models reach test R^2 values of 0.625 and 0.629, and the combined model 0.932. A surface field prediction takes less than one minute, against six to eight hours on a 300-core CPU cluster for the corresponding RANS simulation.Together, the studies advance the understanding of AFC physics from first principles and provide efficient data-driven tools for industrial design.
  

DOCTORAL DEGREE IN AGRI-FOOD TECHNOLOGY AND BIOTECHNOLOGY

• BISCAMPS DALMAU, JORDI: Generació de mapes de vigor mitjançant sensors remots i proximals per a l’aplicació a dosis variable de productes fitosanitaris en vinya utilitzant tecnologia de modulació d’ample de pols (PWM).
  
  Author: BISCAMPS DALMAU, JORDI
  Programme: DOCTORAL DEGREE IN AGRI-FOOD TECHNOLOGY AND BIOTECHNOLOGY
  Department: Department of Agri-Food Engineering and Biotechnology (DEAB)
  Mode: Normal
  Deposit date: 11/09/2026
  Reading date: 03/12/2026
  Reading time: 10:00
  Reading place: Sala de Graus de l'EEABB, Campus del Baix Llobregat de la UPC, C. Esteve Terradas 8, Ed. D4, Castelldefels
  Thesis director: GIL MOYA, EMILIO | GARCIA RUIZ, FRANCISCO JOSE
  Thesis abstract: This doctoral thesis contributes to the development and validation of variable-rate technologies for the application of plant protection products in vineyards through flow-rate control systems based on pulse-width modulation (PWM) and vegetation characterization methods using remote and proximal sensors. First, a prototype based on PWM valves was developed and validated. The system used prescription maps generated from multispectral imagery acquired with an unmanned aerial vehicle to identify vigor zones and automatically adjust the flow rate. Trials were conducted in both trellised and goblet-trained vineyards at two phenological stages. The valves showed an almost linear response over a duty-cycle range of 20-80%. Under field conditions, the system reduced the spray volume applied by up to 23.8%, with an average reduction of 18.6%, without significant differences in normalized deposition compared with the conventional treatment. Second, three application strategies were compared: a conventional constant-volume system, a pressure-controlled variable-rate system, and the PWM-based system. The results showed that working pressure and the resulting droplet spectrum had a greater influence on spray drift than the total volume applied. The conventional system generated ground losses close to 40% under low-vigor conditions, whereas the PWM system reduced both ground losses and airborne drift under all the conditions studied. Finally, a device for high-throughput vegetation characterization was designed using ultrasonic sensors, GNSS, and an onboard control unit. The system was validated under laboratory and field conditions and compared with three-dimensional models generated using UAV photogrammetry. Both methods provided comparable estimates of the main structural parameters of the vineyard, with mean absolute percentage errors below 10%. Although photogrammetry offered higher spatial resolution, ultrasonic sensors proved to be a robust and operational alternative under field conditions.
  

DOCTORAL DEGREE IN ARCHITECTURAL DESIGN

• GONZALEZ VIROS, MARIA ITZIAR: El rescat de "Les Rambles" de Barcelona. Arquitectura Social i Cooperació Ciutadana en l'espai urbà
  
  Author: GONZALEZ VIROS, MARIA ITZIAR
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL DESIGN
  Department: Department of Architectural Design (PA)
  Mode: Normal
  Deposit date: 16/09/2026
  Reading date: 23/11/2026
  Reading time: 10:00
  Reading place: ETSAB (Escuela Técnica Superior de Arquitectura de Barcelona) - Planta -1 - Sala d'ActesAv. Diagonal, 649-651 - 08028 - Barcelona
  Thesis director: MÀRIA SERRANO, MARIA MAGDALENA
  Thesis abstract: This doctoral thesis organizes the theoretical knowledge and practical experience of a thirty-year ongoing action-research project. The result is a methodology for Citizen Cooperation in urban spaces and Social Architecture that, through diagrammatic, dialogical, and procedural tools, concretizes the transformative action that has the unanimous acceptance of all participating stakeholders. This methodology is transferable to all those who, from diverse positions and roles, participate in processes that define and design socio-urban transformations.Given the complexity of the stakeholders involved in this type of transformation scenarios, and the current disconnect between citizens, politicians and the administration, it is urgent to provide professionals responsible for implementing projects with tools that (i) help them promote dynamics of trust and cooperation among all parties and (ii) solidify the definition of the general interest as a common good and as a space for convergence.The case study described in detail is the Cooperative Process conducted with the Km-Zero Joint Venture for defining the Action Strategies and the Preliminary Project for the Comprehensive Intervention on La Rambla in Barcelona (2017-2018).The aim is to demonstrate:1) The need for a method that legitimizes collective decision-making and establishes what constitutes the general interest for specific communities, as opposed to private interests or the clientelism of a few.2) The greater impact on social cohesion of citizen cooperation processes compared to formal participation in urban projects and planning, as they simultaneously achieve the realization of a project and the construction of a citizen community that will advocate for it before institutions and private interests, thus ensuring its proper implementation over time.Beyond citizen cooperation in urban planning and space, other applications of the method include: Social Architecture for the comprehensive regeneration of neighbourhoods, the co-production of public policies, the prevention of corruption in urban planning, the democratization of decision-making and the improvement of governance, a new disciplinary specialization in Social Architecture within university studies, a scientific methodology for participatory research processes, legislative contributions to the Spanish Urban Planning Law 3/2012, as well as the creation of observatories and citizen empowerment.The inspiration and theoretical foundations of this proposal are: libertarian urbanism and proposals for degrowth and eco-social transition; the deeply applied and socially connected tradition of numerous researchers, architects, and thinkers; the theoreticians of social, political and the right to the city sciences; the participatory and urban planning practices of new professional and academic groupings; and the proposals of artists who have worked on building the relational fabric of urban spaces in transformation.
  

DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY

• COLOM BARCELONA, EMMA: Les remuntes en edificis residencials històrics a l'Eixample de Barcelona
  
  Author: COLOM BARCELONA, EMMA
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY
  Department: Department of Architectural Technology (TA)
  Mode: Normal
  Deposit date: 23/09/2026
  Reading date: 23/11/2026
  Reading time: 11:00
  Reading place: ETSAB (Escola Superior d'Arquitectura de Barcelona) - Planta baixa - Sala de grausAvda. Diagonal, 649-651 - 08028 - Barcelona
  Thesis director: DIAZ GOMEZ, CESAR | CORNADÓ BARDÓN, CÒSSIMA
  Thesis abstract: The uniformity of the urban tissue of Ildefons Cerdà’s Plan for the Eixample of Barcelona has undergone a constant transformation since its inception, due to the different difficulties, private interests and a reinterpretation from the city itself. The different volumetric variations in the buildings in the Eixample and the varied heights of the lines of the cornices or the crowning of the buildings are the result of an evolution in history, the numerous regulatory changes (progressive increase in the regulatory height and the buildable depth), and the progressive densification of the city. In front of a deformed or distorted built park, the main objective of the thesis is to provide knowledge of the story adding on the historic residential buildings in the Eixample of Barcelona.For this purpose, a representative sample of its count is based on the whole plot that comes mainly from primary sources, licenses of major works consulted in the Contemporary Municipal Archive and the Municipal District Archive. The sample contains both buildings located in bands and chamfer.The study investigates the construction of the Eixample in Barcelona from its origin to the present day, with the recognition of the regulatory framework of reference and the possibilities of growth, as well as its degree of protection, since many of these are discordant volumes. From the sample, a typological classification of the morphological variations presented by the story addings is carried out, and they are characterized in relation to the growth possibilities that the original building had at the time of construction, and the representative volumetric model is detected. It also studies the functional and constructive aspects, the materials used, as well as the different contact or encounter solutions with the existing building. Finally, it analyzes the stylistic and compositional characteristics of the story adding, and its impact on the landscape. Its singularities and main modifications are defined. Its analysis allows a more objective evaluation of the patrimonial value and a greater appreciation of the degree of sensitivity of the architectural actions carried out to date, providing tools for future interventions.The conclusions and contributions of the doctoral thesis cover the following areas: knowledge of the regulatory framework, degree of protection of the historical building, sampling, typological analysis and concretion of the number of existing story addings, volumetric study, functional characterisation, constructive recognition and stylistic, compositional and patrimonial characteristics. Transversal contributions that deepen knowledge of the Eixample of Barcelona and provide final reflections, as well as a knowledge base and future lines of research.
  
• REYNA RUIZ, CATALINA: Producción de bloques de tierra comprimida (BTC) para climas cálidos y húmedos con maquinaria adobera, y el establecimiento del agente estabilizador óptimo para el cumplimiento de los códigos locales.
  
  Author: REYNA RUIZ, CATALINA
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY
  Department: Department of Architectural Technology (TA)
  Mode: Article-based thesis
  Deposit date: 21/09/2026
  Reading date: 12/11/2026
  Reading time: 16:30
  Reading place: ETSAB (Esc.Téc.Sup.Arquit.Bcn)-Pl. Baja-Sala GradosAv. Diagonal, 649Enlace a videoconferencia: https://meet.google.com/nyr-vdqm-jboConnexión 16.00h
  Thesis director: GOMEZ SOBERON, JOSE MANUEL VICENTE | ROJAS VALENCIA, MARIA NEFTALI
  Thesis abstract: ABSTRACTAs world population grows so does the already existing housing deficit and it becomes evident that the construction industry has a responsibility to mitigate its environmental impacts that come from the direct extraction of raw materials, their transformation and the transportation. On the other hand, the implementation of climate control systems increases the energy demand.Simultaneously there is a global increase of the production of different waste materials that if not treated pose a great challenge to maintain ecosystems healthy. In the case of the United States, the annual volume of the construction and demolition residues as well as the glass that are not recycled is equivalent to 20,000 and 546 bases of the Statue of Liberty respectively.Return the gaze to the earth, is not a beautiful metaphorical phrase but a proposal for the construction industry to opt for materials with a reduced carbon footprint that can be sourced locally to reduce it transportation impact and that offer a greater insulation capacity. Those are the main characteristics of the Compressed Earth Blocks (CEB). If these include closed loop materials in their formulation; a greater sustainability is achieved.This research work studied the incorporation of local soils and aggregates as well as two closed loop materials in the production of Compressed Stabilized Earth Blocks (CSEB). One group with lime and another with cement in three different concentrations by weight (5, 10 and 15%). They were manufactured with a semi-automatic machine in a locality that had average temperature of 32 °C and 91% relative humidity. Four matrices were design per type of stabilizer, the first one was considered the one of reference and included the soils and the natural aggregates, for the second one, natural sand was replaced with recycled glass sand, for the third one the natural aggregates were replaced with the crushed concrete potion of construction and demolition wastes and the fourth one incorporated both closed loop materials (24 formulations). In the case of the CSEB with lime, 92% of the formulas exceeded the simple compression test (SCT) and capillary water absorption (AbsCoeff10) values established by the normativity. The highest SCT obtained was 4.3 MPa. For the CSEB with cement, a broader set of characteristics were studied; such as apparent porosity (AP) – immersion test, modulus of elasticity (MoE) and thermal conductivity (TC) in the second phase of the research and additionally, for the third one; thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and spectrometry of dispersed X-ray energy (EDS). With an analysis of optical images (OIA) a method was presented to correlate the formulas with some of the properties, including predicting capabilities with mathematical equations. Analyzing SEM images ITZ width values and porosity values were obtained. The greatest SCT value registered was 7.3 MPa and the lowest values of AbsCoeff10 and CT were 8 g/(cm² × min0.5) y 0.684 W/m·K. The formulas with 15% of cement showed the biggest mass loss, associated to the presence of interlayer water and the hydration products as well as the greater porosity and ITZ width reduction with the highest concentrations of silicon and calcium.
  

DOCTORAL DEGREE IN ARCHITECTURAL, CIVIL AND URBAN HERITAGE AND REFURBISHMENT OF EXISTING BUILDINGS

• GARCIA SALANOVA, ANTONIO: Arquitectura amb propòsit per a una gestió sostenible dels equipaments públics
  
  Author: GARCIA SALANOVA, ANTONIO
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL, CIVIL AND URBAN HERITAGE AND REFURBISHMENT OF EXISTING BUILDINGS
  Department: Departamento de Representación Arquitectónica (RA)
  Mode: Normal
  Deposit date: 09/09/2026
  Reading date: 18/11/2026
  Reading time: 10:30
  Reading place: ETSAB (Escuela Técnica Superior de Arquitectura de Barcelona) - Planta -1 - Aula C-B11Av. Diagonal, 649-651 - 08028 - Barcelona
  Thesis director: REDONDO DOMINGUEZ, ERNEST
  Thesis abstract: PURPOSEFUL ARCHITECTURE FOR THE SUSTAINABLE MANAGEMENT OF PUBLIC FACILITIESThis research analyses, formulates and reasonably contrasts a comprehensivea model of sustainable management of public facilities throughout their life cycle, from planning and design to operation and dismantling, and incorporates data-driven governance aimed at facilitating collaborative decision-making between the different agents involved. It is based on the hypothesis that the adoption of a comprehensive sustainable management model, based on collaborative digital methodologies —especially Building Information Modeling (BIM)—, sustainability criteria and life cycle analysis (LCA), makes it possible to overcome the limitations of traditional models of management of public facilities, characterized by the fragmentation of processes, the lack of traceability of information and the low optimization of the use phase. The work adopts a mixed methodological approach that combines systematic review of the literature, comparative analysis between management models, interviews with experts from the public and private sectors, quantitative validation and the development of an original methodological instrument: a methodological framework of 100 sustainable technical criteria applicable to the entire life cycle, which operationalizes the proposed management model. Unlike predominantly theoretical approaches, the research is carried out in a real context of public management of educational facilities and incorporates recent data and professional experiences (2024–2025), especially in relation to the implementation of BIM in the operation phase.The research also develops a practical case, a hypothetical Audiovisual Vocational Training Institute of Catalonia in the Tres Xemeneies del Besòs site, which acts as a proof of concept of the proposed comprehensive management model. This case makes it possible to contrast the coherence and feasibility of the model, as well as its architectural translation in relation to the pedagogical requirements of vocational education.The results positively show the three hypotheses formulated. Firstly, the comprehensive management model based on BIM–LCA improves the efficiency, quality and sustainability of processes. Secondly, its application determines a new flexible, modular architectural typology aimed at efficient maintenance. Thirdly, the integral model is adapted in a coherent way to the functional and pedagogical requirements of Vocational Training, reinforcing the connection between architecture, management, educational innovation and participatory governance processes. Of particular relevance is the contribution in the field of digital operation management, still underdeveloped in current institutional practice,Finally, the research proposes future lines aimed at data-driven exploitation, the integration of intelligent systems and the development of new professional profiles linked to life cycle management.
  

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

• GEBELLÍ GUINJOAN, FERRAN: User-centred Explainable Human-Robot Interaction
  
  Author: GEBELLÍ GUINJOAN, FERRAN
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Institute of Robotics and Industrial Informatics (IRI)
  Mode: Normal
  Deposit date: 15/09/2026
  Reading date: 17/11/2026
  Reading time: 10:00
  Reading place: Sala de juntes de la Facultat de Matemàtiques i Estadística (FME), Campus Diagonal Sud, Carrer de Pau Gargallo, 14, 08028 Barcelona
  Thesis director: ROS ESPINOZA, RAQUEL | LEMAIGNAN, SÉVERIN
  Thesis abstract: As robots are increasingly deployed in everyday human environments, the ability to explain their actions and decisions to users becomes essential for building trust, fostering collaboration, and enabling effective interaction. However, existing approaches to explainability in Human-Robot Interaction (HRI) often treat users as a homogeneous group, neglecting the diversity in knowledge, cognitive styles, and informational needs that characterise real-world deployments. This thesis investigates user-centred explainability in HRI through a series of longitudinal, in-the-wild studies that span the full lifecycle of explanation design, evaluation, generation, and personalisation. First, a participatory design methodology has been developed and implemented in a real healthcare use case, demonstrating that user expectations and requirements for explainability emerge gradually during in-situ deployment, and that involving users in the early design stages is crucial to incorporate a user-centred perspective on explainability. Secondly, we have explored the evaluation of explainability, focusing on one of the main desired outcomes of explainability for users: improving their understanding of the robots they interact with. We present a systematic literature review which identifies significant variability in how understandability is conceptualised and measured in HRI, highlighting the lack of standardised tools and longitudinal, in-the-wild evidence. This literature review also poses an open question about the relationship between objective and subjective understandability measures. Because of that, we conduct a two-month field study that demonstrates that objective and subjective understandability can evolve independently over time: users may report an increase in perceived understanding while the actual comprehension remains poor, underscoring the need to assess both dimensions separately. Finally, this thesis addresses the need for user-centred explanation generation, making use of Large Language Models (LLMs). We first introduce a modular framework that orchestrates specialised component explainers mapped to individual robot subsystems, which produces more accurate and contextually appropriate explanations compared to monolithic approaches. Building on this, and linking with the thesis topic and previous findings, a personalisation framework is developed that adapts explanation detail to each user by tracking acquired knowledge from previously received explanations over time. A one-month office deployment validates that personalised explanations are perceived as more appropriately detailed and remain concise, although their benefits depend on the criticality of what is being explained and diminish over extended periods, potentially due to predictability costs and anchoring effects. Taken together, these contributions advance the understanding of explainability as a dynamic, user-dependent property and provide concrete methods and empirical evidence to guide the design and development of explainable human-robot interaction in real-world settings.
  
• PEÑA CAMPOS, JOHAN SEBASTIAN: Interpretable Decision Support Systems for Early Cancer Diagnosis and Personalized Treatment
  
  Author: PEÑA CAMPOS, JOHAN SEBASTIAN
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Department of Automatic Control (ESAII)
  Mode: Change of supervisor
  Deposit date: 22/09/2026
  Reading date: 04/12/2026
  Reading time: 11:00
  Reading place: Aula 28.8 del ETSEIB, Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB) Campus Diagonal Sud, Av. Diagonal, 647, 08028 Barcelona
  Thesis director: OCAMPO MARTINEZ, CARLOS AUGUSTO | PATIÑO GUEVARA, DIEGO ALEJANDRO
  Thesis abstract: Cancer remains a leading cause of death worldwide, with gastric and metastatic prostate cancer imposing substantial burdens, particularly in low- and middle-income countries. This thesis develops interpretable Decision Support Systems (DSS) for two phases of cancer care: early diagnosis and personalized treatment optimization.The first stage targets early diagnosis of gastric cancer using routinely collected data from the Colombian health system (SGSSS). A deep learning architecture combines bidirectional Long Short-Term Memory (LSTM) networks and multi-head attention to process sequences of diagnostic codes and procedures from over 4.9 million patient trajectories, with Spanish biomedical embeddings, intelligent undersampling and Focal Loss addressing the extreme class imbalance (5103:1). It is then reformulated as a more parsimonious 2D convolutional network (CNN-2D) with demographic features, adopted as the final model for its interpretability, parsimony (~176k vs ~4.5M parameters) and competitive performance (AUC-ROC ≈ 0.835). The Nonlinear Oblique Subspace Projections (NObSP) methodology is extended to dynamic systems to interpret the model, decomposing predictions into clinically meaningful components (reconstruction error below 5%) and separating genuine clinical signal, an enriched upper-gastrointestinal pattern and a coherent age threshold, from geographic and utilization confounds.The second stage addresses personalized treatment for metastatic castrate-resistant prostate cancer (mCRPC) by integrating Evolutionary Game Theory (EGT) and Model Predictive Control (MPC). Lotka-Volterra competition models capture frequency-dependent selection among phenotypically distinct cell populations under therapy, and MPC optimizes adaptive schedules balancing tumor burden, resistance, toxicity and parsimony. For single-agent Abiraterone, it extends the median Time to Progression (TTP) from 275 days under continuous Maximum Tolerated Dose (MTD) to 420 days, roughly a 50% improvement over continuous MTD, while using about one fifth of its cumulative drug dose, and it outperforms statically optimized schedules (344 and 340 days). Dual-agent formulations coordinating Abiraterone and Docetaxel delay resistant-population dominance beyond 8,000 days, about 50% longer than the best adaptive-therapy baseline of West et al., while a blocking strategy cuts computation by over 98% versus recomputing at every step.The framework is further extended by introducing replicator dynamics, the canonical equation of EGT, as an alternative prediction model, deliberately creating a structural mismatch with the Lotka-Volterra plant while keeping the controller, objective and decision criteria unchanged. The replicator-based controller yields smoother single-agent dosing with equivalent clinical outcomes, and a minimal intervention, an 81% reduction in cumulative exposure relative to the matched Lotka-Volterra controller, suffices for sustained tumor control over the full simulation horizon in the dual-agent case, with 94% less computation than that controller. This gain follows from the modeling choice, not a different control law.Both stages treat interpretability as a core design requirement, operate within resource-constrained settings and establish validation frameworks that open pathways toward clinical evaluation, showing how mathematical and computational methods can be applied systematically across cancer care to improve patient outcomes.
  

DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING

• CASTELLS DELGADO, ANTONI: Rhythmic Emotional Stimulation and Heart Rate Variability: Exploring the Limits of Visual and Acoustic Modulation of Stress
  
  Author: CASTELLS DELGADO, ANTONI
  Programme: DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING
  Department: Department of Electronic Engineering (EEL)
  Mode: Normal
  Deposit date: 30/09/2026
  Reading date: 09/12/2026
  Reading time: 15:00
  Reading place: Aula de Graus de l'Escola Tècnica Superior d'Enginyeria de Telecomunicació de Barcelona (ETSETB), C4,C4-002, C/Jordi Girona, 1-3, 08034 Barcelona
  Thesis director: GARCIA GONZALEZ, MIQUEL ANGEL | FERNANDEZ CHIMENO, MIREYA
  Thesis abstract: This study investigates the effects of Rhythmic Visual Emotional Stimulation (RVES) and Rhythmic Acoustic Emotional Stimulation (RAES) on Heart Rate Variability (HRV), specifically analyzing SDNN, RMSSD, and IBI as key physiological indicators of autonomic function. HRV is a well-established biomarker of stress and autonomic regulation, and previous research has demonstrated that rhythmic external stimuli presented at the resonant frequency of the arterial baroreflex (0.1 Hz) can enhance HRV. RVES, originally developed by Vaschillo et al. (2008), utilizes emotionally charged visual stimuli to elicit high-amplitude HRV oscillations. This study extends prior research by exploring whether RAES, using emotionally matched acoustic stimuli, can induce comparable effects.Thirty healthy participants (15 males, 15 females) underwent both RVES and RAES protocols, with HRV measured before, during, and after each intervention. The results revealed distinct patterns in autonomic responses to the two modalities. RVES significantly increased SDNN, indicating its effectiveness in enhancing overall HRV variability, with females exhibiting stronger and more sustained HRV responses than males. RMSSD showed an initial increase during RVES but declined post-intervention, particularly in males, suggesting a short-term parasympathetic withdrawal. RAES, in contrast, had a weaker effect on HRV, producing only a modest increase in RMSSD during the intervention with no significant changes in SDNN. Additionally, BMI was found to be a moderating factor, with a significant three-way interaction between stimulation, sex, and BMI (p = 0.023) for IBI in RAES, highlighting individual variability in autonomic responses.These findings suggest that RVES is a more effective tool for autonomic modulation compared to RAES, supporting previous studies on visual rhythmic entrainment of the baroreflex. The weaker effects of RAES indicate that auditory stimuli alone may not be as effective as visual stimuli in eliciting sustained HRV changes. The significant influence of sex and BMI further emphasises the importance of individual differences in autonomic regulation. Future research should explore multimodal integration (visual-auditory rhythmic stimulation), personalised stimulus design, and repeated exposure effects to optimise HRV-based interventions for stress management and autonomic health.
  
• CLARAMUNT MOLET, MIREIA: Development of a novel clinical gait assessment tool for monitoring and stratifying neuromuscular diseases
  
  Author: CLARAMUNT MOLET, MIREIA
  Programme: DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING
  Department: Department of Mechanical Engineering (EM)
  Mode: Normal
  Deposit date: 24/07/2026
  Reading date: 17/11/2026
  Reading time: 10:30
  Reading place: Aula 28.8. Planta 1, Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB), Av. Diagonal, 647, 08028 Barcelona
  Thesis director: FONT LLAGUNES, JOSEP MARIA | IDELSOHN ZIELONKA, SEBASTIAN
  Thesis abstract: Neuromuscular diseases are chronic and degenerative conditions of the skeletal musculature that progressively impair gait, one of the primary determinants of functional independence. Their monitoring, both in clinical practice and clinical trials, relies on clinical scales and functional tests that are subject to observational bias, ceiling effects, and insufficient sensitivity to detect subtle changes. At a time when novel disease-modifying therapies are emerging, the availability of an objective, portable tool integrable into routine clinical practice for biomechanical mobility assessment represents an unmet clinical need.To address this need, the present thesis develops the biomechanical algorithms to derive spatiotemporal parameters, sagittal joint kinematics, muscle activation, plantar pressure distribution, and heart rate from raw wearable sensor data. Data capture relies on the Ephion Mobility system, which integrates and synchronises inertial sensors, surface electromyography, plantar pressure insoles, and a cardiac sensor within a single mobile application. Using this system, data were collected from 176 volunteers, 90 patients and 86 controls, across two countries and standard hospital settings.The first study, conducted in collaboration with Hospital Sant Joan de Déu, serves as the proof of concept. It validates a multidimensional gait score for Duchenne muscular dystrophy, derived from multisensor data through unsupervised learning, which demonstrates good agreement with current clinical metrics and promising capacity for disease monitoring.With the validity of the approach established, the second study, carried out at the Copenhagen Neuromuscular Center, explores its applicability in two conditions with markedly different distributions of muscle weakness: Becker muscular dystrophy and myotonic dystrophy type 1. Biomechanical gait assessment is shown to discriminate disease-specific patterns and severity gradients that functional tests do not capture. Finally, the third study, conducted in collaboration with the Spanish Pompe Patient Association, addresses the most demanding question: whether the tool can detect longitudinal progression in a slowly evolving disease. The Pompe-MDPI achieves statistical significance over one year of follow-up in a context where current metrics fail to detect change over the same interval.Taken together, the results provide preliminary evidence that portable multidimensional biomechanical assessment is clinically feasible, sensitive to functional severity, and capable of detecting longitudinal disease progression where conventional measures fall short. The derived scores represent promising candidates as digital biomarkers for natural history studies and clinical trials of disease-modifying therapies.
  
• GARCÍA HERNANDO, GABRIEL: Development of an advisory system for the administration of anaesthetics and analgesics
  
  Author: GARCÍA HERNANDO, GABRIEL
  Programme: DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING
  Department: Department of Automatic Control (ESAII)
  Mode: Normal
  Deposit date: 18/09/2026
  Reading date: 27/11/2026
  Reading time: 11:00
  Reading place: Aula 28.8, Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB), Campus Diagonal Sud, Av. Diagonal, 647 08028 Barcelona
  Thesis director: VALLVERDU FERRER, MARIA MONTSERRAT | GONZÁLEZ PIJUAN, CARMEN
  Thesis abstract: Current technology provides valuable indices of hypnotic state, and although adverse anaesthesia effects have declined, important challenges remain. In particular, distinguishing between pharmacologically distinct anaesthetic agents and reliably predicting and detecting intraoperative nociception from physiological signals would support more personalized perioperative care.Electroencephalography (EEG) and heart rate variability (HRV), derived from RR intervals, provide complementary information on brain and autonomic responses to anaesthetic drugs and noxious stimuli. However, the optimal parameterisation of nonlinear descriptors, such as time delay, symbolic encoding, frequency band, and analytical signal representation, has not been systematically explored for drug discrimination and nociception assessment.This thesis pursues two objectives: first, discrimination between three pharmacological states, no drug (ND), propofol (P), and remifentanil (R), using EEG-based symbolic dynamics and Poincaré plot analysis; and second, prediction and detection of intraoperative nociception, defined as movement response to a noxious stimulus, using Poincaré analysis of EEG and RR signals.A total of 599 patients under general anaesthesia were analysed. For drug discrimination, 84 patients met stability criteria (28 ND, 28 P, 28 R). For nociception analysis, 163 patients yielded 329 stimulus instances (159 movers, 170 non-movers). At the patient level, 55 were consistent movers, 72 consistent non-movers, and 36 showed mixed responses.EEG signals were decomposed into seven frequency bands. For each band, three Hilbert-based representations were derived: amplitude, envelope, and phase. The first derivative was also computed for symbolic dynamics. Poincaré descriptors and symbolic features were extracted across all bands and representations, forming a multidimensional feature space applied consistently to both analyses.Symbolic dynamics parameters (number of symbols, word length, quantification factor, sampling rate) were systematically optimized. For Poincaré analysis, time delay was exhaustively evaluated across traditional, segmented (SPPA), and asymmetry-based descriptors, applied to all EEG representations and RR windows (30–60 s). Nonlinearity was validated using surrogate data. Linear EEG and HRV features were also assessed. Quadratic discriminant analysis with leave-one-out cross-validation was used throughout. In all cases, combining features across modalities and representations outperformed single-feature approaches.For drug discrimination, symbolic dynamics achieved the highest performance (AUC = 0.952 ND vs P; 0.919 P vs R; 0.837 ND vs R). Poincaré descriptors provided complementary results: traditional descriptors performed best for ND vs P (AUC = 0.836, F1 = 84.2%) and ND vs R (AUC = 0.835, F1 = 84.7%), while asymmetry-based descriptors were optimal for P vs R (AUC = 0.893, F1 = 90.0%).For nociception, prediction was best achieved using SPPA descriptors of RR intervals over a 30 s pre-stimulus window (AUC = 0.691, F1 = 68.3%), while detection was best with traditional Poincaré descriptors of EEG (AUC = 0.700, F1 = 72.9%).Overall, nonlinear analysis of EEG and RR signals, combined with systematic parameter optimisation, enables robust drug discrimination and meaningful nociception assessment from a single frontal EEG channel. Although nociception performance was moderate, reflecting the complexity of predicting behavioural responses under anaesthesia, the consistent benefit of multimodal and multi-representation features supports their use in next-generation personalized anaesthesia monitoring systems.
  

DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING

• MARÍN RIVAS, ENRIQUE DAVID: Mechanochemical Preparation of Pd-Cu/CeO₂ Catalysts for Carbon Monoxide Oxidation
  
  Author: MARÍN RIVAS, ENRIQUE DAVID
  Programme: DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 31/07/2026
  Reading date: 13/11/2026
  Reading time: 11:00
  Reading place: Sala Polivalent - Edifici IEEBEhttps://eebe.upc.edu/ca/lescola/com-arribar
  Thesis director: LLORCA PIQUE, JORDI | VENDRELL VILLAFRUELA, XAVIER
  Thesis abstract: Cerium oxide (CeO2)-based catalysts are widely studied for oxidation reactions due to their redox properties, oxygen storage capacity, and ability to stabilise metal-support interfacial sites. Among these systems, Pd/CeO2 and Cu/CeO2 catalysts are of particular interest for low-temperature CO oxidation. However, their catalytic behaviour depends on the synthesis method, metal dispersion, and defect structure. In this thesis, mechanochemical synthesis by planetary ball milling was investigated as a sustainable route for preparing CeO2-based catalysts, together with different treatments aimed at modifying their structural and catalytic properties.The first part of this work focused on Pd/CeO2 catalysts prepared by planetary ball milling under controlled atmospheres. The results demonstrated that mechanochemical synthesis promotes the formation of active Pd-Ce interfacial structures. Catalysts prepared at 250 rpm under air for 10 min exhibited the highest CO oxidation activity, outperforming those prepared by conventional impregnation. This behaviour was attributed to the formation of PdOx-Ce interfacial species and strong metal-support interactions. Electron microscopy revealed highly dispersed Pd nanoparticles and clusters on the ceria surface.The second part investigated Cu/CeO2 catalysts prepared by mechanochemical methods using different precursors, calcination temperatures, milling conditions, and reduction treatments. The results showed that mechanochemical synthesis can produce catalysts with superior performance compared with conventional methods. Catalysts prepared from copper nitrate and calcined at 300 °C showed the best activity. H2/N2 reduction further enhanced catalytic performance. Electron microscopy confirmed the absence of large CuOx aggregates and the presence of highly dispersed copper species. In addition, operando synchrotron experiments revealed dynamic Cu+/Cu2+ redox cycling under reaction conditions, contributing to catalyst stability and progressive activation.The third part addressed bimetallic Pd-Cu/CeO2 catalysts prepared by planetary ball milling. Different Cu/Pd ratios, metal loadings, and deposition sequences were evaluated. Under non-reduced conditions, Pd incorporation did not significantly improve activity compared with monometallic Cu/CeO2 catalysts. However, after H2 reduction, the bimetallic catalysts exhibited enhanced activity, highlighting the importance of pre-reduction in the formation of favourable Pd-Cu-Ce interfacial structures.Electron beam irradiation was also investigated as a post-synthesis treatment for Pd/CeO2 catalysts. Irradiation improved catalytic activity and reduced the apparent activation energy for CO oxidation. Raman and XPS analyses revealed an increase in structural defects, peroxide species, and additional PdOx-Ce interfacial sites.Finally, flash sintering was applied to ceria-based materials. Although the treatment induced significant microstructural and electrical modifications, the resulting materials exhibited lower catalytic activity than untreated CeO2, mainly due to the thermal effects associated with Joule heating.Overall, this thesis demonstrates that mechanochemical synthesis is an effective strategy for preparing highly active CeO2-based catalysts. The catalytic behaviour of Pd/CeO2, Cu/CeO2, and Pd-Cu/CeO2 systems is governed by metal-ceria interfacial structures, metal dispersion, and the redox properties of the support.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• FARSHBAF, SIMA: Computational and Data-Driven Design of Additively Manufactured Auxetic Metamaterials for Enhanced Energy Absorption
  
  Author: FARSHBAF, SIMA
  Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Article-based thesis
  Deposit date: 29/09/2026
  Reading date: 30/11/2026
  Reading time: 11:00
  Reading place: Sala Zienkiewich (CIMNE) Building C1, UPC - Campus North Gran Capitan S/N 08034 Barcelona
  Thesis director: DIALAMISHABANKAREH SOLTANI, NARGES | CERVERA RUIZ, LUIS MIGUEL
  Thesis abstract: This doctoral thesis presents a computational-experimental framework for the analysis, design, and optimization of auxetic metamaterials with enhanced energy absorption performance. The proposed methodology combines experimental characterization, nonlinear finite element analysis, additive manufacturing, structural design, and machine learning to enable the efficient development of lightweight metamaterials with tailored mechanical properties.The thesis first investigates the mechanical behavior of conventional and auxetic cellular structures through experimental testing and validated nonlinear finite element simulations. The analyses provide insight into the influence of cellular topology, loading direction, and deformation mechanisms on the mechanical response, demonstrating the superior energy absorption capability of re-entrant auxetic structures over conventional honeycomb architectures.Building on these findings, novel geometrical modifications of the conventional re-entrant unit cell are proposed to enhance its auxetic response and energy absorption capacity while preserving its characteristic deformation mechanisms. The numerical predictions are experimentally validated, confirming the effectiveness of the proposed designs. Compared with the base design, the modifications achieve improvements of up to 1250\% in energy absorption capacity and 860\% in specific energy absorption.To accelerate the design process, a machine learning-based forward and inverse design framework is developed using datasets generated from validated finite element simulations. The proposed methodology enables efficient prediction of nonlinear mechanical responses and inverse identification of unit-cell geometries for both uniform and thickness-graded auxetic structures with prescribed mechanical performance. Furthermore, a physics-guided machine learning framework that combines a layer-wise response decomposition strategy with deep neural networks is developed to substantially reduce the computational cost of dataset generation while enhancing predictive performance. The proposed framework achieves prediction errors below 2.5\%, including in extrapolation scenarios, using only 10 training samples, compared with 2,145 samples required by the conventional deep neural network.Overall, this thesis establishes a framework integrating computational mechanics, experimental validation, structural optimization, and physics-guided machine learning for the efficient design of advanced auxetic metamaterials. The proposed methodologies provide practical tools for developing lightweight structures with tailored mechanical performance and enhanced energy absorption, while providing a methodological basis for extending data-driven design approaches to other metamaterial systems.
  

DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS

• BENÍTEZ COLOMINAS, POL: Modeling Lattice-Mediated Optoelectronic Response in Anharmonic Semiconductors: A First-Principles and Machine Learning Study
  
  Author: BENÍTEZ COLOMINAS, POL
  Programme: DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS
  Department: Department of Physics (FIS)
  Mode: Article-based thesis
  Deposit date: 15/10/2026
  Reading date: 12/11/2026
  Reading time: 10:00
  Reading place: Sala Polivalent, Edifici A, Escola d'Enginyeria de Barcelona Est (EEBE), Campus Diagonal Besos
  Thesis director: CAZORLA SILVA, CLAUDIO | SAUCEDO SILVA, EDGARDO ADEMAR
  Thesis abstract: The rapid development of next-generation energy technologies, such as photovoltaics, necessitates the discovery of materials with highly tunable and resilient optoelectronic properties. This dissertation investigates the fundamental role of lattice dynamics in phase stability and thermal renormalization of the optoelectronic properties of anharmonic materials exhibiting strong electron-phonon coupling, through an integrated approach combining first-principles quantum simulations and machine learning.The first part of this work analyzes in detail a family of materials known as antiperovskites, with chemical formula Ag3BC (B: S, Se; C: Cl, Br, I), that is fundamentally very interesting and highly relevant for energy and optoelectronic applications. In particular, by employing crystal structure prediction and free-energy calculations, we demonstrate that the cubic phase identified in experiments is dynamically stabilized at finite temperatures or represents kinetically trapped metastable states. Following this, we quantify a giant thermally induced band-gap renormalization in these systems, revealing that large-amplitude phonon displacements at room temperature can narrow the electronic band gap by more than 50%. This finding not only reconciles theory with experiment but also reveals a sensitive coupling between polar lattice distortions and electronic hybridization. We leverage this insight to propose a novel paradigm for “electro-optoelectronic” tuning, demonstrating that external electric fields can mimic thermal effects to provide non-chemical control over the band gap in centrosymmetric semiconductors.To scale these findings to more complex systems, the second part of the thesis focuses on the development of physics-informed artificial intelligence (AI) workflows. We show that graph neural networks trained on datasets generated via phonon-informed sampling, rather than random displacements, exhibit superior accuracy and generalizability. Through model interpretability analysis, we prove that these networks effectively learn the relative importance of specific chemical bonds in determining electronic responses. Finally, we implement an AI-workflow to evaluate the thermal response of complex solid solutions (Ag3SBr(x)I(1-x)), successfully simulating systems that were previously computationally prohibitively expensive using standard methods. Collectively, this research establishes that the explicit inclusion of lattice dynamics is essential for the accurate description of anharmonic materials and provides a robust, AI-accelerated framework for the “temperature-aware” design of functional semiconductors.
  
