DOCTORAL DEGREE IN APPLIED MATHEMATICS

• GONZALEZ HERNANDEZ, LAURA: On families of prime ideals with an unbounded minimal number of generators in a three-dimensional power series ring
  
  Author: GONZALEZ HERNANDEZ, LAURA
  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: 27/01/2026
  Reading date: 27/03/2026
  Reading time: 16:00
  Reading place: Sala d'Actes de l'FME, Edifici U, Campus Sud
  Thesis director: PLANAS VILANOVA, FRANCESC D'ASSIS
  Thesis abstract: This thesis deals with the existence of families of prime ideals in the power series ring k[[x,y,z]] with an unbounded minimal number of generators.We begin by studying in-depth the related results of Moh on the area. We reprove and generalize a result of Moh which gives a lower bound on the minimal number of generators of an ideal in k[[x,y,z]]. In doing so, we demonstrate that the minimal number of generators of Moh’s prime P3 might decrease depending on the characteristic of the field k. This result contradicts a previous statement made by Sally and leaves as an open problem finding families of prime ideals in k[[x,y,z]] with an unbounded minimal number of generators, when the characteristic of k is different from zero. The main result of this thesis is the construction of a new family of prime ideals in k[[x,y,z]] with an unbounded minimal number of generators, explicitly described, up to constant coefficients, which improves all the former results. The construction and analysis of these families rely on the theory of numerical semigroups and the study of binomial matrices.We first study the numerical semigroup S spanned by three consecutive natural numbers, a,a+1,a+2. We define and characterize the set of elements whose factorizations have all the same length, ULF(S), We provide an explicit description of their factorization sets and a natural partition based on the length and the denumerant. Moreover, by using Apéry sets and Betti elements, we are able to extend some of these results to any general numerical semigroup G. These findings link the structural properties of S directly to the defining ideals of the semigroup rings k[t^a,t^b,t^c], providing a bridge between factorization theory and the minimal generating sets of the corresponding prime ideals.In addition to our particular study of the numerical semigroup S, we need to work with binomial matrices. We derive closed formulae for binomial determinants and calculate bases to left nullspaces of some special binomial matrices. Additionally, we provide an alternative proof for the positivity of binomial determinants, originally shown by Gessel and Viennot. Finally, we display our new family of prime ideals with unbounded minimal number of generators in k[[x,y,z]], where k is a field of characteristic zero. These primes are obtained as the kernel of a quasi-monomial algebra homomorphism. Up to constant coefficients, we give a description of their minimal generating polynomial sets. The advantage of our family with respect to some previous work is the explicit description of the minimal generating sets and the simplicity of the exponents of the monomial presentation.
  

DOCTORAL DEGREE IN BIOINFORMATICS

• MANZINI, ENRICO: Deep Learning Strategies for Longitudinal EHRs: Patient Trajectory Modelling, Survival Analysis and Semantic Representations in Chronic Diseases
  
  Author: MANZINI, ENRICO
  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 BIOINFORMATICS
  Department: School of Mathematics and Statistics (FME)
  Mode: Article-based thesis
  Deposit date: 02/02/2026
  Reading date: 25/03/2026
  Reading time: 12:00
  Reading place: Sala de Juntes FMECampus SudEdifici U
  Thesis director: PERERA LLUNA, ALEXANDRE
  Thesis abstract: The growing availability of longitudinal electronic health records (EHRs) offers unprecedented opportunities to advance personalized medicine and improve patient care. Motivated by recent breakthroughs in deep learning (DL) and the transformative impact of large language models and foundation models in other domains, this thesis explores how similar computational approaches can be adapted to the complexities of healthcare data. The work investigates how neural architectures can capture temporal patterns, non-linear interactions, and latent structures within sparse, heterogeneous clinical datasets, enabling the prediction of disease trajectories and clinical outcomes with greater precision. A central focus is on chronic diseases, particularly type 2 diabetes and chronic obstructive pulmonary disease, where patient trajectories vary widely and outcomes depend on dynamic interactions among biomarkers, treatments, and comorbidities. By developing and adapting attention-based and recurrent neural networks, the thesis shows that DL can predict disease evolution, identify patient subgroups with distinct clinical trajectories, and estimate the risk of key clinical events over time. Hence, by learning meaningful representations of patient histories, these models support dynamic, data-driven decision-making that moves beyond static risk scores toward truly personalized care. In doing so, the work shows how the principles underlying generative foundation models and LLMs—such as sequence modelling, attention mechanisms, and contextual embeddings—can be translated into clinical applications, enabling DL models to generate interpretable, actionable insights from complex longitudinal data. Beyond predictive performance, this thesis emphasizes interpretability, usability, and the integration of patient-generated data. Techniques to translate patient-reported symptoms into structured medical ontologies, for example, illustrate how artificial intelligence can bridge communication gaps, enhance data quality, and facilitate real-world implementation. The work also reflects on methodological considerations, highlighting the importance of tailoring architectures to irregular, multidimensional clinical data, leveraging pre-training and defining embedding strategies to improve robustness, generalisation, and reproducibility. Specifically, this thesis is organized around four complementary lines of research, each addressing a different aspect of applying deep learning to healthcare data. The first focuses on unsupervised techniques, clustering longitudinal trajectories in type 2 diabetes and identifying patient subgroups with distinct disease progression patterns and clinical profiles to support personalized management. The second and third lines focus on supervised learning: the second develops a transformer-based model to predict longitudinal outcomes, emphasizing model architecture and the adaptation of attention-based networks to irregular, multidimensional EHR data, while the third is centred on modelling the complex dynamics of clinically relevant outcomes through deep survival analysis. Finally, the fourth line investigates the translation of layperson medical terminology into structured ontologies, enabling patient-reported data to be integrated into standardized clinical vocabularies and facilitating usability and research applications. Taken together, the four lines of research of this thesis demonstrate both methodological innovations and clinically meaningful results, spanning predictive modelling, patient stratification, and the enhancement of healthcare data usability. They represent a step forward in precision medicine and AI-assisted healthcare, showing that thoughtfully designed deep learning frameworks can transform complex, heterogeneous EHR data into interpretable, actionable knowledge.
  

DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING

• PRATS BISBE, ALBA: Nous entorns interactius de realitat virtual immersiva aplicats a la neurorehabilitació de funcions cognitives i sensoriomotores
  
  Author: PRATS BISBE, ALBA
  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: 29/01/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: JANE CAMPOS, RAIMON | OPISSO SALLERAS, ELOY
  Thesis abstract: Recovery following an acquired brain injury (ABI) represents a major challenge with significant implications for health, quality of life, and socioeconomic burden. Advances in medicine and neurorehabilitation —particularly personalized, patient-centred clinical practice— have contributed to improved outcomes by promoting autonomy and participation in society. Technology has become a cornerstone in this continuous improvement, and virtual reality (VR) has emerged as a promising therapeutic tool. VR immersive properties, ergonomic interaction capabilities, ecological validity, and intrinsic advantages of digitalisation can enhance motor learning and cognitive improvement. However, there is still no conclusive evidence regarding VR clinically significant effects and consistent adoption in routine hospital practice.The aim of this thesis is to identify the barriers to VR implementation in neurorehabilitation and to elicit the specific requirements for its integration as an effective support tool. To achieve this goal, a systematic review of current applications was first conducted to identify methodologies and features associated with significant therapeutic outcomes. This analysis revealed considerable heterogeneity across clinical protocols, as well as the hardware and software used, highlighting the lack of standards and quality criteria that hinder result generalization. To address this gap, a new conceptual framework for evaluating VR tools in clinical contexts was developed: the Virtual Reality-tools Quality Assessment Framework (VR-tools QAF), which defines technical, functional, and safety requirements for VR equipment and virtual environments. In parallel, a comprehensive methodology for user-centred design, iterative development, and clinical validation was created, termed the Virtual Reality-tools Design and Development Guide (VR-tools DDG).Through the combined model (VR-tools QAF + DDG), eleven multimodal VR environments were developed to support the rehabilitation of cognitive and sensorimotor functions in individuals who have suffered an ABI. These environments integrate principles of repetitive practice, multisensory feedback, adaptive difficulty, and mechanisms for tailoring the experience to the patient’s profile. Validation was carried out in collaboration with a leading hospital in neurorehabilitation and brain health, where usability and feasibility tests were conducted with healthcare professionals and patients with ABI. Proof-of-concept trials demonstrated good acceptance and ease of use among clinicians (n = 26) from different specialties, as well as good tolerance and absence of adverse effects among the 20 patients. Moreover, a longitudinal VR intervention conducted within an efficacy study confirmed the feasibility and safety of delivering a 9-hour VR-based cognitive rehabilitation protocol with 21 patients with ABI, distributed in 20–30-minute sessions, 2–3 times per week.Overall, this research establishes a comprehensive methodological model for effectively integrating immersive VR into neurorehabilitation hospital settings, combining scientific rigour with technical and clinical feasibility. The results lay a solid foundation for future efficacy studies aimed at developing standardized treatment protocols for patients with ABI.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• CHASCO GOÑI, UXUE: Innovative techniques for the 3D numerical simulation of high mountain torrent flows.
  
  Author: CHASCO GOÑI, UXUE
  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: 23/12/2025
  Reading date: 27/02/2026
  Reading time: 12:00
  Reading place: Sala Zienkiewich (CIMNE) Building C1, UPC - Campus North Gran Capitan S/N 08034 Barcelona
  Thesis director: ROSSI BERNECOLI, RICCARDO | ZORRILLA MARTÍNEZ, RUBÉN
  Thesis abstract: This thesis develops a numerical tool for the analysis of torrential flows in high-mountain area. The formulation is based on an Eulerian two-fluid, Newtonian incompressible approach combined with a level set method for capturing the free surface.One of the main contributions of the thesis is the improvement of the mass-preserving and energy-preserving properties of Eulerian two-fluid formulations. A consistent mass source term is added to adress the intrinsic mass losses of the level-set method, and a three-step splitting strategy is introduced to guarantee the energy-preserving properties of the numerical scheme for the coupled Navier–Stokes and free-surface convection problem.The formulation is also extended to non-Newtonian rheologies, providing the capability to reproduce the more complex flow behaviours exhibited during mass flow events. A method is proposed that adapts standard CFD boundary conditions within a two-fluid framework to hydraulic flows, allowing both supercritical and subcritical regimes to be accurately captured.A black-box tool for generating three-dimensional terrain meshes is also developed, producing geometries derived from real terrain data and enabling its application to mass flow hazard scenarios.The proposed framework is validated through theoretical, experimental, and real-scale cases. Among these cases, the glacier–rock collapse in Chamoli (India, 2021) is especially significant, as it demonstrates the capability of the developed tool to reproduce a large scale torrential event and confirms its suitability for high mountain mass flow hazard analysis.
  