• DYHR, SØREN ISTVÁN ADORJÁN: Optimal Metrics in Odd-Dimensional Geometry: Reeb Dynamics and Applications in Fluid Mechanics
  
  Author: DYHR, SØREN ISTVÁN ADORJÁN
  Programme: DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 11/09/2026
  Reading date: 12/11/2026
  Reading time: 13:00
  Reading place: Sala de juntes Facultat de Matemàtiques i Estadística, Campus Sud - UPC
  Thesis director: MIRANDA GALCERÁN, EVA | GONZÁLEZ PRIETO, ÁNGEL
  Thesis abstract: Particles described by Hamiltonian mechanics tend to stay on odd-dimensional hypersurfaces of symplectic manifolds. In this thesis we study a generalization of the geometric structures appearing on such submanifolds. They all have a Reeb vector field and, in dimension three, coincide with stable Hamiltonian structures (SHS), a class which includes both cosymplectic and contact structures. We study two problems concerning metrics compatible with such structures.First we consider the Navier-Stokes equations, which describe viscous incompressible fluids. It turns out that Reeb vector fields of cosymplectic structures are stationary solutions for all compatible metrics. We create a cosymplectic plug from a construction by Cardona, Miranda, Peralta-Salas, and Presas, which realizes Turing machines as vector fields. Their construction was originally used in contact geometry to extend these vector fields to stationary solutions of the 3D Euler equations, which model ideal (inviscid) fluids. We extend their result by embedding the plug to obtain cosymplectic Reeb fields, and thus stationary solutions to the 3D Navier-Stokes equations, capable of simulating any Turing machine.Second we study an energy functional on the space of compatible metrics, originally considered for contact manifolds by Blair as well as by Chern and Hamilton. The metrics of minimal energy for contact manifolds in dimension three have been classified. We generalize the functional and the classification to three-dimensional SHSs and find that positive energy critical metrics correspond to the algebraic Anosov flows.Finally we obtain a similar result in higher dimension when there exist certain first integrals satisfying a non-degeneracy condition. We also classify a family of five-dimensional examples of critical metrics, including some not satisfying the non-degeneracy condition.
  
• MARCH PONS, DAVID: Collective Decision-Making in Bio-Inspired Swarms: From Behavioral Rules to Interaction Structure
  
  Author: MARCH PONS, DAVID
  Programme: DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 26/10/2026
  Reading date: 16/12/2026
  Reading time: 15:00
  Reading place: Sala Teleensenyament, Edifici B3 - Ricardo Valle (Sala 103), Planta 1, Campus Nord UPC
  Thesis director: PASTOR SATORRAS, ROMUALDO | MIGUEL LOPEZ, M. DEL CARMEN
  Thesis abstract: Living groups, from human societies to insect colonies, self-organize and coordinate in order to thrive in nature. Collective decisions are a central task in their life cycles, keeping the group cohesive around social norms, foraging strategies or collective movement. This self-organization emerges from the individual behaviors and social interactions between members of the group, so identifying the mechanisms that let a group gather and exchange information and reach a decision outcome is a central question in the study of collective behavior.The self-organizing capacity of insect societies has, in turn, long inspired the design of decentralized protocols for swarm robotics: combining insights from nature with engineering principles allows artificial swarms to reach collective decisions---on tasks such as effort allocation or objective selection---without any external control. Studying how such collective behaviors emerge from the interactions between the units of a group sits at the core of complex systems science, and it is within this framework that the present thesis addresses collective decision-making.Specifically, we investigate mechanisms of collective decision-making inspired by the social behavior of honeybee swarms endowed with a nest site selection task: a paradigmatic example in which individual behavior---information seeking, option quality assessment---and social interactions---recruitment of uncommitted peers, inhibition of divergent opinions---intertwine to produce consensus as an emergent property of the swarm. From these traits we extract basic modelling assumptions, studying the resulting agent-based models through both mean-field analytical methods and stochastic simulations.We first examine how the balance between individual and social information-seeking, and between competing option qualities, shapes decision accuracy and speed. We further show that the best outcomes are attained at the onset of criticality, and that the model replicates superorganism-like features, with the swarm reacting to physical stimuli as a single cognitive unit. Then, we implement this model on a swarm of Kilobot robots, complemented by virtual simulations, to establish how the percolation of a proximity-based, time-varying communication network---governed by interaction duration, range and robot density---shapes the emergence of consensus under real sensing and communication constraints. Building on this, we introduce a non-linear cross-inhibition signal that captures a many-body effect, whereby an agent abandons a divergent opinion only after receiving a sufficient number of inhibitory signals. We show that this signal enhances consensus accuracy and decision speed, at the cost of reliably selecting the higher-quality option. Finally, we address the complementary symmetry-breaking problem, by which the group must resolve a decision deadlock between equivalent options. We show that higher-order group interactions---whose effect is not reducible to a sum of pairwise ties---offer an alternative to cross-inhibition, giving rise to a qualitatively different landscape of first- and second-order phase transitions.Together, these results delineate how individual behavioral rules and the structure of social interactions---time-varying, pairwise or higher-order, linear or non-linear---shape the speed, accuracy and robustness of collective consensus. Beyond honeybee swarms, this work contributes theoretical tools and design principles for decentralized decision-making in artificial swarms, bridging mean-field theory, network science and embodied robotic experimentation.
  
• MONTALÀ SALES, RICARD: Data-Driven Strategies for Active Flow Control in Wings
  
  Author: MONTALÀ SALES, RICARD
  Programme: DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS
  Department: Department of Physics (FIS)
  Mode: Article-based thesis
  Deposit date: 21/10/2026
  Reading date: 30/11/2026
  Reading time: 10:00
  Reading place: Sala de Conferències TR5, Planta 1, Porta 1.41. 'ESEIAAT (UPC- Campus Terrassa)
  Thesis director: SORIA GUERRERO, MANUEL | RODRIGUEZ PEREZ, IVETTE MARIA
  Thesis abstract: Flow separation remains a major limitation to wing aerodynamic performance, particularly at low speeds, where viscous effects become increasingly important and reduce the ability of boundary layers to withstand adverse pressure gradients. Active flow control (AFC) offers the possibility of mitigating these effects by modifying the flow through localized actuation. However, designing effective AFC strategies becomes increasingly challenging for complex separated flows, for which the relationship between actuation, flow dynamics, and aerodynamic performance is highly nonlinear. This doctoral dissertation investigates data-driven methodologies, combined with high-fidelity computational fluid dynamics (CFD), for the autonomous discovery of AFC strategies in increasingly complex aerodynamic configurations.The research first establishes a detailed physical understanding of the turbulent flow past the three-element 30P30N high-lift wing using wall-resolved large eddy simulations (LES) at a Reynolds number of Re=750,000. The analysis identifies the main flow mechanisms governing the aerodynamic performance of the configuration, including boundary-layer development, separated shear layers, wake dynamics, and the interactions between the slat, main element, and flap. Conventional predetermined AFC strategies are subsequently investigated, demonstrating their ability to modify the flow while highlighting the difficulty of identifying effective actuation parameters solely from physical intuition.To overcome these limitations, a computational framework coupling high-fidelity CFD with deep reinforcement learning (DRL) is developed and systematically validated across increasingly complex flow configurations. The framework is first validated for the canonical flow past a circular cylinder at Re=100, yielding results consistent with those reported in the literature. It is then applied to the NACA0012 airfoil at Re=1,000 and high angle of attack, where the flow exhibits weakly turbulent characteristics. An extensive analysis of the control strategy learned by the DRL agent demonstrates its ability to recover actuation mechanisms consistent with established flow-control strategies reported in the literature. The methodology is subsequently applied to the fully separated SD7003 airfoil at Re=60,000, where the learned control policies considerably outperform predetermined AFC strategies. Furthermore, wall-mounted sensors are shown to achieve comparable control performance to wake-based sensing while requiring fewer sensors, providing a more realistic sensing configuration for practical AFC applications.Finally, the methodology is applied to the 30P30N high-lift wing initially studied, revealing the computational challenges associated with DRL at higher Reynolds numbers. The reduced time step required by the high-fidelity CFD simulations, combined with the large number of flow-control experiences required for DRL training, results in substantial computational costs and complicates the selection of suitable control configurations and hyperparameters. Bayesian optimization (BO) is therefore investigated as an alternative data-driven methodology for the low-dimensional control problem. After only 19 CFD evaluations, BO identifies an effective actuation strategy that maintains the baseline lift while reducing drag and increasing aerodynamic efficiency. Compared with the corresponding DRL training campaign, BO requires approximately half the wall-clock time and nearly sixty times fewer GPU-hours.
  

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

• CARO ROCA, MARTÍ: Efficient Tailoring of AI-based Solutions for Safety-Critical Systems
  
  Author: CARO ROCA, MARTÍ
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 10/09/2026
  Reading date: 19/11/2026
  Reading time: 10:15
  Reading place: C6-E101
  Thesis director: ABELLA FERRER, JAIME
  Thesis abstract: The increasing performance of computing platforms enables the use of larger Deep Neural Networks (DNNs) that achieve the accuracy needed for real-time applications such as Camera-based Object Detection (CBOD) in Autonomous Driving (AD). While high inference accuracy is mandatory for DNNs in Critical Real-Time Embedded Systems (CRTES), memory bandwidth and energy consumption are also critical factors, often constraining the achievable performance and determining whether those DNNs meet application requirements (e.g., frames per second). Therefore, some highly accurate but large DNN models must be optimized to operate under these constraints.Moreover, automotive applications with safety requirements must adhere to standards such as ISO 26262, which impose the use of diverse redundancy for the highest integrity level (ASIL D) to mitigate common-cause faults — random hardware faults that can potentially affect redundant components similarly and remain undetected. Dual Modular Redundancy (DMR), also referred to as Dual-Core LockStep (DCLS) for CPUs, and Triple Modular Redundancy (TMR), often combined with some form of diversity, are commonly used in safety-critical systems to provide fault detection and tolerance. However, efficiently realizing diverse redundancy for DNN-based safety-related tasks, such as object detection, remains an open challenge, as these applications can leverage semantic redundancy rather than bit-level equivalence.In this thesis, we first perform an at-scale evaluation of several approximation domains to optimize DNN models. In particular, we focus on CBOD models, which are essential in AD to detect objects surrounding the vehicle. We study several techniques independently and jointly — including reduced-precision arithmetic, approximate computing, and low-voltage operation — to assess how they can be combined to significantly reduce the area, delay, and energy of AI systems. We further extend this analysis by studying the impact of weight clustering for different arithmetic representations, including floating-point and integer formats, providing insights to guide the development of low-power CBOD accelerators with negligible impact on accuracy.Next, we design an efficient diverse redundancy scheme tailored to AI applications by leveraging reduced precision. The proposed scheme operates on reduced-precision arithmetic obtained by dropping selected bits from the fetched data of the main accelerator. This enables mitigation of random hardware faults while reducing the delay, area, and energy of the redundant accelerator compared to traditional DCLS implementations, without noticeable accuracy loss.We also propose a diverse redundancy technique with a similar cost to DCLS-like implementations but with a significant accuracy increase, achieved by mitigating AI model inaccuracies and avoiding the need for specific hardware support. This scheme applies input transformations (e.g., horizontal flip or Gaussian noise) and uses merging algorithms to fuse detections from redundant components. We further evaluate its ability to mitigate adversarial attacks, allowing a single mechanism to simultaneously address random hardware faults, DNN model inaccuracies, and adversarial attacks. Finally, we show that the scheme can be generalized to other AI models and tasks, confirming that the observed conclusions and trends hold across different AI modalities.Overall, this thesis studies approximation techniques that can significantly optimize AI models for CRTES and proposes two enhanced diverse redundancy techniques: one targeting energy efficiency and another focusing on improving the accuracy of the diverse redundant system with negligible overhead.
  

DOCTORAL DEGREE IN COMPUTING

• PONS RECASENS, GERARD: Evolving Knowledge Graphs: Continuous Knowledge Acquisition, Adaptation, and Exploitation
  
  Author: PONS RECASENS, GERARD
  Programme: DOCTORAL DEGREE IN COMPUTING
  Department: Department of Computer Science (CS)
  Mode: Normal
  Deposit date: 01/10/2026
  Reading date: 11/11/2026
  Reading time: 15:00
  Reading place: Sala d'Actes FIB - Edifici B6 Campus Nord
  Thesis director: QUERALT CALAFAT, ANNA | BILALLI, BESIM
  Thesis abstract: Modern systems continuously generate vast amounts of heterogeneous data. While this data contains valuable information, its full potential remains difficult to realize when it is treated as a collection of isolated observations lacking meaning and context. Unlocking its full value therefore requires enriching data with explicit semantics that capture concepts, relationships, and contextual information, transforming isolated observations into structured knowledge. This thesis argues that such semantic enrichment constitutes a fundamental step towards building more effective intelligent systems. In this context, Knowledge Graphs (KGs) provide a natural framework for representing and organizing this knowledge, while Knowledge Graph Embeddings (KGEs) transform it into latent representations that can be flexibly exploited by modern Machine Learning methods to address evolving analytical needs.As knowledge is not static, realizing this vision requires addressing challenges that span its entire life cycle. First, data originating from heterogeneous and unstructured sources must be incorporated into a continuously evolving knowledge structure, where it is enriched with semantics. Second, as this knowledge structure evolves, its latent representations must be continuously updated while preserving previously acquired knowledge. Finally, the evolving knowledge structure and its learned representations must be effectively exploited to support adaptive behavior in intelligent systems.This thesis addresses these challenges through the framework of evolving KGs. For knowledge acquisition from unstructured sources, it focuses on textual information and proposes a schema-aware entity disambiguation method that combines Large Language Models (LLMs) with the hierarchical structure of KGs, improving adaptability across domains without requiring model retraining. To maintain latent representations over time, it investigates the continual adaptation of KGEs. Within this scope, it identifies a previously overlooked phenomenon that contributes to the degradation of previously acquired knowledge and proposes an adjusted evaluation protocol to accurately capture its effects. Additionally, it introduces an initialization strategy for newly added embeddings that enhances knowledge acquisition while mitigating this performance degradation. Finally, for knowledge exploitation, it demonstrates how continuously evolving KGs and their learned representations can support adaptive recommendation and intent-aware assistance in experiment-driven data analytics environments. Together, these advancements contribute towards enabling evolving KGs to continuously acquire, adapt, and exploit knowledge.
  

DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING

• ESCOBAR ESCOBAR, KEVIN ISAAC: Strengthening of existing reinforced concrete structures with textile reinforced mortars
  
  Author: ESCOBAR ESCOBAR, KEVIN ISAAC
  Programme: DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 17/09/2026
  Reading date: 12/11/2026
  Reading time: 11:30
  Reading place: ETSECCPB. UPC, Campus Nord- Edifici C1. Sala: 002C/Jordi Girona, 1-3 , 08034 Barcelona
  Thesis director: OLLER IBARS, EVA MARIA | MURCIA DELSO, JUAN
  Thesis abstract: The ageing of reinforced concrete (RC) infrastructures has driven the development of efficient repair and strengthening methods to extend their service life. Fibre-reinforced polymer (FRP) have been widely used for structural strengthening owing to their high resistance and lightness, but their limitations regarding fire resistance, substrate compatibility, and application conditions have motivated the development of alternative solutions. A promising alternative is the textile reinforced mortar (TRM), also known as fabric reinforced cementitious matrix (FRCM), comprising an open-mesh textile made of high-strength fibres embedded in an inorganic matrix.This thesis investigates the use of TRM for the strengthening and rehabilitation of RC structures, progressing from material characterisation to application in structural elements, including corrosion-damaged members. The research first focuses on the mechanical characterisation of TRM composites made with different textiles and mortars and then examines their structural performance in RC beams and corroded RC slabs subjected to flexure. This research contributes to the understanding of the tensile and bond behaviour of TRM, while addressing knowledge gaps related to the use of alternative textile-mortar combinations and TRM application for the repair and strengthening of corrosion-damaged RC elements.During the mechanical characterisation phase, tensile and single-lap shear tests were performed on carbon, basalt and hemp TRM systems using different mortars with ordinary Portland cement (OPC), OPC with synthetic fibres, OPC with glass fibres, and calcium sulfoaluminate cement (CSAC). Digital image correlation (DIC) was used to analyse cracking, strain evolution, and failure mechanisms. Results showed that textile type, reinforcement ratio, and mortar significantly affect tensile and bond behaviour. CSAC-based carbon and basalt TRM achieved tensile performance comparable to OPC systems, while bond behaviour depended on the textile. A trilinear cohesive bond model successfully reproduced the force-slip response and identified an optimal bond length. For hemp TRM the highest tensile performance was achieved with 1% reinforcement and OPC mortar (845 MPa tensile strength, 2.1% ultimate strain). Debonding at the matrix-textile interface was the predominant failure mode, with effective bond lengths between 109 and 125 mm. Following the material characterisation stage, TRM was applied to strengthen RC beams in flexure. Three-point bending tests were performed on beams strengthened with carbon and hemp-based TRM systems, including a carbon TRM system with spike anchors. In these elements, the dominant failure mode was concrete crushing, accompanied by partial TRM debonding, which limited textile utilisation. Experimental results, together with parametric finite element analyses, showed that flexural performance strongly depends on bond quality and on the area ratio between internal steel reinforcement and external TRM reinforcement.The thesis extends the application of TRM to the strengthening of RC slabs affected by chloride-induced corrosion. Four slabs were subjected to accelerated corrosion, producing deterioration with a target 8% mass loss in the longitudinal reinforcement over half of the slab width. Two slabs were then repaired and strengthened with two layers of carbon TRM using mortar with short glass fibres and carbon spike anchors arranged in two different layouts. Flexural tests showed that the strengthened slabs achieved increases in maximum load of 32% to 39% compared with the un-strengthened corroded slabs. Both spike anchors arrangements were effective in enabling textile rupture. Parametric finite element analyses showed the effectiveness of the TRM for different levels of corrosion and number of TRM layers. The investigation shows that TRM is a promising solution for strengthening and rehabilitation of undamaged and corrosion-damaged RC structures.
  

DOCTORAL DEGREE IN EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS

• CUESTA ARRILLAGA, JOKIN: Physics-integrated artificial intelligence prognostics for wind turbine components under uncertainty and data scarcity
  
  Author: CUESTA ARRILLAGA, JOKIN
  Programme: DOCTORAL DEGREE IN EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 11/09/2026
  Reading date: 20/11/2026
  Reading time: 10:00
  Reading place: EEBE. CAMPUS BESOSEdifici ASala PolivalentAvinguda d'Eduard Maristany, 16, 08019 Barcelona / Sant Adrià de Besòs
  Thesis director: VIDAL SEGUI, YOLANDA | LETURIONDO ZUBIZARRETA, URKO | POZO MONTERO, FRANCESC
  Thesis abstract: Wind energy plays a central role in the global transition towards sustainable energy systems. However, the operation and maintenance costs associated with wind turbines remain a major challenge, particularly due to unexpected component failures and the difficulty of accurately predicting their remaining useful life. Prognostics and health management has emerged as a key enabler of predictive maintenance strategies, yet current prognostic approaches often face limitations related to data scarcity and quality, limited observability of degradation, lack of physical consistency, and inadequate uncertainty quantification.This thesis addresses these challenges by developing adaptive physics-informed prognostic methodologies for wind turbine components operating under uncertainty and with scarce degradation data. A unified uncertainty-aware prognostic framework is proposed that integrates physical knowledge into data-driven models based on the observability level of the degradation process. For directly observable degradation scenarios, physics-informed neural network architectures based on time-series transformers are developed by embedding degradation laws into the learning process. For indirectly observable degradation scenarios, where degradation cannot be measured directly, a physics-guided framework is introduced to construct health indicators from operational data through residual-based representations of healthy system behavior.The proposed methodologies are validated through a two-level experimental strategy. First, a dedicated laboratory testbed is designed to generate controlled, run-to-failure wear data. Second, the framework is assessed using real wind turbine SCADA data from gearbox degradation cases to demonstrate its applicability in operational environments. In both scenarios, multiple uncertainty quantification techniques are investigated and benchmarked to characterize predictive confidence and support maintenance decision-making.The results demonstrate that integrating physical knowledge into advanced deep learning architectures improves degradation forecasting accuracy, robustness, and remaining useful life estimation performance compared with purely data-driven approaches. Furthermore, the proposed uncertainty-aware framework provides reliable confidence estimates, enhancing the interpretability and operational usefulness of prognostic predictions. The findings contribute to the development of trustworthy hybrid prognostic systems for wind energy applications and maintenance timing, supporting wind-farm availability management and the dependable operation of renewable energy assets.
  
• WANG, SHUN: Artificial Intelligence for Wind Turbine Condition Monitoring and Fault Diagnosis Towards Predictive Maintenance
  
  Author: WANG, SHUN
  Programme: DOCTORAL DEGREE IN EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 21/09/2026
  Reading date: 23/11/2026
  Reading time: 10:00
  Reading place: EEBE. CAMPUS BESOSEdifici ASala PolivalentAvinguda d'Eduard Maristany, 16, 08019 Barcelona / Sant Adrià de Besòs
  Thesis director: POZO MONTERO, FRANCESC | VIDAL SEGUI, YOLANDA
  Thesis abstract: The continued expansion of wind energy depends on the reliable operation of large, complex, and geographically dispersed turbines. Late fault detection can cause secondary damage, unplanned downtime, and costly maintenance. Artificial intelligence can learn condition patterns from turbine measurements, but its practical use is limited by scarce fault labels, changing operating conditions, noise, and interactions among variables.This doctoral thesis develops and validates physically informed artificial intelligence strategies for wind turbine predictive maintenance through three information routes: vibration monitoring, supervisory control and data acquisition (SCADA) monitoring, and thermal-image fault diagnosis. The research combines unsupervised representation learning, healthy-data-based anomaly detection, normal behavior modeling, and machine-learning classification. Vibration and SCADA data are used to detect departures from healthy operation, whereas thermal images distinguish labeled electrical equipment conditions. The central question is how representations, references, and inputs can preserve health-related information and support reliable detection or diagnosis. The vibration research progresses from component-level degradation assessment to system-level monitoring and robustness under variable speed. Across four public bearing run-to-failure datasets, the logarithmic envelope spectrum is combined with a variational autoencoder trained only on healthy data to produce an interpretable health index for early fault detection and degradation tracking. For vibration data from an operational research wind turbine, a variational autoencoder learns healthy feature distributions, while exponentially weighted moving average monitoring stabilizes the reconstruction-error indicator for detecting documented pitch faults, icing events, and aerodynamic imbalances. In controlled gearbox experiments, a speed-invariant autoencoder integrates order-domain alignment, cross-condition interpolation, and speed-conditioned reconstruction to obtain stable and threshold-consistent health indicators across the evaluated steady, variable, and unseen speeds. The SCADA-based research examines how input design affects the early-fault sensitivity of normal behavior models. Conventional models can conceal early degradation when highly correlated internal inputs carry the same fault influence as the monitored target. An exogenous-variable virtual sensor is therefore constructed using ambient temperature and wind speed, enabling a model to learn normal drivetrain thermal behavior from inputs external to component health. Across three gearbox- and generator-bearing fault cases from turbines of different manufacturers, the method provides warnings up to 93 days before maintenance and no false alarms during separately assessed healthy periods. The thermal-image research develops a non-contact diagnostic framework for electrical equipment. Modified multiscale two-dimensional color distribution entropy is introduced as a compact feature set extracted directly from pseudocolor thermograms before machine learning classification. In the evaluated induction-motor and power-transformer experiments, diagnostic accuracy exceeds 95\%, and the method performs better under the tested noise and limited-sample conditions than the compared grayscale entropy formulations.Within the evaluated datasets and experimental conditions, the vibration studies demonstrate early degradation assessment and system-level fault detection; the SCADA study provides earlier warnings for the documented drivetrain bearing cases; and the thermal-image study improves fault classification for the evaluated electrical equipment. Together, these results provide proof of principle for earlier and more informative condition assessment while identifying the fleet-level and field validation required before routine integration into wind turbine maintenance decisions.
  

DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING

• LAGE JULIÀ, ARTAI: Process engineering development strategies for the enhancement of PHB production by cyanobacteria.
  
  Author: LAGE JULIÀ, ARTAI
  Programme: DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 12/10/2026
  Reading date: 18/11/2026
  Reading time: 10:30
  Reading place: Place: ETSECCPBUPC, Campus NordBuilding C2. Classroom: 212C/Jordi Girona, 1-308034 Barcelona
  Thesis director: GARCIA SERRANO, JOAN | GONZALEZ FLO, EVA
  Thesis abstract: Conventional petroleum-based plastics cause severe, lasting environmental harm. Polyhydroxybutyrate (PHB) is a promising fully biodegradable, biobased alternative, as cyanobacteria can synthesize it photoautotrophically from sunlight and CO2, bypassing the costly feedstocks that make bioplastic production economically uncompetitive. Yet several bottlenecks prevent cyanobacterial PHB reaching industrial scale. This thesis addresses them via an integrated strategy: strain selection and microbiome assembly, high-throughput methodology development and parameter optimization, and engineering a decoupled continuous production architecture.Five wild-type cyanobacterial strains were isolated from natural aquatic environments via single-cell isolation, yielding stable populations with markedly divergent PHB accumulation despite high genetic similarity within species. Two Synechocystis sp. and one Leptolyngbya sp. isolate emerged as the top producers, while Synechococcus sp. and a second Leptolyngbya sp. isolate showed negligible accumulation. Secondary effluent was detrimental to accumulation, as residual nutrients interfered with induction, but remained viable for biomass growth.The two best strains (Synechocystis sp. AP, Leptolyngbya sp. R) were evaluated as monocultures, while an artificial microbiome combining Synechocystis sp. AP with the low-producing Synechococcus sp. AP tested community-level synergies. Co-cultivation enhanced PHB performance in both species beyond monoculture levels, and the microbiome was more robust under non-sterile conditions, sustaining stable, contamination-free operation across consecutive cycles. This microbiome showed functional redundancy: under divergent conditions (low phosphorus with uncontrolled pH above 10, versus nutrient-replete conditions with strict pH control at ~8.25), relative population abundances shifted considerably, yet overall PHB potential remained intact. Differences in PHB content were attributable primarily to operational parameters, not population composition: strict pH control and sufficient nutrients during growth enabled up to 36.3% dcw, versus only 17% when pH was uncontrolled.To enable rapid screening, a fluorometric platform based on Nile Blue staining was developed and validated, enabling 124 conditions to be evaluated without the demands of chromatographic quantification. Nitrogen depletion was confirmed as the primary, continuous induction trigger, while phosphorus acted as a threshold switch. Strict pH control (~8.25), dark anoxic conditions, and a 600 mg/L acetate dose were identified as optimal, and validated at photobioreactor scale, confirming PHB synthesis directly from acetate without a glycogen pre-accumulation step.Building on this microbiome, expanded with Leptolyngbya sp. R into a three-strain community, a novel two-stage reactor decoupling photoautotrophic biomass growth from dark, anoxic PHB accumulation was designed and validated for 125 days under non-sterile conditions. Eliminating lags inherent to sequential single-reactor systems, this delivered ~23 mgPHB/L/d volumetric productivity, over fourfold higher than the best single-reactor configurations, with PHB up to 26% dcw. These results show continuous biomass availability, not maximal intracellular PHB content, is the decisive driver of volumetric productivity.Overall, this thesis highlights the value of environmental prospection and strain screening, since its microbiomes were assembled entirely from environmentally isolated strains. It demonstrates the need for strict control of culture conditions, as operational parameters, not population composition, governed PHB outcomes, and underscores the role of reactor configuration in translating biology into industrial productivity gains. Secondary effluent supporting biomass growth offers initial evidence that wastewater is a viable PHB feedstock, highlighting the potential of integrating wastewater treatment with biopolymer production.
  

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

• GUO, TIAN: Reducing the uncertainty on subsurface heterogeneity from microseismicity and geodetic data
  
  Author: GUO, TIAN
  Programme: DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 01/10/2026
  Reading date: 24/11/2026
  Reading time: 15:00
  Reading place: ETSECCPB.UPC, Campus NordBuilding C1. Classroom: 002C/Jordi Girona, 1-308034 Barcelona
  Thesis director: VILARRASA RIAÑO, VÍCTOR | WU, HAIQING
  Thesis abstract: Ensuring geological CO₂ storage (GCS) at scale requires more than just the availability of pore space. Thermal, hydraulic, mechanical, and chemical interactions during and after CO₂ injection pose challenges due to limited access to the subsurface. Reducing subsurface uncertainty is one of the most critical challenges for the safe deployment of GCS. This thesis aims to reduce this uncertainty by linking ground deformation and induced microseismicity with data-driven inversion, stress analysis, and numerical hydromechanical modeling. Specifically, this thesis evaluates (1) how ground deformation can be predicted and used to infer subsurface and fault properties, (2) how microseismic focal mechanisms can constrain the stress state and fault reactivation, and (3) how coupled simulators can support the long-term interpretation of the hydromechanical responses of Opalinus Clay to the injection of CO₂-rich brine.First, we develop a multi-stage, data-driven workflow to predict ground deformation caused by fluid injection into fault-intersected reservoirs. Synthetic poroelastic solutions are used for training and verified against CODE_BRIGHT simulations. Deep neural networks outperform linear regression and tree-ensemble-based models. Pressure change, shear modulus, and fault geometry are dominant controls on surface displacement, enabling rapid assessment of subsurface conditions. Secondly, we propose a probabilistic inversion framework based on conditional invertible neural networks (cINNs) to estimate subsurface parameters from geodetic data and quantify the non-uniqueness of the characterization. Synthetic tests demonstrate that the reservoir width is well-constrained and the throw-to-thickness ratio is partially constrained, whereas the fault dip is only weakly identifiable due to its subtle surface expression. Application of this framework to the Illinois Basin-Decatur Project (IBDP) reveals an equivalent reservoir width that increases over time, consistent with the lateral migration of the pressurized region.We also constrain the stress state and fault stability at the IBDP by integrating microseismic focal mechanisms with borehole data, vertical stress estimates, and instantaneous shut-in pressure (ISIP) measurements. Slip-tendency analysis of 26 focal mechanisms suggests a maximum horizontal stress (SHmax) magnitude of approximately 93 MPa, oriented at ~110°. Fault reactivation thresholds prove to be highly sensitive to ISIP, SHmax magnitude, and the fault friction coefficient.Finally, we present hydromechanical benchmark simulations based on the CO₂LPIE experiment at the Mont Terri Underground Rock Laboratory in Switzerland, comparing CODE_BRIGHT and OpenGeoSys in axisymmetric, anisotropic, and stratified configurations. Both codes reproduce consistent patterns of pressure diffusion and dissolved CO₂ transport, whereas the geomechanical fields (deformation, displacement, and stress) exhibit strong sensitivity to bedding anisotropy and constitutive models, highlighting the need for careful calibration against field data.Overall, this thesis demonstrates that GCS safety benefits from addressing monitoring, modeling, and uncertainty quantification in an integrated manner. Ground deformation provides spatial information on reservoir pressurization, microseismicity constrains stresses and fault reactivation, and machine learning models enable rapid prediction and probabilistic inversion for subsurface characterization. The proposed framework improves the characterization of subsurface structures and properties while supporting an adaptive assessment of GCS safety.
  

DOCTORAL DEGREE IN MARINE SCIENCES

• HERRERA GUTIERREZ, ANGEL RAUL: Valoración de la geodiversidad del corredor Puertecitos-San Luis Gonzaga, Baja California, México: bases para la gestión geopatrimonial y su potencial como geoparque
  
  Author: HERRERA GUTIERREZ, ANGEL RAUL
  Programme: DOCTORAL DEGREE IN MARINE SCIENCES
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 16/10/2026
  Reading date: 03/12/2026
  Reading time: 16:00
  Reading place: Place: ETSECCPBUPC, Campus NordBuilding D2. Classroom: 216C/Jordi Girona, 1-308034 Barcelona
  Thesis director: MÖSSO ARANDA, OCTAVIO CESAR
  Thesis abstract: Geodiversity encompasses the abiotic components of the landscape, the processes that generate them, and their relationship with the biotic, cultural, and historical elements of a territory. Its study constitutes a fundamental basis for the identification, assessment, and management of geological heritage, as well as for the development of geoconservation strategies, environmental education, and geotourism. In Mexico, studies on geodiversity and geoheritage are still limited; however, the recognition of the Comarca Minera Geopark in Hidalgo and the Mixteca Alta Geopark in Oaxaca has fostered interest in evaluating new territories with geoheritage potential.This research analyzes the Puertecitos–San Luis Gonzaga corridor, located on the eastern coast of Baja California, covering an area of approximately 2,472 km². The region forms part of the western margin of the Gulf of California and is characterized by remarkable geological, geomorphological, tectonic, volcanic, sedimentary, paleontological, historical, and archaeological diversity. Arid conditions, sparse vegetation cover, and excellent bedrock exposure make this area a natural laboratory for the interpretation of geological processes and for the development of low-impact geotourism activities.The study integrated a literature review, cartographic analysis, geographic information systems, semi-structured interviews, and field campaigns. As a result, 74 Geosites (Sites of Geological Interest) were identified and assessed, considering their field of interest, representativeness, state of conservation, accessibility, and potential use. In addition, a normalized Geodiversity Index (IGDn) was developed, comprising five sub-indices: geomorphological, geological, paleontological, cultural, and geosites. For the spatial model, the 74 geosites located within the defined study area were incorporated.The IGDn results show that 51% of the area has a medium geodiversity value, 28% a low value, and 21% a high value. The highest-value areas are mainly concentrated in coastal sectors, where geomorphological, geological, sedimentary, cultural features, and field-recorded sites coincide. Among the most relevant sectors are Puertecitos, San Luis Gonzaga, and Punta Willard.At Punta Willard and the Papá Fernández tourist camp, 13 features of geological, geomorphological, historical, and archaeological interest were identified, including a tombolo, dune fields, a volcanic structure, cliffs, a rocky outcrop, shell middens, a lithic workshop, stone circles, a well, and a mission storage facility. The concentration of these features within a small area confirms the site’s potential as a pilot area for interpretation activities, environmental education, geotourism, and integrated management of natural and cultural heritage.The results allow concluding that the Puertecitos–San Luis Gonzaga corridor has a solid geoscientific and territorial basis to initiate a geoheritage development process. However, its potential progression toward a geopark candidature should be understood as a gradual process, conditioned by the need to strengthen research, demonstrate international geological significance, consolidate governance mechanisms, involve local communities, and address limitations related to infrastructure, water, waste, safety, and basic services. In this context, the main contribution of this thesis is to provide a technical, spatial, and methodological diagnosis that serves as a foundation for decision-making regarding the conservation, management, and potential geoheritage development of the territory.
  
• ORIHUELA GARCÍA, Mª ANDREA: Controls on Particulate Organic Carbon Budgets in the North Atlantic Mesopelagic Zone: Process-Based Modelling, Observations, and Model Uncertainty
  
  Author: ORIHUELA GARCÍA, Mª ANDREA
  Programme: DOCTORAL DEGREE IN MARINE SCIENCES
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 26/10/2026
  Reading date: 21/01/2027
  Reading time: 10:00
  Reading place: Place: ETSECCPB UPC, Campus Nord Building C1. Classroom: 002 C/Jordi Girona, 1-3 08034 Barcelona
  Thesis director: GALÍ TÀPIAS, MARTÍ | RUPRICH ROBERT, YOHAN
  Thesis abstract: This thesis investigates the mechanisms controlling particulate organic carbon (POC) budgets in the ocean, with particular focus on the North Atlantic and the mesopelagic zone. The biological carbon pump transfers organic carbon from the surface ocean to depth, where its residence time is determined by the balance between vertical export, biological transformations and, ultimately, remineralisation and horizontal transport. Despite the critical role of these processes in long-term carbon storage and, hence, in the regulation of global climate, significant uncertainties remain in both observations and their model representation.To address these questions, the thesis combines process-based modelling with a broad set of observational datasets, including satellite products, BGC-Argo floats, gliders, shipboard measurements, and sediment traps. The core modelling framework is the NEMO–PISCES coupled model, employed to diagnose epi- and mesopelagic POC budgets, quantify the relative contribution of different export pathways, and evaluate how detrital size classes, remineralisation rates, and zooplankton-mediated processes shape carbon flux attenuation with depth. Sensitivity simulations explore the influence of key parameters and structural choices, including sinking speed, remineralisation rates, and zooplankton flux feeding. Comparisons with the MEDUSA model and one-dimensional experiments at the Porcupine Abyssal Plain offer a complementary perspective on model uncertainty. In addition, an alternative NEMO–PISCES configuration, forced with phytoplankton-derived surface carbon, is used as a novel approach to assess model uncertainty arising from biases in the representation of upper ocean ecosystem dynamics.The results demonstrate that mesopelagic carbon budgets in PISCES are strongly controlled by the interplay between export composition, particle reactivity, and biological processing within the twilight zone. Small detritus plays a central role in sustaining mesopelagic POC stocks, while zooplankton-mediated transformations and temperature-dependent degradation regulate flux attenuation with depth. The relative importance of each process varies regionally across PISCES: gravitational sinking and microbial remineralisation decline in absolute magnitude yet become progressively more dominant at lower latitudes. The thesis further demonstrates that improvements in surface phytoplankton biomass do not propagate linearly to depth, highlighting the buffering role of the epi- and mesopelagic food webs. Furthermore, case studies reveal that convective and seasonal export events can substantially alter the supply of carbon to depth, and are not consistently captured by standard model parameterisations.Taken together, this thesis provides a mechanistic framework for analysing ocean interior carbon budgets and for identifying structural biases in biogeochemical models. By combining process-based diagnostics with a diverse set of observations, it advances the understanding of carbon export efficiency and remineralisation in the North Atlantic, offering guidance for improving future projections of the ocean carbon cycle and its response to anthropogenic perturbation.
  

DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING

• FOOLADIMAHANI, SAGHAR: Assessment of fracture and fatigue behavior of cemented carbides by using small-scale artificial flaws
  
  Author: FOOLADIMAHANI, SAGHAR
  Programme: DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING
  Department: Department of Materials Science and Engineering (CEM)
  Mode: Article-based thesis
  Deposit date: 21/09/2026
  Reading date: 13/11/2026
  Reading time: 11:00
  Reading place: ESCOLA D'ENGINYERIA BARCELONA ESTC/Eduard Maristany, 16 (08019 Barcelona)EDIFICI A planta 0, SALA POLIVALENTmeet.google.com/swu-kiha-hwq
  Thesis director: LLANES PITARCH, LUIS MIGUEL
  Thesis abstract: This PhD thesis investigates the fracture and fatigue behavior of WC-Co cemented carbides through a deterministic damage-tolerance approach based on controlled artificial small-scale flaws. These materials, commonly referred to as hardmetals, are widely used in demanding engineering applications due to their combination of hardness, strength, and toughness. However, their structural reliability is strongly affected by microstructural heterogeneities and service-induced defects, which act as critical failure origins under monotonic and cyclic loading. Conventional assessment approaches rely mainly on stochastic natural flaws or long through-thickness cracks, thereby limiting reproducibility and predictive capability. This work addresses these challenges by developing and validating an experimental framework to systematically assess damage tolerance using well-defined artificial flaws.The research was conducted on four fine-grained WC-Co grades with different cobalt contents to isolate the influence of the metallic binder. Three complementary strategies were employed. Conical indentation reproduced blunt contact damage dominated by irreversible deformation and, at higher loads, radial cracking. Sharp Vickers indentation introduced surface fissures suitable for fatigue crack growth studies. Nanosecond laser ablation was optimized to generate reproducible microdimples and notch-like surface defects with controlled geometry. Their effects on residual strength, fatigue performance, crack growth behavior, and fracture toughness were assessed through mechanical testing, microscopy, fractography, crack-path inspection, and fracture-mechanics analysis.The results show that controlled artificial flaws provide a robust basis for evaluating damage tolerance in hardmetals. Under monotonic loading, residual strength is governed by flaw severity and intrinsic fracture toughness. For imprint-type or dimple-like defects without pre-existing cracks, strength reduction is mainly associated with geometric stress concentration. Once cracking occurs, fracture toughness becomes dominant, causing abrupt strength degradation in low-binder grades and more stable crack evolution in tougher materials. Under cyclic loading, the metallic binder plays a dual role. In crack-free damaged conditions, higher binder content increases fatigue sensitivity due to localized cyclic plasticity, whereas in pre-cracked conditions it improves resistance to subcritical crack propagation through crack-tip shielding and energy dissipation.A specific part of the thesis addresses laser ablation for fracture toughness determination. Laser-induced microdimples combined with quantitative fractography produced toughness values in close agreement with established fracture-mechanics methods. Laser-generated shallow notches also acted as controlled crack-initiation geometries for conventional toughness evaluation, providing a practical alternative to traditional pre-cracking procedures. These results demonstrate that laser-induced flaws are effective both for damage-tolerance studies and for reliable fracture-mechanics characterization.Overall, this thesis establishes a rigorous framework for investigating fracture and fatigue in WC-Co cemented carbides through controlled small-scale flaw engineering. The methodology distinguishes the effects of microstructure, damage condition, and flaw characteristics; clarifies the role of binder content under different loading conditions; and validates indentation- and laser-induced flaws for assessing strength, fatigue behavior, crack propagation, and fracture toughness. These findings provide a practical basis for reliability assessment and the design of hardmetals with improved resistance to service-like damage.
  

DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING

• BERNÈ ARTIEDA, LUIS JAVIER: Energy Auditing of In-Service Hydraulic Systems: Methodology and Loss Diagnosis for Side-Loader Refuse Collection Vehicles
  
  Author: BERNÈ ARTIEDA, LUIS JAVIER
  Programme: DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING
  Department: Department of Mechanical Engineering (EM)
  Mode: Normal
  Deposit date: 01/10/2026
  Reading date: 18/11/2026
  Reading time: 12:00
  Reading place: Sala de Conferències TR5, ESEIAAT
  Thesis director: RAUSH ALVIACH, GUSTAVO ADOLFO | CODINA MACIA, ESTEBAN
  Thesis abstract: Legislation on fuel use and emissions has shifted the focus of hydraulic design in mobile machinery towards efficiency. The most widespread architecture is still load-sensing with a variable-displacement pump, which supplies only the demanded flow at a pressure slightly above that of the load. Even so, it retains two main sources of inefficiency: flow is regulated by throttling and, when several movements are fed simultaneously from a single pump, the most heavily loaded section sets the supply pressure and the rest throttle the difference. In addition, loads that can accelerate the motion require overcenter valves, which introduce further losses into the system.This thesis studies the loading mechanism of a side-loader refuse collection vehicle, a multi-actuator system with overrunning loads and a load-sensing architecture. With hundreds of collections a day, losses that are small in each operation can become significant at fleet scale.In this context, the losses arise from the interaction between the multi-actuator load-sensing architecture and the overcenter valves, and no single component accounts for them on its own. The literature mainly offers global figures and rarely separates these mechanisms in experimental balances on real machines. Moreover, the overcenter–load-sensing coupling is little studied, and refuse collection vehicles are among the least analysed within mobile machinery.The aim is to address this gap through a complete energy decomposition that identifies experimentally the mechanisms, components and cycle phases where the energy is dissipated, distinguishing the reducible part from the unavoidable one. The approach is deliberately applied: the measurements are taken on an in-service vehicle, which conditions the instrumentation. Pressure is measured with transducers, but the flow of each actuator cannot be obtained directly, among other reasons because of space constraints, and is reconstructed from the position and geometry of the actuators, with a single flowmeter at the pump outlet for the system balance closure. This differentiation amplifies sensor noise and becomes a significant source of uncertainty. To resolve this, a synthetic reference of known kinematics allows the filter to be selected objectively and spurious motion to be removed. From the processed signals, a quasi-static power balance is built that quantifies the losses by mechanism and is validated through its closure. The method is applied to different load conditions.The main conclusion is that the efficiency deficit has a structural origin: it lies in the system architecture and in the interaction between its components and actuators. Simultaneity is the dominant loss mechanism, and replacing components with more efficient ones recovers only a limited fraction of the dissipated energy. The analysis also shows that a view focused solely on components can lead to wrong conclusions. Despite using the same valve, the tilt and lift circuits behave in opposite ways: in tilt, the dissipation is high but mostly reducible at component level; in lift, the direct dissipation is lower, but its real cost is architectural, since it fixes the supply pressure at its maximum value.Beyond the results obtained, the thesis establishes a diagnostic framework and develops a reproducible methodology, independent of the machine analysed and applicable to other machines in the mobile and off-road machinery sector. This framework makes it possible to identify and quantify the origin of the energy losses and to assess improvement alternatives before undertaking their redesign.
  

DOCTORAL DEGREE IN NETWORK ENGINEERING

• FERNÁNDEZ LANGA, SERGI: Future Immersive and Interactive Media Experiences: Multiparty Holoportation in Social Virtual Reality (VR) Scenarios
  
  Author: FERNÁNDEZ LANGA, SERGI
  Programme: DOCTORAL DEGREE IN NETWORK ENGINEERING
  Department: Department of Network Engineering (ENTEL)
  Mode: Normal
  Deposit date: 29/09/2026
  Reading date: 23/11/2026
  Reading time: 15:00
  Reading place: aula VGB107 de l'edifici Aulari (VGB) del Campus de Vilanova
  Thesis director: RINCON RIVERA, DAVID | MONTAGUD CLIMENT, MARIO
  Thesis abstract: The promise of Virtual Reality (VR) is that of a medium which makes you feel like being in a place where you are not and freely explore it, potentially immersed in a plot, as well as interact with any element in it. Beyond that, Social VR aims to provide togetherness, impacting users’ sense of presence, also through embodiment, and give the possibility to bring multiple people into the same story or context, into the VEs, so the experience is not only immersive but shared among a group of humans. This thesis aims primarily to design, develop, and evaluate new technological contributions for the application and scalability of multiparty holoportation in Social VR scenarios, with the general objective of improving the quality of shared immersive experiences. In other words, this work aims at evolving and improving state-of-the-art Social VR solutions, by enabling the integration of multiple remote users into shared VEs, embodied and represented as 3D volumetric holograms, captured and reconstructed in real-time. The thesis revolves around four main hypothesis: the first hypothesis is that VEs resulting from a strategic hybridization of synthetic 3D and 2D video-based elements can provide satisfactory levels of immersion, interactions and plausibility at low costs; the second hypothesis is that low-cost full-body volumetric capture setups can enable live multiuser holoportation in Social VR, while providing satisfactory levels of interaction, presence, embodiment and togetherness; the third hypothesis is that single camera volumetric capture setups can result in pleasant group-shared experiences (e.g., virtual meetings) in scenarios where the tele-ported users are not meant to move significantly; and the fourth hypothesis is that the bottlenecks that will arise when increasing the number of tele-ported volumetric users into a single VE can be mitigated by applying network-based media processing optimizations on the server side.The results from this thesis have resulted in three main research contributions: a full-fledged multiparty VR holoportation platform; a set of VR environments through which the developed technical components can be demonstrated and evaluated; and a server-side component to optimize multiuser holoportation or communications based on volumetric video.
  
• GONZALEZ DIAZ, NESTOR: Improving the Scalability and Availability of Indoor Location Solutions based on Wi-Fi RTT (IEEE 802.11mc)
  
  Author: GONZALEZ DIAZ, NESTOR
  Programme: DOCTORAL DEGREE IN NETWORK ENGINEERING
  Department: Department of Network Engineering (ENTEL)
  Mode: Normal
  Deposit date: 24/09/2026
  Reading date: 02/12/2026
  Reading time: 11:00
  Reading place: Sala de actos (001-Pg) de la EETAC (Castelldefels)
  Thesis director: ZOLA, ENRICA VALERIA | MARTÍN ESCALONA, ISRAEL
  Thesis abstract: Indoor positioning is a key enabler of location-based services, yet no technology has emerged as the indoor counterpart of Global Navigation Satellite Systems (GNSS). Wi-Fi Round-Trip Time (RTT), standardized in IEEE 802.11mc through the Fine Timing Measurement (FTM) protocol, is a promising candidate because it reuses the Wi-Fi infrastructure already deployed in most buildings and measures distances with sub-meter error on commodity devices.However, the real-world adoption of Wi-Fi RTT is hindered by three interrelated challenges. Accuracy degrades under Non-Line-of-Sight (NLoS) and multipath conditions, which introduce systematic biases in the ranging estimates. Scalability is capped by the peer-to-peer nature of the FTM protocol, which requires an exchange of location-dedicated frames between the user and the access point (AP). This procedure limits each AP to about thirty users updating their position once per second. Finally, the machine-learning models required to exploit the signal often exceed the memory and the latency budget of resource-constrained devices. This dissertation argues that accuracy, scalability, and computational complexity must be optimized jointly, meeting the memory, latency, and availability requirements of Internet of Things (IoT) deployments.The system proposed in this dissertation is based on fingerprinting and combines the active RTT observable with passive observables that add no network overhead, namely the Received Signal Strength Indicator (RSSI) and the standard deviation of the RTT burst. The system is organized into a clustering stage, a feature selection stage, and a multiclass classification stage. All experiments use measurement campaigns collected with commodity smartphones in two real scenarios: an open auditorium, with line of sight (Line-of-Sight, LoS) between users and APs, covered by up to seven 802.11mc-compatible APs, and a floor of corridors and offices, without line of sight (NLoS), served by three APs.The dissertation first characterizes the accuracy achievable with Wi-Fi RTT fingerprinting. Two RTT requests attain very good results in both scenarios: an accuracy above 97% in LoS when one RSSI is added, and a root-mean-square error (RMSE) between 50 and 65 cm in NLoS when three RSSI are added. It then proposes a clustering and feature selection architecture that distributes the FTM traffic overhead among the APs, increasing the potential number of concurrent users without degrading accuracy. Third, a low-complexity proximity model, which replaces the iterative clustering and the tree-based feature selection with a single sort of the observed RSSI, matches the accuracy of more complex algorithms while reducing the clustering memory to less than half and storing no persistent model; in addition, the RMSE stays below 30 cm in LoS and near half a meter in NLoS. Finally, it reveals that the RSSI from passive scanning and the RSSI from the FTM frames are systematically biased and locally uncorrelated observables that carry complementary positional information. The proposed system, evaluated with both sources, reaches an RMSE of 0.66 m at the highest user count and of 0.30 m with the three RTT requests in NLoS.Taken together, these results show that accuracy, scalability, and low computational complexity can be achieved jointly on commodity hardware, providing an integrated and reproducible framework for scalable and available indoor localization based on Wi-Fi RTT.
  
• MIRANDA PASCUAL, ÀLEX: Toward a Theory of Preprocessing and Composition in Differential Privacy
  
  Author: MIRANDA PASCUAL, ÀLEX
  Programme: DOCTORAL DEGREE IN NETWORK ENGINEERING
  Department: Department of Network Engineering (ENTEL)
  Mode: Change of supervisor
  Deposit date: 24/09/2026
  Reading date: 28/01/2027
  Reading time: 11:00
  Reading place: Karlsruhe
  Thesis director: PARRA ARNAU, JAVIER | STRUFE, THORSTEN
  Thesis abstract: Personal data processing is essential to many applications from health to finance and urban development, but data may contain sensitive information, raising serious privacy concerns. Privacy-enhancing technologies therefore seek to preserve utility while limiting disclosure, creating an inherent privacy–utility tradeoff. Differential privacy (DP) has become the standard privacy notion due to its strong protection guarantees and rigorous definition. Its composition properties allow complex DP mechanisms from simpler ones, with post- and preprocessing techniques extending DP to more tasks. However, DP can struggle to achieve an acceptable privacy–utility tradeoff for complex tasks. Moreover, the central DP model requires trust in a single curator, whereas local approaches remove this assumption at a substantial utility cost. Thus, this thesis studies how the main building blocks of DP—composition and preprocessing—affect the privacy–utility tradeoff and how this tradeoff adapts to the trust requirements. Understanding these tools helps researchers develop better DP mechanisms.We study the privacy-preserving publication of human trajectory databases under DP and syntactic notions. Our systematization shows that DP suffers under the increased complexity and presence of outliers. Because these limitations are not exclusive to trajectories, we focus the remainder of this thesis in general contexts.The negative impact of outliers motivates our study on record omission in DP as preprocessing. We first analyze sampling that amplifies privacy by uniformly selecting a subset of records of the database. However, our evaluation shows that core DP mechanisms with sampling consistently yield a worse tradeoff than the mechanism without sampling over all tested scenarios. We then introduce suppression in DP and derive theorems characterizing the privacy guarantees under arbitrary suppression, showing that it can either amplify or degrade privacy depending on the setting. However, targeted outlier suppression also does not improve the privacy–utility tradeoff and is less effective than sampling. These results show that preprocessing should be evaluated based on its overall privacy–utility impact, rather than privacy amplification alone.We next study composition and its interaction with preprocessing. Existing sequential and parallel composition theorems may overestimate privacy loss when mechanisms access overlapping data, while parallel composition does not apply to some DP variants, including bounded DP. We therefore introduce a general composition theorem that accounts for deterministic preprocessing under arbitrary domains and neighborhood definitions. By modeling data access as preprocessing, our theorems provide tighter privacy estimates and enable intermediate composition settings between sequential and parallel composition.Finally, we investigate limiting data access to reduce trust requirements. We introduce the k-curators model, positioned between the central and local models, where disjoint portions of the data are randomly distributed among k non-colluding curators. To analyze this model, we introduce probabilistic parallel composition, which provides tighter privacy bounds than standard parallel composition. Our evaluation of the privacy–utility–trust tradeoff shows that the k-curators model can limit the data accessed by each entity with minimal utility cost at fixed privacy levels.Overall, this thesis advances the understanding of DP by characterizing the effects of composition, preprocessing, and their interaction. It provides new theoretical results, more accurate privacy guarantees, and evaluates their impact on the privacy–utility(–trust) tradeoff, offering new insights and tools for designing future DP mechanisms.
  

DOCTORAL DEGREE IN PHOTONICS

• MEZZADRELLI, ALESSIA: Transparent glass surfaces with functional metallic nanostructures for display applications
  
  Author: MEZZADRELLI, ALESSIA
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 21/10/2026
  Reading date: 02/12/2026
  Reading time: 15:30
  Reading place: ICFO Auditorium
  Thesis director: PRUNERI, VALERIO | MAZUMDER, PRANTIK
  Thesis abstract: Display technologies are ubiquitous in everyday life, generally consist of multiple functional components arranged in a stack, where each layer must satisfy specific optical, electrical, mechanical and surface requirements. In this context, nanofabrication offers the possibility to modify material properties and introduce additional functionalities without compromising the primary operation of the device. Glass represents an ideal platform because of its optical transparency, mechanical robustness, chemical stability, and compatibility with thin-film deposition and surface processing. Among the possible material approaches, ultra-thin metal films (UTMFs) are particularly attractive, as their response can be strongly tuned through composition, thickness, morphology, and nanoscale structuring. This thesis investigates the engineering of UTMFs and derived metallic nanostructures on glass for multifunctional display-related applications, with particular emphasis on transparent antimicrobial surfaces and transparent conductors.The first part addresses high-touch surfaces, such as public and shared touchscreens, which can contribute to microbial transmission. Ultra-thin copper films were thermally dewetted to form electrically isolated nanostructures, preserving compatibility with capacitive touch sensing while providing strong antimicrobial activity. Optimization of the thermal treatment enabled control of particle morphology and plasmonic response. Combined with a silica protective layer and an Easy-To-Clean coating, the resulting surfaces achieved bacterial reduction above 99.9%, visible transmission of approximately 70-80%, electrical insulation, and resistance to mechanical abrasion.To further improve the optical performance of antimicrobial surface, Cu-Zn mixed films were investigated as a material-engineering strategy to increase color neutrality while maintaining the antimicrobial functionality of Cu. Co-sputtered Cu-Zn films followed by thermal dewetting produced transparent and electrically insulating nanostructured surfaces with transmission above 80% in the visible range, improved color neutrality, and bacterial reduction exceeding 99.9%. The results demonstrate how compositional engineering can tune the optical response without compromising antimicrobial efficacy.The final part of the thesis explores UTMFs as transparent conductors. Several metals were compared in terms of transmission, sheet resistance, film growth, and percolation behavior, identifying CuZn as a promising material because of its balance between conductivity, transparency, color neutrality, film formation, and time stability. Its optoelectronic properties were further investigated as a function of thickness, thermal annealing, and aging. Compositional analysis indicated a redistribution of Zn toward the surface, associated with the formation of a protective Zn-rich oxidized region and a comparatively Cu-rich metallic layer underneath. This evolution is consistent with the experimentally observed increase in optical transmission and decrease in sheet resistance. Finally, a lithography-free colloidal patterning approach was explored to introduce openings into CuZn UTMF and further tune the trade-off between optical transmission and electrical conductivity.Overall, this work demonstrates how composition, thickness, and nanoscale morphology can be used to engineer ultra-thin metallic systems toward markedly different functionalities. Optical modelling and experimental nanofabrication were combined throughout the work, with particular attention to fabrication routes compatible with scalable industrial processing. The results highlight the potential of UTMFs as a versatile platform for transparent glass surfaces combining optical quality with antimicrobial activity, electrical insulation, or electrical conduction for next-generation display and optoelectronic technologies.
  