DOCTORAL DEGREE IN EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS

• ZAPATA FRANCO, ANA MARIA: Probabilistic Seismic Risk Assessment Integrating Soil Nonlinearity, Structural Response and Gender Perspectives
  
  Author: ZAPATA FRANCO, ANA MARIA
  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 EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 04/02/2026
  Reading date: 10/03/2026
  Reading time: 11:00
  Reading place: ETSECCPB.UPC, Campus NordBuilding C1. Classroom: 002C/Jordi Girona, 1-308034 Barcelona
  Thesis director: VARGAS ALZATE, YEUDY FELIPE | GONZALEZ DRIGO, JOSE RAMON
  Thesis abstract: In recent years, soil–structure interaction (SSI) has become a key element in the estimation of seismic risk, as the soil beneath a structure acts as a filter that can amplify or attenuate the seismic response depending on its dynamic properties. This may lead to resonance phenomena in structures whose natural periods are close to those of the soil, increasing seismic demand and the probability of damage. In this regard, the growing use of advanced numerical models that explicitly incorporate SSI has significantly improved the understanding of this complex and nonlinear phenomenon.Accurate characterization of the dynamic response of soil profiles is therefore essential for a realistic assessment of seismic risk. The scientific literature emphasizes the importance of considering SSI, particularly the nonlinear behavior of soils, in the analysis of the seismic performance of structures located in areas of moderate to high seismic hazard, as well as critical infrastructure. To model these interactions, different approaches have been developed, ranging from simplified 1D models to three-dimensional finite element models capable of representing complex geometries, spatial variability, and multidirectional coupling.This research aims to deepen the understanding of the dynamic behavior of structures under realistic seismic conditions, with particular emphasis on SSI. The study analyzes seismic wave propagation through four main stages: i) probabilistic characterization of seismic motion at the bedrock level, ii) nonlinear propagation of waves through heterogeneous soil profiles, iii) evaluation of structural response under site-specific ground motions, and iv) incorporation of social vulnerability, especially gender-related inequalities, into probabilistic seismic risk estimation. This multistage approach enables the integration of engineering and social dimensions in a more comprehensive risk assessment.The research is based on two main hypotheses. The first proposes that advanced intensity measures, based on velocity and energy metrics, provide better predictive capability for seismic demand than traditional acceleration-based measures. The second argues that probabilistic modeling of soil properties within SSI frameworks enables more robust damage predictions than deterministic approaches. Finally, the integration of social factors such as income, housing conditions, and population exposure seeks to contribute to the development of more equitable and effective risk mitigation strategies, aimed at safer and more resilient built environments.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• BRAGANTINI, ANDREA: Learning-based State Estimation for Low Voltage Distribution Grids Using Neural Networks
  
  Author: BRAGANTINI, ANDREA
  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: 20/01/2026
  Reading date: 27/02/2026
  Reading time: 14:00
  Reading place: Aula Capella - ETSEIB Enlace meet público: meet.google.com/qba-hxad-kzb
  Thesis director: SUMPER, ANDREAS
  Thesis abstract: This doctoral thesis investigates how learning-based methods, particularly artificial neural networks (ANNs), can provide a practical and cost-effective solution for state estimation in low-voltage (LV) distribution grids, where measurement infrastructure is typically scarce or absent. Traditional state estimation (SE) approaches, such as Weighted Least Squares (WLS), are effective at transmission and, with adaptations, at medium-voltage level, but are economically and technically unfeasible for LV networks. Their radial topology, unbalanced operation, high R/X ratios, and large number of nodes make dense metering and communication systems prohibitive for distribution system operators (DSOs).This work proposes a simulation-driven methodology to train ANN-based state estimators (ANNSEs) capable of monitoring LV grids in near real time using a limited set of synchronized measurements, primarily those available at secondary transformer substations.The research begins by defining a standardized design and evaluation framework for ANNSEs. Monte Carlo–based probabilistic power flow simulations are used to generate synthetic training datasets from minimal grid information. Initially, a single-phase approximation is adopted, and ANN models are trained to map four basic substation measurements (voltage, current, active and reactive power) to nodal voltage magnitudes. A bi-dimensional performance assessment combining mean absolute error (MAE) and R² is introduced. Case studies on rural, village, and suburban networks show MAE values typically below 1 V, with higher robustness in larger grids exhibiting stronger voltage gradients. Input voltage measurement accuracy emerges as the main limiting factor.The methodology is then benchmarked against alternative machine learning models, including linear regression, random forests, gradient-boosted trees, and multilayer perceptrons. While prediction accuracy remains comparable, custom feed-forward neural networks (FFNNs) demonstrate superior scalability and architectural flexibility, supporting their selection as the preferred ANNSE architecture.The core contribution extends the methodology to realistic three-phase, four-wire LV networks. A multi-network FFNN architecture with separate sub-networks for each phase and the neutral conductor is combined with a three-phase probabilistic power flow. Validation using real pilot data confirms accurate prediction of phase-to-ground voltages, including severe voltage drops and neutral voltage rise, with MAE below 0.3 V and down to 0.2 V when an additional measurement device is optimally placed.The final study addresses robustness and deployment challenges. Sensitivity analyses quantify the impact of grid-model inaccuracies, network evolution, and measurement errors. Moderate errors in line parameters, load growth (up to 9%), or PV penetration (up to doubling) only marginally affect performance, postponing retraining. In contrast, incorrect phase allocation and biased or missing voltage measurements significantly degrade accuracy. Local Sensitivity Analysis shows that ANNSE predictions are primarily anchored to voltage inputs, while power and current measurements contribute locally within feeders, yielding physically interpretable sensitivity patterns.Taken together, these studies define a coherent methodology for deploying ANN-based state estimators as a scalable and cost-effective monitoring tool for LV distribution grids. The thesis demonstrates that ANNSEs, trained offline on digital twins with simulation-driven data, can be deployed in practice to detect voltage deviations and fluctuations in near real time using minimal instrumentation, enhancing observability and reliability in currently unmonitored LV networks.
  
• NOLASCO BENITEZ, EDITH: Evaluación de programas de electrificación rural desde un enfoque de sostenibilidad: Análisis del impacto del BID-FERUM II en Ecuador
  
  Author: NOLASCO BENITEZ, EDITH
  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: 20/01/2026
  Reading date: 20/03/2026
  Reading time: 10:00
  Reading place: Aula 28.8 Sala de Conferències de l'ETSEIB
  Thesis director: GOMIS BELLMUNT, ORIOL
  Thesis abstract: Access to energy is a key driver of economic and social development, as it fosters income generation, contributes to poverty eradication, and enhances quality of life. Its significance has been acknowledged through initiatives such as the 2030 Agenda, which prioritises universal access to clean and modern energy. Nevertheless, despite notable progress, millions of people worldwide remain without access to electricity services, predominantly in rural areas of developing countries. Africa is among the most affected regions, while others, such as Latin America, the Caribbean, and East Asia, have made substantial progresses towards universal access. Factors such as the pandemic, inflation, and the global energy crisis have slowed this progress, impacting equity and sustainability in energy access.In response to this scenario, rural electrification has been approached through various technical strategies, including grid extension, stand-alone systems, and mini-grids. However, significant challenges persist regarding the sustainability and effectiveness of implemented programmes. The need for comprehensive evaluations has led to the development of methodological frameworks focused on energy sustainability.This doctoral thesis aims to evaluate a rural electrification programme using a methodology based on a sustainability framework comprising five dimensions: technical, economic, social, environmental and institutional. The evaluation is conducted at the local level, using a case study the Rural and Urban-Marginal Electrification Programme FERUM II, implemented in the province of Esmeraldas, Ecuador. Through this territorial analysis, key aspects for evaluating such programmes are identified, and specific indicators are defined to assess the achievement of objectives within each dimension. The proposed methodology seeks to offer a practical, contextualised, and replicable guide for developing countries interested in conducting rigorous evaluations of rural electrification initiatives.The research is structured in several phases: first, a systematic literature review to contextualise the problem and build the theoretical framework; then, the development of the evaluation methodology, applied to the Ecuadorian case through semi-structured interviews, questionnaires and fieldwork in rural communities. Based on the analysis of locally collected data, two fundamental questions are addressed: What elements should be considered when evaluating rural electrification programmes? and What outcomes emerge from applying the sustainability framework to the FERUM II case?Preliminary results indicate that the programme has led to substantial improvements in access to electricity services and in the quality of life of the beneficiary population in Esmeraldas. This demonstrates that the proposed sustainability framework effectively captures the multidimensional impacts of rural electrification in vulnerable contexts. The economic dimension reveals certain weaknesses, particularly regarding the promotion of productive activities and access to credit. In contrast, the social dimension shows a positive impact, with progress in education, communications, and security. From an environmental perspective, a reduction in the use of fossil fuels is observed due to the incorporation of grid electricity. Regarding the institutional component, although performance is generally acceptable, deficiencies are identified in the relationship between distribution companies and beneficiary communities, particularly in terms of user support and communication.Keywords: Rural electrification, energy sustainability, programme evaluation, energy access, social and economic development, sustainable development, Esmeraldas, Ecuador.
  

DOCTORAL DEGREE IN ELECTRONIC ENGINEERING

• ROSERO POZO, CARLOS ALBERTO: CONTRIBUTION TO THE DESIGN OF INSTRUMENTATION FOR THE SURFACE AND SUBSURFACE OF MARS
  
  Author: ROSERO POZO, CARLOS 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 ELECTRONIC ENGINEERING
  Department: Department of Electronic Engineering (EEL)
  Mode: Normal
  Deposit date: 22/01/2026
  Reading date: 19/03/2026
  Reading time: 11:00
  Reading place: Aula de Teleensenyament, edifici B3
  Thesis director: DOMINGUEZ PUMAR, MANUEL MARIA | JIMENEZ SERRES, VICENTE
  Thesis abstract: Accurate in situ characterization of the atmospheric environment and its interaction with planetary surfaces, as well as the thermophysical properties of those surfaces, is essential for understanding surface–atmosphere processes, supporting the development of climate predictive models, and enabling the design of exploration systems for robotic and human missions. On Mars, these measurements are strongly constrained by low atmospheric pressure, large temperature gradients, while current missions have strict limitations associated to mass, power and autonomy. This thesis addresses these challenges through the analysis, modeling, and validation of instrumentation and methodologies for planetary surface exploration.The main contribution of this work is the adaptation and validation of a wind sensor structure as a spherical thermoprobe for the characterization of regolith thermophysical properties based on the thermal impedance concept. By injecting a controlled periodic thermal excitation and analyzing the temperature response in the frequency domain, the proposed approach enables the extraction of thermal conductivity and thermal diffusivity. A detailed and realistic analytical thermal model is developed, including probe-specific parameters to improve sensor performance, together with the implementation of compensation techniques for structural heat losses, allowing the capture of the most relevant thermal impedance spectra over an extended frequency range. The methodology is experimentally validated through measurements using hollow glass microbeads and the MMS-2 simulant, the latter being representative of realistic Martian conditions, and showing good agreement with reference instruments.In addition, this thesis investigates the thermal behavior of the Martian wind sensor of the MEDA instrument, with emphasis on the supporting structures that interact with the surrounding atmosphere. The one-dimensional analytical thermal model used to describe the sensor response is evaluated through three-dimensional finite element simulations under low-density atmospheric conditions. The applicability of different convective heat transfer correlations is analyzed, showing that rarefaction effects play a key role in slender structures such as bond-wires. The results confirm the validity of the simplified analytical formulation and provide improved insight into heat transfer mechanisms in Martian wind sensing probes.Overall, this work contributes to improving the reliability of in situ measurements and to the development of compact solutions suitable for integration on landers, rovers, and small robotic platforms for future Mars surface missions or other celestial bodies.
  