• PLASCENCIA OROZCO, SUSANA: Quantum memories based on rare-earth doped solids: from spatial multiplexing to new materials
  
  Author: PLASCENCIA OROZCO, SUSANA
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 12/10/2026
  Reading date: 16/11/2026
  Reading time: 10:00
  Reading place: ICFO Auditorium
  Thesis director: DE RIEDMATTEN, HUGUES
  Thesis abstract: Quantum repeaters play a fundamental role in the development of long-distance quantum network. In most architectures, their functional core is constituted by quantum memories. Although many systems have been investigated as potential quantum memory, no single platform yet satisfies all the requirements simultaneously. Solid-state systems, particularly cryogenically cooled rare-earth doped crystals represent one of the most promising routes toward efficient, long-lived and massively multiplexed quantum memories, with great prospects for integration. This thesis addresses two main objectives. The first is to extend the spatial multimode capacity of a rare-earth-doped quantum memory using a praseodymium-doped yttrium orthosilicate Pr^{3+}:Y_2SiO_5 to increase the entanglement generation rate required for realistic quantum repeater application. The second objective, carried out in collaboration with Corning, investigates the spectroscopic properties of erbium-doped-chalcogenides to assess their suitability as fiber-integrated quantum memory operating at the telecom wavelength. To achieve spatial multiplexing in the Pr^{3+}:Y$_2SiO_5 crystal, we implement a quantum memory array (QMA) using a pair of acousto-optic deflectors, creating ten individually controllable spin-wave memory cell featuring on-demand read-out. By combing the spatial multiplexing of the array with the intrinsic temporal multimodality of the atomic frequency comb (AFC) protocol, we store and retrieve on-demand up to 250 modes using weak coherent pulses at the single-photon level, both surpassing the current state-of-the-art for solid-state quantum memory. The high signal-to-noise ratio and low cross-talks enable the storage of heralded single-photons. To do so, we use a cavity enhanced spontaneous parametric down conversion source to generate a pair of photons, with the signal photon stored in the QMA and the idler at telecommunication wavelength. We demonstrate the violation of the Cauchy-Schwarz inequality by at least 4.8 standard deviations in all the memory cells, demonstrating light-matter quantum correlations between the QMA and the telecom photon. We further demonstrate the potential use of our system as a random access quantum memory (RAQM) by storing path and time-bin qubits encoded with weak coherent states in the quantum memory array, achieving average fidelities of 95 ± 2% and 91 ± 2%, respectively. We further load sequentially a time-bin qubit in two different memory cells, simultaneously store both qubits, and perform a collective read-out. The high fidelities together with independent control pair represent a significant step toward a solid-state RAQM for quantum repeaters and photonic quantum processors. For the fiber-compatible quantum memory, we study three Er-doped chalcogenide glasses with a different glass network rigidities quantified by the coordination mean number (MCN). We measure their optical coherence time (T_2) through two-pulse photon echo (TPE) technique and find that the sample with MCN < 2.4 exhibits the shortest T_2, while the most rigid sample (MNC = 2.9) suffers from internal stress that also limits the coherence time. The intermediate rigidity sample (MNC = 2.69) shows a T_2 close to 1 μs (corresponding to a homegeneous linewidth ≈ 370 kHz) at 2 K and 0.2 T, which is among the longest coherence times reported for Er-doped glasses under practical cryogenic conditions, reachable with a standard close-cycle cryostat. However, the spectral hole burning measurements reveal hole widths around 50 MHz for two best TPE performing samples, severely restricting the achievable comb finesse and therefore constraining the AFC efficiency in these materials.
  
• PONS LANAU, ROGER: Single-Molecule Spatiotemporal Dynamics of Protein Export from the Endoplasmic Reticulum
  
  Author: PONS LANAU, ROGER
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 06/10/2026
  Reading date: 12/11/2026
  Reading time: 15:00
  Reading place: ICFO Auditorium
  Thesis director: GARCÍA PARAJO, MARÍA | CAMPELO AUBARELL, FELIX
  Thesis abstract: The secretory pathway is a crucial process for cellular homeostasis, responsible for the synthesis, processing, and trafficking of approximately a third of all proteins to their final destinations. Newly synthesized secretory proteins enter the endoplasmic reticulum (ER) and, after proper folding, are sorted into and exported from specific ER subdomains named ER exit sites (ERES). As the first trafficking step, ER protein export plays a crucial role in ensuring the correct flow of proteins to downstream compartments, and defects result in a variety of pathological conditions. Unraveling its organization in space and time is essential to understanding its mechanisms. Despite the origins of this research field dating to the late 1960s, it was not until the widespread adoption of fluorescence microscopy techniques in the past three decades that rapid progress was made in how we conceptualize ER protein export in living cells. Yet, up until now, researchers have mostly relied on population-averaged measurements, which provide limited information on the molecular heterogeneity inherent in biology. Insights into molecular dynamics, transient interactions, short-lived states, or nanoscale distribution of secretory pathway proteins in living cells have largely remained veiled. Developing a complete view requires characterizing the process at the single-molecule level.In this thesis, we develop and apply a quantitative framework based on single-molecule fluorescence microscopy to dissect the dynamic organization of the early secretory pathway at the molecular level. By leveraging recent technological advances in fluorescent dyes, functional assays, gene editing, and machine learning tools, our approach enables the detection, monitoring, and analysis of individual cargo protein molecules as they are exported from ERES with high spatial precision (~20-30 nm) and temporal resolution (~10 ms). Our characterization provides novel insights into the orchestration of the early secretory pathway, allowing us to revisit conflicting ideas in the field. Overall, this thesis provides a generalizable methodology and an updated, more accurate view of a fundamental intracellular trafficking process.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• CHARI, SHREYA KRISHNAMA: Resource orchestration at the MEC for heterogeneous networks and services using Reinforcement learning enhanced by Generative AI
  
  Author: CHARI, SHREYA KRISHNAMA
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 01/10/2026
  Reading date: 03/12/2026
  Reading time: 09:30
  Reading place: Aula de Graus C4-002, UPC Campus Nord, Barcelona
  Thesis director: VERIKOUKIS, CHRISTOS
  Thesis abstract: The evolution of 5G and beyond communication has enabled rapid expansion of network capabilities, services and applications. The requirements of modern communication and computing infrastructures need to accommodate heterogeneous resource requests while maintaining service quality, resource distribution and energy efficiency. Shifting the compute-intensive applications to centralized cloud architectures has alleviated the problems related to network resource procurement. However, the geographical distance of these cloud data centers introduce communication delays, network congestion and privacy issues due to the physical distance from the source of the generated data. In light of these circumstances, edge computing emerged as a viable option to bring computation, storage, and intelligence closer to end users and other data sources. Multi-access Edge Computing (MEC) infrastructure makes it accessible for the communication networks to provide computing capabilities at or near the network edge. With resources available at the network edge, low-latency communication, context-aware applications and distributed learning is enabled. Despite the advantages, several significant issues such as task offloading, efficient resource allocation, service placement, and workload scheduling remain open for improvement. Most of the use cases expected in future wireless networks will present multi-objective and multi-constrained non-trivial optimization problems which require intelligent solutions. Moreover, the large-scale data generated at the user end with millions of connected devices and rapidly changing network environment requires a flexible solution that can adapt to the variability. This dissertation investigates smart solutions for MEC resource management while simultaneously accounting for changing network environment using artificial intelligence. The main aim is to develop algorithms that can address open challenges of orchestration and allocation of edge resources to dynamic network workloads. Further, the algorithms developed should also optimize the overall network performance by bringing down latency, energy and resource allocation gaps. Reinforcement learning (RL) is selected as the primary optimization method as it has the capability to interact and learn from custom environments that can mold to varying workloads and perform multi-objective optimization. Further, the RL feedback loop continuously provides learning signals to refine the decision-making strategy to improve resource management. On the whole, the contributions from this thesis encourage using RL methods for MEC resource orchestration and is further enhanced by inclusion of GenAI components. The findings establish that intelligent techniques can be used for dynamic coordination and allocation of heterogeneous edge resources for diverse services. The research work in this thesis, provides proof-of-concept resource management framework which is scalable, energy-efficient and adaptable to evolving requirements of future wireless networks.
  

DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE

• ALAZETTA, PASCALE ISABELLE: Quartiers anciens en déshérence - pratiques et expérimentations du neutre
  
  Author: ALAZETTA, PASCALE ISABELLE
  Programme: DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE
  Department: Department of History and Theory of Architecture and Communication Techniques (THATC)
  Mode: Change of supervisor
  Deposit date: 29/09/2026
  Reading date: 20/11/2026
  Reading time: 09:00
  Reading place: Sala de Actos del Institut d’Urbanisme et de Géographie Alpine. Grenoble.
  Thesis director: ROSSELLO NICOLAU, MARÍA ISABEL | SANTAMARIA, FREDERIC SEBASTIEN | SCARNATO, ALESSANDRO
  Thesis abstract: Along the French Mediterranean coast, the central districts of medium-sized cities have, in recent years, seen their populations change, the mix of social classes disappear, the businesses close. They have sometimes become places of social marginalization where unsanitary conditions take hold. Attempts are being tried to reverse this trend. These attempts are often adequate in the central, vibrant parts of cities, where the refurbishment of public spaces and facilities, combined with the restoration of building facades and the renovation of historic buildings, revitalizes these historic centers and generates a certain commercial, cultural, and social vitality. The challenges lie in older working-class neighborhoods, where services and businesses rarely establish themselves, where public spaces receive little improvement, and where modest housing is difficult to adapt to contemporary living standards due to high building densities with cramped units, lack of light, ventilation, private outdoor space, accessibility, greenery, parking spaces, etc. Yet they consist of urban forms and historic buildings that possess significant spatial, aesthetic, and social qualities, as well as adaptability to topography, climate, and construction. Often, the solutions proposed trivialize the space, as interventions are strictly functional and overlook sensitive aspects of urban composition and building design. Contemporary architecture can also be controversial in these areas due to heritage constraints. And when the revitalization of these neighborhoods is successful, it often leads to their gentrification. It is therefore necessary to consider how these complexes might be adapted to contemporary lifestyles and ways of living, in an era where environmental concerns must necessarily guide solutions. The question of public tools and policies aimed at run-down historic neighborhoods—their content, implementation, complementarity, interconnection, and the issue of governance—must also be examined.This project proposes to analyze some of these situations and seek solutions that would allow for intervention and find a comfort that meet the expectations of contemporary life for a diverse population, while countering the mechanisms of gentrification. This work will be based on the specific case of four districts in medium-sized French cities with a rich urban and architectural heritage—Béziers, Narbonne, and Perpignan—which have been increasingly confronted in recent years with a marked decline in the quality of life in parts of their historic centers. Despite growing signs of poverty—which exceed national averages—these cities, unlike other struggling cities and due to their location along the Mediterranean coast, are experiencing population growth, rising real estate prices, and strong tourist appeal.In contrast, the city of Girona, in Spanish Catalonia, which has been the subject since the 1980s of an ambitious renovation plan that has led to an undeniable revitalization of its historic center, appears to be facing problems linked to gentrification and a proliferation of tourist accommodations that have altered the lives of its residents. In response to overly procedural specifications, programs, and spatial solutions, a work on neutral practices in urban planning and architecture may be explored. The neutral, as Roland Barthes understands it, can be understood here as the desire to leave spaces open, resistant to theoretical interpretations and subjective intentions that predetermine meaning and freeze the possibilities of inhabiting.
  

DOCTORAL DEGREE IN URBAN AND ARCHITECTURAL MANAGEMENT AND VALUATION

• ZHANG, XU: Urban expansion and its environmental consequences: Green space, thermal environment, and climate responses from a remote sensing perspective
  
  Author: ZHANG, XU
  Programme: DOCTORAL DEGREE IN URBAN AND ARCHITECTURAL MANAGEMENT AND VALUATION
  Department: Department of Architectural Technology (TA)
  Mode: Normal
  Deposit date: 30/07/2026
  Reading date: 18/11/2026
  Reading time: 10:30
  Reading place: ETSAB (Esc.Téc.Sup.Arquit.Bcn)-Pl. Baja-Aula A-BetaAv. Diagonal, 649 Enlace a videoconferencia: https://meet.google.com/hpj-hwmu-cciConnexión 10:00h
  Thesis director: ROCA CLADERA, JOSE NICASIO | ARELLANO RAMOS, BLANCA ESMARAGDA
  Thesis abstract: Against the backdrop of global urbanization and intensifying climate risks, urban expansion has become a key process reshaping spatial organization and environmental systems. Urban growth not only alters land-use structures and urban boundaries, but also affects thermal environments, ecological quality, and biodiversity through the reconfiguration of urban spatial structure. Existing studies often focus on single-scale analyses or isolated processes and lack systematic integration across scales, regions, and environmental mechanisms.This dissertation develops an integrated framework linking urban expansion, spatial structure, and environmental responses. Using multi-source remote sensing data, including nighttime light imagery, spectral indices, land surface temperature, vegetation indices, and biodiversity observations, the study establishes methods for urban expansion detection and urban boundary delineation. Landscape ecological metrics are applied to quantify urban morphology, connectivity, and fragmentation, while thermal and ecological responses are analyzed through heatwave indicators, surface energy partitioning, and ecological quality assessments.The study areas include rapidly urbanizing regions in China and mature metropolitan areas in Europe, enabling comparative analysis under different climatic and developmental conditions. The results show that the environmental impacts of urban expansion are determined not only by the proportion of built-up land, but mainly by spatial organization and landscape configuration. Spatial fragmentation alters energy distribution, weakens ecological connectivity, and reshapes cooling diffusion pathways, leading to differentiated thermal and ecological responses.During rapid urbanization stages, increasing impervious surfaces and declining green space continuity amplify thermal risks and reduce ecological resilience. In more mature metropolitan regions, environmental responses become more localized and heterogeneous, although they remain strongly conditioned by spatial structure. Even when total green space changes little, fragmentation can progressively degrade ecological network stability and biodiversity over time.Cross-regional comparisons reveal that expansion intensity, climatic conditions, and urbanization stages significantly influence the pace and spatial expression of environmental responses, while the fundamental structure-mediated mechanisms remain consistent across contexts.This dissertation proposes that the environmental consequences of urban expansion are essentially systemic effects driven by spatial structural reorganization, with spatial structure acting as the key mediating variable linking expansion and environmental responses. By integrating urban expansion detection, landscape structure analysis, thermal environment assessment, and ecological evaluation into a unified framework, this study advances urban expansion research from area-based analysis toward structural mechanism interpretation.The dissertation establishes a transferable multi-scale analytical framework integrating multi-source remote sensing data across national, metropolitan, municipal, and street scales. The findings highlight the importance of blue-green networks in maintaining thermal regulation and ecological stability, emphasizing that sustainable urban development depends not only on limiting expansion scale, but also on optimizing spatial structure and strengthening ecological functions.
  

DOCTORAL DEGREE IN URBANISM

• CATRÓN LAZO, CAROLINA: El azul en el gris: Intervenciones multiescalares en el espacio azul urbano. El caso de las lagunas urbanas de Concepción (Chile).
  
  Author: CATRÓN LAZO, CAROLINA
  Programme: DOCTORAL DEGREE IN URBANISM
  Department: Department of Urbanism, Territory and Landscape (DUTP)
  Mode: Change of supervisor
  Deposit date: 23/10/2026
  Reading date: 24/11/2026
  Reading time: 11:00
  Reading place: Universidad del Bio Bío - Chile
  Thesis director: GALINDO GONZALEZ, JULIAN | BAERISWYL RADA, SERGIO LEONARDO
  Thesis abstract: This thesis analyses the interventions that influence the relationship between people and urban blue spaces, considering accessibility and visibility as conditions that can expand or restrict opportunities for interaction. The research is conducted through a comparative study of five urban lagoons in Concepción, Chile: Lo Custodio, Lo Galindo, Lo Méndez, Redonda, and Tres Pascualas.The qualitative methodology adopts a multiscalar perspective encompassing the urban, neighbourhood, and specific-site scales. At the urban scale, the relationship between the lagoons and the street network is examined through Space Syntax analysis, complemented by a historical reconstruction. At the neighbourhood scale, potential centralities are identified, together with the barriers and connections that condition the continuity of routes between these centralities and the lagoon access points. At the specific-site scale, the architectural and landscape interventions within the parks are analysed according to their configuration as points, lines, planes, and volumes, as well as their proximity to the water. Visibility is examined through georeferenced photographic records from Instagram.The results show that accessibility is configured through a multiscalar sequence: mobility axes and transfer points at the urban scale; neighbourhood mobility axes and articulation points at the neighbourhood scale; and point, line, plane, and volume interventions at the specific-site scale. Urban interventions connect, neighbourhood interventions articulate, and specific-site interventions distribute. Continuity between these interventions favours progressive movement towards the water, whereas discontinuities restrict it. Visibility has a more localised expression and is primarily associated with interventions that enable positions close to and oriented towards the body of water. Overall, the thesis proposes understanding interventions as a system of relationships across scales, whose articulation conditions opportunities for accessibility and visibility in urban blue spaces.
  

DOCTORAL DEGREE IN APPLIED MATHEMATICS

• KULKARNI, SHARDOOL: Mathematical and Computational Modeling of Single Cell Electrotaxis
  
  Author: KULKARNI, SHARDOOL
  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 APPLIED MATHEMATICS
  Department: School of Mathematics and Statistics (FME)
  Mode: Normal
  Deposit date: 06/11/2026
  Deposit END date: 19/11/2026
  Thesis director: SAEZ VIÑAS, PABLO
  Thesis abstract: Understanding cell migration is an essential question in biology. It is pivotal to tissue regeneration, organ development, and even to diseases such as cancer. Cells migrate in response to external cues in vivo and in vitro. Growing evidence suggests that electric fields represent a precise and programmable method to control cell migration. However, the underlying mechanism behind sensing of the electric field, how that leads to polarity, and, eventually, to migration is poorly understood.Using mathematical and computational modelling, this work aims to understand single-cell electrotaxis and its underlying mechanisms, specifically how and why cells migrate in a particular direction under an electric field. Electric fields can physically bring about asymmetry on the cell membrane, redistribution of cell membrane proteins and in ion fluxes, which in turn can produce intracellular gradients of ions such as calcium, whose role in cell migration is well established.First, using a one-dimensional finite element model that incorporated signaling models and an active gel, we show that EGFR polarizes cathodally, and the cathodal accumulation of downstream signals, like PI3K, leads to the polarization of the motile machinery and cathodal migration. A proteome-wide screen showed that an approximately equal number of proteins would polarize anodally and cathodally. The opposed polarization of membrane receptors triggers downstream competing signaling pathways, and, depending on where and at what strength receptors polarize, the prevailing signal will make cells migrate anodally or cathodally. This activation strength is cell-type dependent, and the downstream signaling competition between different activation pathways may explain opposite responses in electrotaxis.Then, a two-dimensional KNP-EMI model shows that the cell cytoplasm is completely shielded from the electric field; therefore, the experimentally observed polarity must originate at the membrane. We then model membrane effects such as ion channel redistribution, EGFR-driven IP3 production, and store-operated calcium entry. The combined effect of these produces a noticeable gradient in intracellular calcium. The cathodal calcium polarity reverses with the field, increases linearly with field amplitude, and is suppressed by chloride channel inhibition. The model also predicts that a partial block of the SERCA pump increases total calcium in the cytosol but reduces the calcium asymmetry.Together, these models show that electrotaxis is an electro-chemo-mechanical phenomenon in which the field is sensed at the membrane and relayed through redistribution of membrane proteins, ion transport, and signaling to the motile machinery of the cell.
  

DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY

• MOOSAVI, SEYEDEH MARYAM: Guidelines for the cultural and socio-spatial rehabilitation of vulnerable residential buildings in traditional Iranian architecture: application to the historic Sang-e Siah district in Shiraz, Iran
  
  Author: MOOSAVI, SEYEDEH MARYAM
  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: Normal
  Deposit date: 11/11/2026
  Deposit END date: 24/11/2026
  Thesis director: CORNADÓ BARDÓN, CÒSSIMA
  Thesis abstract: This dissertation investigates the rehabilitation of vulnerable traditional residential buildings within the historic urban fabric of Shiraz, with particular emphasis on the Sang-e Siah neighbourhood. The research adopts an integrated socio-spatial perspective that combines cultural interpretation, spatial configuration analysis, visual-perceptual assessment, and heritage rehabilitation. Structured as an article-based dissertation, the thesis synthesises four peer-reviewed publications that progressively build a comprehensive rehabilitation framework.The first publication, The Social Life of Residential Architecture: A Systematic Review on Identifying the Hidden Patterns Within the Spatial Configuration of Historic Houses, systematically reviews international research on historic residential architecture. It identifies the principal theoretical and methodological trends while revealing significant gaps in the integration of socio-cultural values, spatial configuration, and residential heritage rehabilitation, particularly within non-Western contexts.Building upon this foundation, the second publication, Analyzing the Influence of Residents' Sociocultural Reflections on the Spatial Configuration of Historical Persian Residential Architecture, examines how cultural values, including privacy, hospitality, family structure, and social hierarchy, are embedded within the spatial organisation of traditional Persian houses. Through socio-spatial analysis, the study demonstrates that residential architecture functions as a cultural system rather than merely a physical structure.The third publication, The Impact of Window Visual Permeability on Socio-Spatial Accessibility in Iranian Cultural Heritage Houses, investigates the role of visual permeability, focusing on traditional Orosi windows. The findings demonstrate how visual regulation contributes to privacy, socio-spatial accessibility, environmental performance, and the preservation of cultural identity within Iranian heritage houses.Finally, the fourth publication, Translation of Social, Spatial, and Cultural Dynamics of Persian Cultural Heritage Houses: A Prescriptive Approach for Contemporary Housing Architecture in Iran, translates the knowledge generated by the previous studies into practical design principles for contemporary housing. It proposes culturally informed and measurable architectural guidelines that integrate socio-cultural values, spatial hierarchy, and visual-perceptual principles into contemporary residential design.By integrating these four complementary studies, the dissertation develops a culturally grounded and socio-spatially informed rehabilitation framework for vulnerable residential buildings in traditional Iranian architecture, with application to the historic Sang-e Siah district in Shiraz. The research contributes to heritage conservation and sustainable urban rehabilitation by demonstrating how cultural identity, spatial organisation, visual regulation, and evidence-based design strategies can be integrated into a coherent rehabilitation model.Keywords: traditional Iranian architecture; residential heritage; rehabilitation; socio-spatial analysis; spatial configuration; visual permeability; Orosi windows; cultural identity; Sang-e Siah; Shiraz.
  