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

• ALONSO, MATÍAS: Hydro-mechanical modelling of a sealing concept for a deep geological radioactive waste repository
  
  Author: ALONSO, MATÍAS
  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 GEOTECHNICAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 15/12/2025
  Reading date: 16/03/2026
  Reading time: 11:00
  Reading place: ETSECCPB.UPC, Campus NordBuilding C1. Classroom: 002C/Jordi Girona, 1-308034 Barcelona
  Thesis director: VAUNAT, JEAN | OLIVELLA PASTALLE, SEBASTIAN
  Thesis abstract: Deep Geological Disposal (DGD) has emerged as the most viable solution for the final disposal of radioactive waste, offering the potential for the permanent containment and isolation of waste from the biosphere over extended timescales. Several countries have made significant progress in developing Deep Geological Repository (DGR) concepts for the permanent disposal of such waste. The long-term safety of these facilities relies primarily on the host rock—the natural barrier that plays the central role—supplemented by engineered components collectively referred to as the engineered barrier system (EBS). The EBS includes containers, backfills, buffers, and other structures designed to ensure favourable conditions for the long-term isolation of radioactive waste. The design, performance, and safety assessment of a DGR—and particularly of its EBS components—are therefore essential for the sustainable development of nuclear energy, making their study a key research area within geotechnical engineering.In this context, the main objective of this research is to contribute to the understanding and assessment of the long-term performance of a large-diameter sealing concept developed within the framework of the Cigéo project, led by the French National Radioactive Waste Management Agency (Andra). To achieve this objective, a multi-scale and multi-step numerical modelling strategy has been adopted. The approach combines detailed material characterisation with advanced constitutive modelling of the expansive core, backfill materials, and host rock, accounting for features such as inherent anisotropy and double structure. The modelling framework incorporates coupled hydro-mechanical processes, enabling the analysis of key phenomena such as the natural hydration of the sealing core, the development of swelling pressure, the resaturation and recompression of the excavation-damaged zone (EDZ), the global equilibrium of the sealing system, and the potential deconfinement of the sealing core and its associated loss of swelling capacity. The simulations address the complexity of the problem by integrating large-scale three-dimensional geometries, advanced constitutive formulations, and critical geometric details at the decimetre scale. These challenging simulations provide valuable insights into the performance and long-term integrity of the sealing structures, establishing a robust framework and a powerful tool to enhance the understanding of the behaviour of these EBS, contributing to the optimisation of repository design and safety.
  

DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING

• IGLESIAS FERNÁNDEZ, MARC: Fundamentals of Calcium Phosphate Nanotopographies as Antibacterial Surfaces
  
  Author: IGLESIAS FERNÁNDEZ, MARC
  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 MATERIALS SCIENCE AND ENGINEERING
  Department: Department of Materials Science and Engineering (CEM)
  Mode: Normal
  Deposit date: 02/02/2026
  Reading date: 04/03/2026
  Reading time: 10:30
  Reading place: ESCOLA D'ENGINYERIA BARCELONA ESThttps://meet.google.com/hec-qtvx-euaAv.Eduard Maristany, 16Campus Diagonal BesòsEdifici A Planta 1 Aula A A1.02
  Thesis director: ESPAÑOL PONS, MONTSERRAT | GINEBRA MOLINS, MARIA PAU
  Thesis abstract: Bone defects exceeding a critical size require grafts that provide structural support while promoting bone regeneration. However, surgical implantation of these grafts carries a significant risk of infection, which can compromise graft integration and lead to host bone degradation. This challenge is exacerbated by the increasing prevalence of antibiotic resistance, underscoring the need for alternative antimicrobial strategies. Consequently, the development of synthetic bone grafts that combine osteogenic capacity with intrinsic antimicrobial functionality represents a major clinical and scientific priority.This thesis focuses on the development of synthetic calcium phosphate bone grafts featuring bactericidal nanotopographies effective against both Gram-negative and Gram-positive bacteria, and on elucidating the mechanisms underlying their antimicrobial action.Chapter 1 introduces the clinical motivation and scientific background of the study, providing an overview of implant-associated infections and a critical review of bactericidal nanotopographies reported in the literature, with emphasis on their key design parameters.Chapter 2 focuses on the synthesis, physicochemical characterization, and antimicrobial evaluation of two calcium-deficient hydroxyapatite (CDHA) nanotopographies obtained by hydrolysis of α-tricalcium phosphate under biomimetic and hydrothermal conditions. Both surfaces exhibit nanopillar-like architectures but differ in pillar size and interpillar spacing. The hydrothermally synthesized nanotopography, characterized by larger interpillar spacing, demonstrated superior bactericidal activity against the Gram-negative bacterium Pseudomonas aeruginosa. Ionic-exchange experiments showed that the released ionic species were not toxic to planktonic bacteria, indicating that surface nanotopography, rather than ionic release, is the dominant factor driving bacterial mortality.Chapter 3 investigates the interaction between CDHA nanotopographies and the Gram-positive bacterium Bacillus subtilis using synchrotron-based cryo–soft X-ray microscopy. Cryo-SXT revealed membrane rupture, cytosolic leakage, and multivesicular body formation in bacteria adhering to nanopillars. XANES spectromicroscopy identified a bacterial subpopulation with elevated intracellular calcium associated with substrate-derived ion release; however, this did not affect cell viability, consistent with the halotolerant nature of B. subtilis. Quantitative calcium estimation using linear absorption coefficients provided new insights into mechanochemical bacterial responses.Finally, Chapter 4 presents a time-resolved investigation of the bactericidal mechanisms exerted by CDHA nanotopographies against P. aeruginosa, integrating real-time multiplexed kinetic assays with sequential transcriptomic analyses. The kinetic data revealed four distinct phases: an initial adaptation period, metabolic activation without mortality, an abrupt metabolic collapse accompanied by a sharp increase in cell death, and a persistence phase in the surviving population. Transcriptomic profiling supported this progression, revealing early cell envelope stress and oxidative imbalance (2 h), followed by lipid peroxidation, glutathione depletion, iron dysregulation, and programmed cell death associated with mechanical membrane damage (5 h). At 7 h, global repression of metabolism and translation indicated entry into a persistence-like state, while at 24 h the surviving subpopulation showed partial metabolic reactivation and preparation for regrowth. Altogether, this chapter provides the first sequential genetic framework describing how calcium phosphate nanotopographies trigger mechano-induced oxidative damage leading to bacterial death and persistence.
  

DOCTORAL DEGREE IN NATURAL RESOURCES AND THE ENVIRONMENT

• CASTRO CARRASCO, REBECA IGNACIA: Characterization of sulfate-reducing biofilms using an amperometric printed H₂S sensor
  
  Author: CASTRO CARRASCO, REBECA IGNACIA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN NATURAL RESOURCES AND THE ENVIRONMENT
  Department: Department of Mining, Industrial and ICT Engineering (EMIT)
  Mode: Normal
  Deposit date: 22/01/2026
  Reading date: 27/02/2026
  Reading time: 10:00
  Reading place: Sala d'Aces EPSEM
  Thesis director: GABRIEL BUGUÑA, GEMMA | GUIMERÀ VILLALBA, XAVIER
  Committee:
       PRESIDENT: JIMENEZ JORQUERA, CECILIA
       SECRETARI: SOLE SARDANS, M. MONTSERRAT
       VOCAL: MORA GARRIDO, MABEL
  Thesis abstract: A comprehensive understanding of sulfidogenic processes in bioreactors remains incomplete by the limited availability of tools suitable for the sulfate-reducing activity characterization of immobilized biomass. To address this limitation, the present work is based on developing suitable alternatives for sulfate reducing biomass characterization using electrochemical microsensors. In this sense, a flow-cell bioreactor was developed for real-time monitorization using artificially immobilized biomass to substitute the natural immobilization derived from extracellular polymeric compounds. Physical and functional evaluations enabled the identification of a polymer–biomass matrix capable of preserving sulfate-reducing performance while ensuring adequate microbial retention and structural integrity, as well as a range of operational conditions was assessed to generate detailed H₂S production profiles within the flow-cell bioreactor. In parallel, an inkjet-printed H₂S microsensor was fabricated on polyethylene terephthalate substrates using silver and gold inks and modified with Single-walled carbon nanotubes reinforced with Polyvinyl alcohol and Polydiallyldimethylammonium chloride, which improved ink dispersion, adhesion, and mechanical stability. The optimized formulation yielded long-term operational stability, linear responses across different media, and performance comparable to commercial microsensors despite an initial decrease in sensitivity. Furthermore, the study evaluated the operational behavior of artificial sulfate-reducing granules in column and continuous stirred tank reactors, demonstrating high sulfate removal efficiencies at moderate loading rates, superior stability in column configurations, accumulation of volatile fatty acids associated with incomplete glycerol oxidation, and the effectiveness of a bioaugmentation strategy based on acetate-oxidizing sulfate reducing bacteria immobilized in artificial granules. Lastly, the integrated platform was validated for the analysis of H₂S production in immobilized sulfate-reducing biofilms, combining the flow-cell bioreactor with direct ink writing printed microsensors for simultaneous, in situ monitoring of H₂S and pH. Three-dimensional mapping revealed pronounced H₂S gradients driven by mass-transfer limitations and hydrodynamic dispersion, while printed electrodes exhibited linear amperometric responses and stable performance over extended operation, thereby confirming the suitability of the proposed platform for high-resolution, real-time characterization of sulfidogenic biofilms and immobilized sulfate-reducing biomass.
  

DOCTORAL DEGREE IN OPTICAL ENGINEERING

• LARROSA EXPÓSITO, MANEL: Viabilidad de un nuevo diseño de lentes de contacto de gran diámetro para ojos con queratocono. Estudio clínico.
  
  Author: LARROSA EXPÓSITO, MANEL
  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 OPTICAL ENGINEERING
  Department: Department of Optics and Optometry (OO)
  Mode: Normal
  Deposit date: 22/12/2025
  Reading date: 05/03/2026
  Reading time: 11:30
  Reading place: Auditori del Centre Universitari de la Visió
  Thesis director:
  Thesis abstract: Introduction:Keratoconus is an ocular disease that affects millions of people worldwide and represents a major cause of visual disability. Contact lens fitting is the most widely used strategy for correcting the refractive errors it induces, as it has proven to be an effective and safe option. However, no currently available lens design provides fully satisfactory results in all cases.Work performed:The main objective of this thesis was to evaluate the efficacy and safety of a new large-diameter rigid corneal contact lens design, featuring peripheral corneal support and vaulting over the cone, while simultaneously optimizing the personalized lens fitting process.In an initial study, the suitability of the corneal periphery as a bearing zone was assessed. To this end, the symmetry of revolution of the cornea in eyes with keratoconus and in healthy eyes was analysed based on a sagittal height measurements. The results indicated that the symmetry of revolution in the peripheral corneal region was comparable between both groups, supporting the feasibility of the proposed design with regard to the lens bearing area.In a second study, a prospective clinical trial was conducted to evaluate the outcomes after one year of lens wear in eyes with keratoconus. The analysis showed efficacy and safety levels comparable to those of other designs, a high level of user satisfaction, and, ultimately, high fitting and retention rates.Finally, a trial lens set based on the new design was developed and preliminarily validated thorough simulated fittings in eyes with keratoconus of different severities.Conclusions:The results obtained in this thesis demonstrate that the new large-diameter corneal lens design is a safe and effective option for visual correction in eyes with keratoconus.
  