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

• RUIZ CELADA, ORIOL: Knowledge Representation and Reasoning for Adaptive Robotic Manipulation
  
  Author: RUIZ CELADA, ORIOL
  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: 05/11/2026
  Deposit END date: 18/11/2026
  Thesis director: ROSELL GRATACOS, JOAN | SUAREZ FEIJOO, RAUL
  Thesis abstract: Service robots operating in unstructured, human-shared environments must integrate perception, task planning, action execution, and monitoring into a coherent system. In practice, these capabilities are often implemented as separate subsystems with distinct data representations, so each one operates with only a partial view of what the system as a whole knows, limiting the ability of the robot to adapt when execution deviates from expectations. This thesis develops the BE-AWARE Framework, a framework that addresses this challenge through Knowledge Representation and Reasoning, the discipline concerned with formally representing knowledge and deriving new facts through inference. Ontologies, formal knowledge bases that encode the entities, properties, and relationships of a domain, serve as a shared semantic foundation that all deliberation functions read from and update continuously. This keeps the system aware of the world state, applicable actions, and execution context, and uses that awareness to adapt behavior at runtime across planning, execution, and monitoring.Four contributions build on this foundation. At the knowledge level, unified access to the knowledge base is provided for all framework functions, with ontological reasoning applied continuously to derive situational, domain, and execution knowledge from asserted facts, enabling the knowledge base to represent more than what sensors alone can observe. For planning, planning problem files are generated automatically from the current reasoned world state, and the planner is re-invoked whenever a deviation from the expected execution state is detected, allowing the robot to recover task progress without abandoning the original goal. For execution, Behavior Trees for each planned action are assembled and adapted using a library of knowledge-driven modifiers that extend or restructure base execution templates based on what the system knows about the current context, so that, for example, handling a fragile object or operating with a different end-effector produces structurally different execution without requiring a separate hand-authored template for each case. Finally, for monitoring, context-sensitive condition checks and recovery strategies are embedded directly into these Behavior Trees, with what to monitor and how to recover determined by situational knowledge evaluated at configuration time rather than fixed in advance.Together, these contributions form an integrated pipeline in which knowledge actively drives awareness and adaptation across planning, execution, and monitoring. Because all functions operate on a shared, continuously reasoned representation of the world, the framework can apply situation-specific behavior not only at planning time but throughout execution. To demonstrate its practical applicability, the framework is evaluated on a shared robotic manipulation scenario used across the work, validating the implementation of each module and evaluating the computational overhead it introduces.
  

DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING

• MARIN LÓPEZ, DANIEL: Gas Sensor-Based Environmental Proxies for Health applications
  
  Author: MARIN LÓPEZ, DANIEL
  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 BIOMEDICAL ENGINEERING
  Department: Department of Automatic Control (ESAII)
  Mode: Normal
  Deposit date: 11/11/2026
  Deposit END date: 24/11/2026
  Thesis director: FONOLLOSA MAGRIÑA, JORDI
  Thesis abstract: Gas sensing systems are increasingly used beyond direct pollutant detection, acting as indicators of often more complex variables. This use is supported by the practical advantages of gas sensors, which are often cheaper, less invasive, and easier to deploy than many alternative monitoring technologies. These characteristics make them suitable for applications in which the variable of interest cannot be measured directly and must instead be inferred from accessible environmental signals. The usefulness of this approach, however, depends not only on sensor accuracy, but also on whether the measured signal remains representative of the higher-level phenomenon it is intended to infer. This thesis examines the effectiveness of environmental variables used as proxies under three different real-world deployment conditions in health and well-being applications that differ in context, scale, and inferential complexity.The first case study addresses home monitoring of an older adult living independently. A gas sensor array was deployed in the home to assess whether changes in indoor air composition could capture domestic activity patterns. The results show that they can detect routine activity and deviations from habitual patterns, although interpretation requires temporal processing and compensation for environmental variability and sensor drift. The second case study focuses on environmental monitoring in occupied educational buildings. Carbon dioxide was evaluated as a proxy for ventilation adequacy, showing that sensor placement and ventilation strategy can introduce spatial discrepancies larger than those explained by sensor specifications alone. In the same monitoring context, thermal comfort was examined as a model-based proxy, showing that simplified input models can remain acceptable when their error stays within the uncertainty of the complete standardized calculation. The third case study addresses asthma patient monitoring. Individual environmental exposure was studied in patients with moderate-to-severe asthma through a six-month multimodal monitoring protocol integrating wearable pollution sensors, fixed-site ambient data, spirometry, physiological wearables, inhaler-use records, and symptom reports. Personal and ambient exposure estimates often diverged, supporting the need for individualized monitoring, but no consistent association was found between pollutant exposure and respiratory outcomes in this exploratory cohort.The thesis shows that analytical accuracy is necessary but not sufficient for valid environmental inference. The dominant source of uncertainty changes with the application: spatial representativeness in shared indoor spaces, model assumptions in thermal comfort estimation, and behavioral and physiological heterogeneity in individualized health monitoring. Overall, gas sensing is best understood as a context-sensitive proxy technology when the inferential target is explicit, deployment conditions are considered part of the methodology, and the limits of interpretation are acknowledged.
  

DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING

• PAPADAKI, ARTEMIS: Contribution to the development of a new quantitative risk analysis methodology considering artificial intelligence methods
  
  Author: PAPADAKI, ARTEMIS
  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 CHEMICAL PROCESS ENGINEERING
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 05/11/2026
  Deposit END date: 18/11/2026
  Thesis director: PLANAS CUCHI, EULALIA | ÁGUEDA COSTAFREDA, ALBA
  Thesis abstract: Catastrophic industrial events have recurred throughout the history of the chemical and petrochemical sectors, indicating the need for continued advancement in the field of process safety, whose primary objective is the prevention and mitigation of industrial accidents. The contribution of artificial intelligence, and more specifically of machine learning, to this domain is currently being actively investigated by the research community, with the aim of enhancing existing methodologies, automating processes and reducing the human intervention required. The present doctoral thesis delves into this topic and examines the development of machine learning models for quantitative risk assessment, specifically focusing on effects and consequences estimation.The first part of the research examines the collection of data derived from integral models and the training of simple and ensemble machine learning models. For the databases generation different modeling software were compared and utilized, i.e. ALOHA, ADAM and PHAST. The scenarios covered a wide range of ambient conditions, different loss of containment cases (leak and catastrophic rupture), and focused on different substances under varying storage conditions. The interpretability of the trained models was analyzed by features importance ranking, and the identification of uncertainties stated the potential sources of error throughout the methodology. Following training, in all the developed models, the predictions were able to successfully reproduce patterns within the training bounds, while exhibiting lower performance for extrapolated data. Emphasizing on emergency response application where information may be limited, the best performing model was integrated into a logic diagram to predict safety distances considering unknown input features.In the second part of the thesis, the development of a neural network model trained on computational fluid dynamics (CFD) simulations is investigated. OpenFOAM-based CFD simulations were validated against experiments for two phase propane tanks exposed to fire. Conjugate heat transfer was considered to model the heat transport from the fire through the tank wall and into the tank content. The governing equations were formulated using the Volume Of Fluid approach, and the evaporation and condensation phenomena were approximated by the Lee model. The developed framework captured effectively the pressure and temperature evolution in the fluid domain. The validated cases served as the foundation for generating additional simulations by varying the diameter, filling degree, flame temperature and engulfment parameters. The database was then utilized to train a graph neural network model. The black-box problem of neural networks was addressed by introducing a physics term in the loss function of the model to regularize the output and avoid non physical predictions in the liquid domain. The trained model was capable of predicting spatial and temporal temperature distributions within seconds, which can be used as a heat map to indicate the state of the tank content.Overall, various approaches for the development of machine learning models were explored, specifically simple, ensemble and neural network models. Non-commercial and open-source computational tools were employed and evaluated in order to promote open science, code accessibility and dissemination of scientific research. The presented methodologies and trained models contribute to the integration of machine learning into risk assessment, underscoring the need for interpretability studies and hybrid frameworks which embed physics principles.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• GONZÁLEZ FUENTES, SEBASTIÁN: Thermo-hydro-mechanical-chemical processes in porous and fractured materials from the aggregate to the continuum scale
  
  Author: GONZÁLEZ FUENTES, SEBASTIÁN
  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 CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Normal
  Deposit date: 04/11/2026
  Deposit END date: 17/11/2026
  Thesis director: VILARRASA RIAÑO, VÍCTOR | DE SIMONE, SILVIA
  Thesis abstract: Achieving a sustainable energy transition requires a detailed knowledge of the behavior of deep geological systems in response to anthropogenic activities. The injection of fluids and/or heat into porous and fractured media activate a series of coupled thermo-hydro-mechanical-chemical (THMC) processes that control the evolution of these subsurface operations and modify the geological media itself. The main objective of this thesis is to improve the understanding of these coupled processes, particularly in the context of deep geological disposal of high-level radioactive nuclear waste and Enhanced Geothermal Systems (EGS).The first part of the thesis focuses on deep geological disposal of radioactive nuclear waste, investigating the long-term integrity of a cementitious engineered barrier in contact with groundwater from the surrounding host rock solving coupled hydro-mechanical-chemical (HMC) processes. Simulation results show that barrier degradation is controlled by the chemical disequilibrium between porewater of the host rock and the cementitious material, leading to porosity changes, especially at the cement-rock interface. Portlandite dissolution governs the propagation of chemical-alteration fronts, while calcium-silicate-hydrate (C-S-H) dissolution results in the largest increase in porosity and permeability, generating the most significant hydraulic and mechanical alterations near the cement-rock interface. The study further demonstrates that chemically-induced porosity and permeability enhancement modify the liquid pressure distribution and effective stresses, with the chemical alteration of the mechanical properties being of secondary importance on the long-term mechanical response of the barrier.The remaining part of the thesis focuses on flow and heat transport in the context of deep geothermal energy. First, we investigate the influence of shear displacement on fluid flow and hydraulic connectivity in rough fractures, analyzing its implications for the development of EGS. Numerical simulations on a natural fracture geometry show that shearing progressively modifies the aperture field, increasing hydraulic heterogeneity and promoting the development of preferential flow channels oriented perpendicular to the shear direction. Permeability enhancement depends not only on aperture increase, but also on the connectivity between these conductive regions. Therefore, the growth direction of preferential flow pathways is mainly controlled by the stress regime, which ultimately determines the most suitable relative location of the injection and production wells to increase their hydraulic connectivity and, consequently, the efficiency of EGS.Subsequently, we analyze the influence of fracture roughness and shear displacement on heat transport in fractured media. Through analytical solutions and numerical simulations performed on synthetic sinusoidal and natural irregular fractures, it is shown that heat transport is controlled by fracture geometry, which defines the interplay of flow channeling with the heat exchange between the fluid circulating in the fractures and the surrounding rock. Increasing shear displacement in rough fractures promotes the development of preferential flow pathways in the direction perpendicular to shear, leading to higher and faster thermal responses and a slower thermal recovery. Furthermore, it is shown that an idealized sinusoidal fracture profile is able to reproduce the thermal behavior observed in natural rough fractures, and that the wavelength-to-amplitude ratio is the most important parameter controlling the observed thermal behavior and allowing an estimate of the shear displacement magnitude
  

DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING

• CARRASCO ASTUDILLO, NICOLÁS: Adoption of the water-energy-food nexus to improve buildings’ climate resilience
  
  Author: CARRASCO ASTUDILLO, NICOLÁS
  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: 29/10/2026
  Deposit END date: 11/11/2026
  Thesis director: GASPAR FÀBREGAS, KÀTIA | CASALS CASANOVA, MIQUEL
  Thesis abstract: Rising temperatures are increasingly affecting people's health, water consumption and food production, with direct consequences for the built environment. As people spend most of their time indoors, buildings are particularly exposed to the impacts of climate change, including hazardous events such as overheating, compromising occupant comfort, increasing the cooling energy demand, and posing direct health risks. To address these challenges, the concept of resilience has been developed, leading to a range of retrofit solutions that have achieved satisfactory results in reducing overheating, lowering emissions and energy demands, and improving the management of critical resources. However, these solutions tend to address challenges in an isolated way, while climate change demands more holistic responses.One concept that could address this challenge is the water-energy-food (WEF) nexus. By encouraging the synergy between these critical resources, populations experiencing water scarcity or food insecurity have been able to manage them more efficiently. Although there have been advances in implementing this concept in the built environment, no systematic method exists for evaluating WEF integration at the building scale from the point of view of resilience.Thus, this doctoral thesis adapts the water-energy-food nexus approach to the context of improving the climate resilience of buildings, assessing the applicability and effectiveness of the concept. Through a review of resilience and WEF metrics, a quantitative framework was developed to evaluate retrofit solutions in terms of both resilience improvement and resource self-sufficiency, using the water-energy-food nexus index for buildings. To test this framework, different rooftop retrofit strategies were applied to reference residential buildings in Catalonia, Spain, modelled in DesignBuilder and simulated under different climatic conditions in the EnergyPlus engine.The main results show that traditional solutions address overheating and energy efficiency effectively, but that resource self-sufficiency is largely absent from their design logic. The exception is the combination of an agrivoltaic system with rainwater collection, which improves resilience indicators while achieving WEF integration consistently across climate zones and future scenarios. This thesis demonstrates that climate resilience and resource self-sufficiency are not conflicting objectives but complementary ones, and provides researchers, policymakers and decision-makers with a method and empirical evidence to support their joint evaluation in building retrofit decisions.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• USECHE ARTEAGA, MARIO ALEJANDRO: Optimal design and operation of energy islands
  
  Author: USECHE ARTEAGA, MARIO ALEJANDRO
  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: 06/11/2026
  Deposit END date: 19/11/2026
  Thesis director: ALBERNAZ LACERDA, VINÍCIUS | CHEAH MAÑÉ, MARC
  Thesis abstract: Energy islands represent a strategic evolution for integrating large-scale offshore wind power, Power-to-X systems, and advanced transmission infrastructure. This thesis develops advanced mathematical optimization frameworks for these systems, addressing the critical challenges of long-term planning, optimal multi-energy dispatch, and uncertainty management.Following a detailed review of the energy island concept, ongoing projects, and technical challenges, comprehensive operational methodologies are established for AC and hybrid AC/DC architectures. For AC islands, multi-objective nonlinear programming models are developed to optimize multi-energy dispatch, balancing energy delivery with voltage regulation and turbine-level dynamics. To overcome the non-convexity of these formulations, the work transitions toward Second-Order Cone Programming (SOCP) relaxations. Building upon this baseline, a Sparse SOCP reformulation is introduced to exploit network topology, reducing computational complexity from quadratic to linear relative to network branches and enabling real-time, large-scale applications.To handle wind power and electricity price volatility, risk-aware methodologies are developed to balance operational security with economic performance. A predictive nonlinear framework with Monte Carlo simulations serves as a benchmark to quantify forecast errors. Building on the SOCP formulations, Robust Optimization (RO) guarantees worst-case feasibility, while Chance-Constrained Programming (CCP) provides a flexible, risk-controlled alternative, enabling tractable uncertainty-aware scheduling.Finally, a two-stage stochastic programming framework using sparse SOCP is proposed for the optimal sizing of VSC-HVDC converter stations, balancing capital investment against operational curtailment. Validated on realistic test systems, including the Princess Elisabeth Energy Island, these scalable, uncertainty-aware methodologies advance the secure operation and strategic planning of future offshore energy hubs.
  

DOCTORAL DEGREE IN ELECTRONIC ENGINEERING

• BASTIAN, GEON GEORGE: MARC PER A LA PRIORITZACIÓ DEL RISC DE SUSCEPTIBILITAT ELECTROMAGNÈTICA EN SISTEMES ELECTRÒNICS ENCASTATS EN L’ETAPA DE DISSENY
  
  Author: BASTIAN, GEON GEORGE
  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: 02/11/2026
  Deposit END date: 13/11/2026
  Thesis director: FERNANDEZ CHIMENO, MIREYA | SILVA MARTINEZ, FERNANDO
  Thesis abstract: The absence of a structured, design-evidence-based framework for electromagnetic susceptibility risk prioritisation in electronic systems represents a critical gap in current pre-compliance engineering practice. Existing approaches, including adaptations of Failure Mode and Effects Analysis, are not natively structured for pre-prototype deployment and offer limited mechanisms for grounding occurrence estimation in verifiable design evidence.This thesis proposes the EM Susceptibility Risk prioritisation methodology, a quantitative framework in which the Occurrence component of electromagnetic susceptibility risk is derived from verifiable design artefacts at PCB layout release stage. The central innovation is the replacement of probabilistic Occurrence scoring with a design-evidence index based on three binary flags: Coupling Path (CP), Entry Attenuation (EA), and Local Resilience (LR); assessed directly from the schematic and layout. A criticality-weighted Risk Priority Number ensures that risk prioritisation reflects both the susceptibility exposure of each functional block and the system-level consequence of its failure.The methodology is developed through two progressive application cases of increasing complexity. The first applies the framework to the BITalino biosignal acquisition board, operating within a representative high-stress ambulance pre-hospital monitoring scenario, serving as a deliberate stepping-stone to demonstrate the methodology's analytical structure on a tractable system before scaling to automotive-grade complexity. The analysis reveals a systemic absence of Entry Attenuation across all block-interference combinations, identifying the Power Conversion block as the highest-risk combination at an adjusted RPN of 896.0 for both Radiated Immunity and Electrostatic Discharge. The second application deploys the methodology on the representative automotive reference design, NXP S32G-VNP-RDB2 assessed within a technically grounded fictional scenario as a rear zonal domain controller in a battery-electric vehicle, producing a complete risk register of 240 block-interference combinations across 60 active component groups and four interference types. Two distinct risk concentrations are identified: Power Backbone and High-Speed Compute, providing actionable guidance for design hardening and compliance test prioritisation.The comparative analysis demonstrates that the proposed methodology reduces subjective Occurrence scoring, enables architectural differentiation of failure mode priority, and provides a reproducible and auditable risk register deployable at the earliest stage of development where design interventions are most cost-effective. The framework is positioned as a practical complement to the regulatory shift toward risk-based electromagnetic compatibility engineering, consistent with the lifecycle-based and risk-informed safety assurance philosophy of ISO 26262. The result is a methodology that an engineer can deploy with a schematic and a layout, before a prototype exists, and walk away with a ranked, auditable list of where to look first; which is precisely when that information is most valuable.Future research directions include the extension of the Local Resilience flag to incorporate resonance geometry screening from ODB++ layout data, the development of an automated multi-agent AI pipeline for large-scale EM-SRA execution, and the formal mapping of electromagnetic interference-induced failure modes to ISO 26262 Automotive Safety Integrity Level classifications, establishing a structured analytical bridge between the electromagnetic compatibility and functional safety engineering disciplines.
  

DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING

• RAJAGANESAN, PRAJEET: On the modelling assumptions for the simulation of pantograph-catenary interaction for rigid catenary systems
  
  Author: RAJAGANESAN, PRAJEET
  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 MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING
  Department: Department of Mechanical Engineering (EM)
  Mode: Normal
  Deposit date: 03/11/2026
  Deposit END date: 16/11/2026
  Thesis director: ARCOS VILLAMARÍN, ROBERT | CLOT RAZQUIN, ARNAU
  Thesis abstract: Rigid catenary systems, also known as overhead conductor rails, are the preferred solution for supplying electrical power to trains in underground railway networks because of their compact geometry and low maintenance requirements. Despite their widespread adoption, their dynamic behaviour has received considerably less research attention than that of conventional flexible catenaries. In particular, the modelling assumptions adopted when simulating pantograph-rigid catenary interaction are rarely examined. Omitting the effects of geometric features such as pre-sag and staggering simplifies the numerical model and reduces the computational effort, but few investigations have been devoted to studying under which conditions this hypothesis can be adopted without compromising the accuracy of the predicted contact. This thesis addresses that question by assessing the influence of pre-sag and staggering, as well as other features as the conductor rail flanges, the effect of multiple pantograph operation, and pantograph model complexity on the simulated dynamic response. The analysis is conducted over a wide range of span lengths and support stiffnesses to assess these effects under different system configurations and draw conclusions as general as possible.The rigid catenary is first studied as a stand-alone structural component. A wave finite element analysis of the catenary, idealised as an infinite periodic structure, shows that neither pre-sag nor flanges significantly alter its dispersion characteristics, whereas span length and support stiffness have a clear influence. In contrast, a moving load analysis of a finite catenary section reveals a noticeable sensitivity to pre-sag. This sensitivity is stronger for long spans, stiff supports, and high speeds. The discrepancy between the two approaches is attributed to three factors that are present in the moving load analysis but absent from the free wave propagation study: the change in load orientation introduced by the deflected geometry; the accumulation of small differences as the wave propagates across successive spans; and wave reflections at the boundaries of the finite section. Staggering has a negligible effect in all the aforementioned cases. For a realistic non-uniform section with shorter spans, the influence of pre-sag becomes negligible. The analysis is then extended to the framework of coupled pantograph-catenary interaction problems. The coupled analysis uses an in-house numerical model with a penalty contact formulation, verified against the reference software PACDIN for both an ideal and a real catenary section. An implicit penalty formulation is shown to be as accurate as and more efficient than an explicit predictor-corrector scheme. With a three-degrees-of-freedom pantograph model, the influence of pre-sag and staggering is similar to the one observed in the moving load analysis. However, it produces differences of up to 40\% when a non-linear pantograph model that includes collector head flexibility and rotation is used. Simulations with multiple pantographs show that contact force fluctuations may also be influenced by the pantograph-catenary-pantograph interaction. All these findings provide guidance for selecting the level of modelling detail that balances numerical accuracy against computational efficiency.
  
• TRAVIESO DISOTUAR, ADRIAN ALBERTO: Enhancing the Surface Integrity and Mechanical Performance of Steels Produced by Laser Powder Bed Fusion through Machining and Vibration-Assisted Ball Burnishing
  
  Author: TRAVIESO DISOTUAR, ADRIAN ALBERTO
  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 MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING
  Department: Department of Mechanical Engineering (EM)
  Mode: Normal
  Deposit date: 29/10/2026
  Deposit END date: 11/11/2026
  Thesis director: TRAVIESO RODRIGUEZ, JOSE ANTONIO | JEREZ MESA, RAMON | VILASECA LLOSADA, MONTSERRAT
  Thesis abstract: This dissertation investigates how machining and vibration-assisted ball burnishing (VABB) can improve the surface integrity of metallic components produced by laser powder bed fusion (LPBF). LPBF surfaces commonly exhibit asperities, valleys, attached particles, and other irregularities that may affect functional performance. While machining removes these features through material removal, VABB modifies the surface through localized plastic deformation. This work evaluates both approaches in Maraging 300 steel and 316L stainless steel.The study combines Taguchi L27 optimization with multiscale surface and subsurface characterization using optical profilometry, SEM, Hurst and fractal analysis, EBSD, nanoindentation, X-ray diffraction, and incremental hole drilling. In addition, axial fatigue tests were performed on an independent experimental series of LPBF Maraging 300 steel specimens to evaluate the influence of surface condition on cyclic behavior. All materials were studied without post-build heat treatment.The results show that VABB effectiveness depends on the initial surface condition. As-built surfaces required greater mechanical action, whereas machined surfaces responded effectively to lower forces. Although machining produced the greatest roughness reduction, direct VABB also substantially improved the LPBF topography without completely removing the surface. Reductions in Sa and Sq did not necessarily correspond to greater spatial persistence, hardness, or compressive residual stresses, confirming that surface integrity requires complementary descriptors.In fatigue, machining produced the smoothest surface but did not yield a proportional and uniform increase in fatigue life. Direct VABB showed a tendency toward longer lives at lower stress amplitudes, together with a strong compressive residual stress field, although substantial scatter was also observed in the high cycle region. Overall, LPBF postprocessing should be evaluated through the combined surface and subsurface integrity state rather than roughness alone.
  

DOCTORAL DEGREE IN PHOTONICS

• HÄNNI, JONATHAN ROMAN LOUIS: Experimental demonstrations of quantum repeater nodes and links with photon pair sources and multimode quantum memories
  
  Author: HÄNNI, JONATHAN ROMAN LOUIS
  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 PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 09/11/2026
  Deposit END date: 20/11/2026
  Thesis director: DE RIEDMATTEN, HUGUES | GRANDI, SAMUELE
  Thesis abstract: Quantum networks aim to distribute quantum states between distant nodes, enabling applications such as quantum key distribution, distributed quantum computing, and quantum sensing. Optical loss in optical fiber, however, is a roadblock to the realization of fiber-based quantum networks at a continental scale. A promising work-around relies on quantum repeaters, where entanglement is generated, stored and distributed between remote locations in a heralded fashion. In this thesis, we focus on a notable approach based on photon-pair sources coupled to multimode quantum memories, forming network compliant quantum nodes. Among various requirements for network operations, we highlight compatibility with the existing fiber network, high system efficiency, long memory storage time and large access to multiplexing. In this thesis, we use photon-pair sources based on cavity-enhanced spontaneous parametric down-conversion coupled to solid-state absorptive quantum memories based on rare-earth-doped solids (specifically, we use Pr:YSO) to perform basic demonstrations of quantum repeater links and nodes. We showcase the viability of this platform with regards to the aforementioned requirements.We start in Chapter 3 by demonstrating heralded entanglement of two spatially separated on-demand spin-wave solid-state quantum memories. We also implement fast conditional phase-control of the heralded entangled state to double the heralding rate up to 510 1/s. Furthermore, we illustrate the linear advantage of temporal multiplexing by implementing an unconditional storage scheme emulating the operation of a metropolitan-distance link. These results are made possible by the state-of-the-art signal-to-noise ratio of the heralded single photon storage as well as the delicate phase stabilization necessary for consistent heralding and entanglement certification.In Chapter 4, a new generation of photon-pair source is designed, based on a periodically-poled potassium titanyl phosphate nonlinear crystal. Two replicas of the new design are assembled, characterized and compared to the older generation based on periodically-poled lithium niobate. We achieve a heralding efficiency above 0.5 with both setups, more than a factor 2 improvement from the previous generation. The heralded single-photon linewidth is measured below MHz level for both replicas. Additionally, the spectral structure of emission, the response to pump power and other figures of merit are measured through time and frequency resolved measurements.We further showcase the extensive capabilities of our quantum node system in Chapter 5 by coupling our photon-pair sources to various high-performance quantum memory demonstrators. Specifically, we firstly demonstrate long-lived heralded single-photon storage in our quantum memory through the use of spin-rephasing techniques, preserving non-classical correlations after a total storage time beyond 10 us. Secondly, we report heralded single-photon storage in a cavity-enhanced high-efficiency memory. We report storage in the excited state at an efficiency up to 0.306(18) and storage as a spin-wave at an efficiency of 0.182(14) whilst preserving non-classical correlations in both cases. Lastly, a final experiment is performed, storing heralded single photons in a quantum memory array featuring 10 independent spatial modes, each featuring 6 temporal modes. We measure non-classical correlations after storage across all 10 spatial modes. We then harness the telecom compatibility given by the photon-pair source to propagate the non-classical correlations over a 39.1 km deployed fiber link in the metropolitan area of Barcelona.The work presented in this thesis marks a sizable step towards more advanced demonstrations of quantum repeater links, and ultimately, a practical and scalable quantum repeater based on photon-pair sources coupled to multimode quantum memories.
  
• RIZZOTTI, DAVIDE: Engineered optical fiber structures for communication and quantum applications
  
  Author: RIZZOTTI, DAVIDE
  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 PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 09/11/2026
  Deposit END date: 20/11/2026
  Thesis director: PRUNERI, VALERIO | SIGNORINI, STEFANO
  Thesis abstract: Loss is one of the main limitations in optical systems. Classical applications are generally relatively tolerant to it: attenuation can often be compensated through amplification or post-processing, at the cost of increased complexity and cost. Quantum applications are fundamentally more sensitive because information is often encoded in single photons and is lost with them. Multi-photon states can be even more vulnerable, making system scalability exponentially sensitive to loss.Current optical systems combine active and passive components. Active devices are generally based on highly nonlinear materials, such as silicon, indium phosphide, or lithium niobate, which are not ideal for low-loss propagation. Light is therefore typically coupled to silica optical fibers, the standard medium for passive transmission and interconnection between devices. Interfacing different material platforms, however, inevitably introduces additional coupling loss. This thesis aims to reduce this contribution by following an alternative approach: using optical fibers themselves as the active material minimizing the need to interface different platforms. The work focuses on two main devices, which eventually could even be combined.The first project explores a novel fused fiber-bundle-like device containing embedded electrodes for active signal modulation. By relying on standard components and post-processing techniques similar to those used for fused fiber bundles, the structure can provide a low-loss interface between standard fibers and complex multi-material cross sections. I fabricated devices with a total insertion loss below 0.5 dB. Separately, I demonstrated light modulation through the DC-Kerr effect with a half-wave voltage below 20 kV. I then analyzed how these results could be combined and further improved toward an ultra-low-loss, electrically controlled fiber modulator.The second project investigates silicon core fibers (SCFs), a type of fiber that consists of a crystalline silicon core surrounded by a pure silica cladding. To the best of my knowledge, I present the first experimental study of their use for quantum applications, specifically as a photon-pair source in the C-band based on intramodal four-wave mixing. A measured intrinsic brightness of 570 kHz/nm/mW^2, a coincidence-to-accidental ratio of 133±2, and a propagation loss of ≲0.3 dB/cm showed that SCFs can support room-temperature quantum sources with performance comparable to, and potentially better than, existing sources based on similar technologies. Coupling to SCFs was identified as the current main practical limitation of this platform, and I therefore proposed an alternative coupling strategy. The strategy is based on an adiabatic transition through fiber tapering between core-modes and cladding-modes, exploiting the fact that the cladding of both SCFs and standard fibers are made of the same material, namely pure silica. Simulations suggest that the coupler loss could ultimately be limited by propagation loss in the SCF section, while preliminary experiments reached a loss of 8.6 dB/coupler.The results obtained during my PhD show that optical fiber-based devices represent a promising platform when minimizing loss is the primary performance objective. I envision quantum applications, specifically communication and memories, and reconfigurable classical networks to be the main fields of interests of ultra-low-loss active devices.
  

DOCTORAL DEGREE IN STRUCTURAL ANALYSIS

• DOLZ RIPOLLÉS, MONTSERRAT: NUMERICAL MODELLING AND SIMULATION OF ADDITIVELY MANUFACTURED COMPOSITE MATERIALS. APPLICATION TO KIRIGAMI STRUCTURES
  
  Author: DOLZ RIPOLLÉS, 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 STRUCTURAL ANALYSIS
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 30/10/2026
  Deposit END date: 12/11/2026
  Thesis director: MARTÍNEZ GARCÍA, JAVIER | TURON PUJOL, FRANCESC
  Thesis abstract: Additive manufacturing (AM) based on fused-filament processes enables lightweight, customized structural components but exhibits strong anisotropy arising from filament orientation, layer stacking, porosity and interfacial bonding. This thesis develops a predictive and experimentally validated numerical framework to model the stiffness and failure of 3D-printed structures, integrating constitutive modelling, parameter identification, multiscale homogenisation and application-driven analysis. First, a comprehensive review of AM anisotropy, structural applications and kirigami-based deployable systems establishes the motivation, research questions and modelling requirements. The core of the work proposes a finite-element formulation that incorporates imported toolpaths, local material frames, orthotropic constitutive models and elastoplastic formulations, and cohesive modelling of interlayer and interfilament interfaces. A systematic calibration protocol is defined using tensile, shear, bending and cyclic tests, enabling accurate identification of elastic, plastic and fracture parameters. The model is validated on coupons and panels, capturing force-displacement behaviour and stiffness evolution with controlled uncertainty.A multiscale module is introduced to connect micro- and mesostructural descriptors—filament architecture, porosity and interfaces—with effective orthotropic properties through representative volume elements subject to periodic conditions. This enables consistent transfer of material parameters to the macroscale and highlights the role of print orientation on stiffness degradation. Finally, the framework is applied to kirigami-based structures relevant to lightweight deployable systems in naval environments. A dedicated experimental programme (manufacturing, quality control, deployment and compression tests) and its corresponding numerical models allow assessing load capacity, hysteresis, buckling modes and degradation mechanisms. From these results, design rules and charts are derived concerning reinforcement width, print orientation, minimum fold radii and optimal infill patterns. The thesis concludes by quantifying predictive accuracy, outlining methodological and experimental contributions, and identifying limitations and avenues for future research such as high-cycle fatigue, environmental effects and extension to advanced polymer–fibre systems.
  
• SALA PASCUAL, ANIOL: Models for Microfluidic Passive Particle Separation Systems
  
  Author: SALA PASCUAL, ANIOL
  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 STRUCTURAL ANALYSIS
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 06/11/2026
  Deposit END date: 19/11/2026
  Thesis director: OÑATE IBAÑEZ DE NAVARRA, EUGENIO | CASAS GONZÁLEZ, GUILLERMO
  Thesis abstract: This thesis develops analytical and numerical tools for predicting particle classification in passive microfluidic devices, focusing on gravity-driven separation in stratified density fields. It examines how velocity-gradient recovery and solute diffusion affect particle transport. Higher-order gradient recovery improves the convergence of fluid acceleration, but its benefits for particle trajectories depend on velocity interpolation, mesh resolution and outcome sensitivity.An exact modal solution of the extended Graetz problem is derived for fully developed flow in circular pipes, retaining axial diffusion and accommodating non-axisymmetric inlet profiles under isothermal or zero-flux wall conditions. Its numerical implementation is verified against finite-element solutions. In the reported fine-mesh benchmarks, the series reduces peak memory use by a factor of approximately 50–65 and evaluates both scalar configurations faster than the finite-element method.The evolving density field is coupled with particle tracking and a flow-weighted measure of stratification loss, termed *blurriness*, to assess how settling and diffusion jointly affect separation. Exploratory simulations extend the methodology to square ducts and serpentine channels. The results provide a basis for evaluating inlet-layer arrangements, residence times and channel geometry, assuming negligible scalar feedback on the flow, constant transport properties and dilute particle suspensions. Experimental validation remains future work.
  

DOCTORAL DEGREE IN SUSTAINABILITY

• SANCHEZ SANTANDER, OLGA LUCIA: Operationalising the Water–Energy–Food–Ecosystems Nexus: A Participatory, AI-Enabled Modelling Framework for Decision Support
  
  Author: SANCHEZ SANTANDER, OLGA LUCIA
  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: 06/11/2026
  Deposit END date: 19/11/2026
  Thesis director: MORATO FARRERAS, JORDI | FONSECA CASAS, PAU
  Thesis abstract: Operationalising the Water–Energy–Food–Ecosystems (WEFE) Nexus requires transparently linking resource interdependencies, context-specific interventions and the evidence used to compare their consequences. This thesis develops and applies a participatory decision-support approach that combines explicit assumptions, formal system representation, process-based simulation and structured intervention assessment. It is structured around four scientific articles submitted to indexed journals, forming a coherent and complementary line of research: the first three focus on the Mediterranean region, while the fourth transfers the developed tool to a Latin American context, the Department of Cauca, Colombia.The first article develops the modelling architecture, linking an assumptions document to the Specification and Description Language (SDL), execution in SDLPS and scenario exploration in NECADA. The second formalises compensatory interventions, distinguishing baseline-relative responses, gaps against targets, mandatory safeguards, interactions among interventions and preference-based evaluation. Their Mediterranean demonstration systems address wastewater treatment and reuse, desalination, local water supply and irrigation. The third examines plastic-mulching scenarios in Moroccan citrus, linking simulated irrigation and pumping requirements with measured harvest data to derive water-productivity and energy-related emission indicators.These studies show that explicit assumptions and decision rules make scenario comparisons traceable, and that functional boundaries, environmental safeguards and indicator weighting influence how alternatives are interpreted and selected. Water-saving scenarios can reduce modelled energy demand, while production outcomes depend on harvest data and energy-source assumptions. Across Articles I–III, the ADoc → SDL → SDLPS → NECADA chain produced traceable comparisons for five Mediterranean systems. In Article I, field data from Bir Ami (Tunisia) showed that subsurface irrigation used 84.6% less water than drip irrigation with 12.8% lower production, so water savings and production had to be assessed together. In Article II, a non-compensable safeguard changed the set of preferable alternatives: at Codorníu, the 50 mg L⁻¹ nitrate threshold excluded four of eight treatment-wetland configurations, including the one ranked first under the environmental-priority profile, whereas ±0.10 weight perturbations at Agios Fokas produced no rank reversal. In Article III, mulching reduced the modelled annual gross irrigation requirement by up to 43.1% and modelled electricity demand by 23.4–37.5%; water productivity, combining simulated irrigation with measured harvest, increased 1.71- to 4.79-fold across varieties, and energy-related emissions fell by 37.5% under grid supply and 50.1% with fully photovoltaic tank filling. Boundaries, safeguards and weights are therefore reported explicitly with every comparison.Article IV extends the approach to cacao and strawberry production in Cauca under synthetic El Niño stress. Using a complete 2025 meteorological record as the reference climate and synthetic S+2 and S+4 perturbations, NECADA simulations show annual gross irrigation requirements rising from 334.87 mm to 553.80 and 796.74 mm for cacao, and from 8.66 mm to 61.64 and 102.41 mm for strawberry. Precision irrigation in strawberry and agroforestry shade management in cacao reduce irrigation demand, whereas rainwater-harvesting tanks and infiltration trenches store rainfall and runoff, increasing the water potentially available to crops without reducing their requirements. The analysis is limited to the Water–Food dimensions of the Nexus. By reconstructing the local context of Cauca’s production systems, the article also broadens the assessment of the approach’s transferability.