DOCTORAL DEGREE IN PHOTONICS

• LAMICH, TOMÁŠ: A single emitter emitting resonance fluorescence into a coherent beam
  
  Author: LAMICH, TOMÁŠ
  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: 15/01/2026
  Reading date: 26/02/2026
  Reading time: 10:00
  Reading place: ICFO Auditorium https://teams.microsoft.com/meet/35229889030806?p=LCcjpiwWFwQJd0iAQs
  Thesis director: MITCHELL, MORGAN | VEYRON, ROMAIN
  Thesis abstract: This thesis studies the statistics of light produced by a single trapped atom in free space when interfaced with two orthogonal coherent beams. The atom scatters light into the same spatial mode as a weak coherent probe beam, giving rise to controllable photon statistics. Being able to control the photon statistics of a source can be used in applications in where different photon statistics are desired.A single emitter in free space, when left to interact with a single pumping beam can only scatter one photon at any given moment leading to anti-bunched photon statistics. However, Goncalves et al. (2021) studied the possibility of interfacing the atom with a strong pumping beam, and a weak probing beam, leading to a controllable photon statistics, where super- and sub-Poissonian statistics can be achieved by varying either the pump-probe ratio or the relative pump-probe phase. By controlling the pump-probe ratio, it is also possible to control the probe transmission through the atom.The experimental implementation of the "GMC" scheme shows the predicted behaviour where the transmission can be suppressed to 62 %, and tuned by changing the pump-probe ratio. It also shows that the photon statistics can go from super- to sub-Poissonian by changing the relative pump-probe phase, and the photon bunching achieved is also pump-probe ratio dependent.In addition, measurements of the atom temperature are presented in this thesis, where the interference of the pump and probe beams on the atom lead to a direct measurements of the rms displacement of the atom within the trap, which is linked directly to the atom temperature. These measurements demonstrate a new non-destructive method of estimating the atom temperature.
  
• WRAGG, JOSEPH ALAN WINDLEY: Action Microspectroscopy for Nanophotonics
  
  Author: WRAGG, JOSEPH ALAN WINDLEY
  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: 28/01/2026
  Reading date: 27/02/2026
  Reading time: 10:00
  Reading place: ICFO Auditorium
  Thesis director: VAN HULST, NIEK | BOLZONELLO, LUCA
  Thesis abstract: Stimulating an object and watching what the object does in response is the basis of scientific discovery. As much is true for much of experimental nanophotonics, where a material is stimulated with light and we observe how the material responds with nanometric precision. In this thesis I describe the development of a new approach to experimental nanophotonics: Action Microspectroscopy.The exploration of how light and matter interact holds the key to understanding, then harnessing, the properties of matter. For instance, light harvesting materials require a deep understanding of their interaction with energy in order to engineer an optimal combination of light absorption and the ensuing conversion to charge. The syntheses of new optoelectronic materials with exotic properties need precision techniques to observe such properties in action and the unexpected consequences such properties may have. As the leading edge of technology delves deeper into the nanoscale, approaches to explore matter on the same scale must be devised to keep pace.Action Microspectroscopy is a Fourier transform excitation spectroscopy platform designed to energetically, spatially and temporally diagnose the excited state in atomic systems. Its development came in stages, each benchmarked by a chapter in this thesis. Firstly, I demonstrated that the spectral response of many single molecules in a widefield image could be simultaneously acquired, meaning that spatial and spectral detail could be combined to diffractionlimited precision.The second step was to focus on the outcome of the excited state in a two dimensional semiconductor, WSe2. By studying the material’s response in fluorescence and photocurrent, it was possible to determine which exciton (excited state electrons bound to positive holes) states were more likely to lead to charge conversion and which were more likely to re-release their energy as a photon.Finally, by combining spatial detail with temporal resolution in photocurrent detection, I show that the measurement of the exciton-specific transfer of energy in materials can be achieved. I obtain spatially resolved pump-probe measurements of exciton states in WSe2, with a view to spatially resolved 2 dimensional electron spectroscopy.
  

DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS

• PUERTAS SEGURA, ANTONIO JESUS: Nano-enabled hydrogel coating for prevention of catheter-associated urinary tract infections
  
  Author: PUERTAS SEGURA, ANTONIO JESUS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS
  Department: Department of Chemical Engineering (EQ)
  Mode: Article-based thesis
  Deposit date: 16/12/2025
  Reading date: 06/03/2026
  Reading time: 15:00
  Reading place: UPC-ESEIATTSala de conferències - TR5C. Colom, 1 - TERRASSAhttps://utgct.upc.edu/ca/imatges/espais-i-recursos/zones-destudi/espai-tr5
  Thesis director: TZANOV, TZANKO KALOYANOV | CIARDELLI, GIANLUCA
  Thesis abstract: Catheter-associated urinary tract infections (CAUTIs) represent a critical healthcare challenge, accounting for a substantial proportion of the nosocomial infections worldwide and imposing significant economic burdens on healthcare systems through prolonged hospitalisation, additional treatments, and increased healthcare costs. These infections are primarily initiated by bacterial adhesion to catheter surfaces, followed by the formation of structured biofilms that protect pathogens against host immune defences and antimicrobial treatments. Biofilm-embedded bacteria exhibit significantly enhanced antibiotic tolerance and facilitate horizontal gene transfer, thereby accelerating the emergence of multidrug-resistant strains. Current clinical strategies, including catheter replacement, systemic antimicrobial therapy, and conventional surface coatings, often prove inadequate due to limited efficacy duration, poor selectivity, or cytotoxicity concerns. This underscores the urgent need for innovative, multifunctional, and biocompatible solutions capable of preventing biofilm establishment whilst maintaining excellent biological compatibility.The present doctoral thesis addresses these challenges through the design and development of advanced nano-enabled hydrogel-based coatings, specifically engineered to enhance the performance of urinary catheters. Innovative coatings were engineered to incorporate diverse antibacterial and antibiofilm nanomaterials, including lauryl gallate-, silver-, ceragenin-, and lignin-based nanoparticles, employing green and cost-effective methodologies such as sonochemical deposition and enzymatic grafting. These nano-actives were incorporated in bio-based and antifouling polymers including chitosan, catechol-modified gelatine, and polyzwitterions. The resulting hybrid coatings were engineered to combine synergistic contact-killing and sustained-release antimicrobial mechanisms with enhanced surface hydration and superior resistance to bacterial adhesion.Comprehensive physicochemical characterisation confirmed the successful integration of the nano-enabled coatings onto indwelling urinary catheters, revealing tailored surface morphology, high stability, and controlled release profiles of the active compound. In vitro assays demonstrated potent bactericidal activity and biofilm inhibition against clinically relevant uropathogens, including Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus, under both static and dynamic flow conditions that simulate physiological environments. Cytotoxicity studies revealed high biocompatibility with human fibroblasts and keratinocytes, confirming safety for prolonged medical applications. Importantly, in vivo experiments using a rabbit catheterisation model showed significant reductions in microbial colonisation and excellent biocompatibility in animals fitted with the coated catheters, validating the protective performance of these devices under realistic physiological conditions.This thesis establishes a framework for the design and implementation of nano-enabled coatings that synergistically combine antimicrobial efficacy, biofilm resistance, and host compatibility. The findings present promising pathways for advancing next-generation urinary catheter technologies and provide a solid foundation for clinical translation, ultimately aiming to minimise CAUTI incidence and reduce the global burden of antimicrobial resistance.
  

DOCTORAL DEGREE IN STATISTICS AND OPERATIONS RESEARCH

• BARRERA GÓMEZ, JOSE ANTONIO: Extension of statistical methods for time series analysis with applications in environmental epidemiology
  
  Author: BARRERA GÓMEZ, JOSE ANTONIO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN STATISTICS AND OPERATIONS RESEARCH
  Department: Department of Statistics and Operations Research (EIO)
  Mode: Normal
  Deposit date: 23/12/2025
  Reading date: 25/03/2026
  Reading time: 11:00
  Reading place: Sala d'actes de la FMECampus Diagonal Sud, Edifici U. C. Pau Gargallo, 14 08028 Barcelona
  Thesis director: BASAGAÑA FLORES, XAVIER | GINEBRA MOLINS, JOSEP
  Thesis abstract: Part of research in environmental epidemiology focuses on the assessment of associations betweenthe exposure to environmental factors and health outcomes based on aggregated longitudinal data in a given population. To model such associations, time series analysis is typically used, in which informational units are time points (e.g. days or weeks). An aggregated measure of the outcome at each time point (e.g. yearly mean cognitive test score or daily mortality count) is linked to an aggregated measure of exposure to some environmental factor of interest at the same time point (e.g. yearly mean air pollution level or daily mean ambient temperature) using a suitable regression (e.g. linear or Poisson) model. In this context, this thesis develops two studies.The first study deals with collinearity. Distributed lag models (DLNMs) have been increasingly used to model delayed effects of environmental factors on health. DLNMs include as predictors the same exposure measured at different time points. Those lagged variables are often highly correlated resulting in correlations between the estimated regression coefficients corresponding to different lags, which can lead to unreliable results. We first illustrate such problems and then propose a visual diagnosis tool to assess consequences of such collinearity. Essentially, new values of the outcome are simulated under an alternative hypothetical effect of the exposure of interest. Then, the original model is fitted again but now using the simulated data. Finally, both original and new results are compared graphically to assess if unexpected results obtained in the original analysis could be driven by collinearity. The tool is implemented in the R package collin. We provide illustrative examples and a user’s guide.The second study extends the Poisson regression model in multi-zone time series analysis for a count outcome. Those models need to control for trends and seasonality, which can be done by including time-stratum indicators (e.g. unique combinations of year, month and day of week). That implies having to include in the model a typically high number of nuisance parameters that can cause computational issues in the estimation process. This problem can be avoided with the conditional Poisson regression model, by conditioning by the sum of the outcome event counts in each stratum, which results in a multinomial regression model. By doing this, the nuisance parameters do not need to be estimated while the model provides relative risks (e.g. change in the mean mortality for a given increase in air pollution concentration) that are adjusted for long-term trends and seasonality. In cases of data from different geographical zones, a two-stage modelling procedure is usually performed, first analysing each zone separately and then combining zone-specific results into a single overall measure using, for instance, meta-analysis. A one-stage analysis, by analysing simultaneously data from all geographic zones, could be performed by including a random effect at zone level. However, the available (frequentist) software for conditional Poisson regression does not allow including random effects. In this context, we propose and develop a one-stage modelling approach, which is computationally feasible, namely Bayesian conditional Poisson mixed model, to analyse time series data for a count outcome that analyses all zones simultaneously while maintaining the good properties of the two-stage analysis. Our approach is based on conditioning out by the sum of the outcome event counts in each zone-time stratum and the inclusion of a random effect to model zone-specific association of interest. In addition, our method allows for including a spatial structure of the random effects as well as considering potential overdispersion. In the study, we derive model equations and implement the modelling procedure in R. To facilitate usage, we develop illustrative examples and provide code and data.
  
• BORJA ROBALINO, RICARDO STALIN: Optimización bayesiana en técnicas machine Learning clásicas: redes neuronales y XGBoost y su aplicación como modelos predictores de diabetes en pacientes ecuatorianos
  
  Author: BORJA ROBALINO, RICARDO STALIN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN STATISTICS AND OPERATIONS RESEARCH
  Department: Department of Statistics and Operations Research (EIO)
  Mode: Normal
  Deposit date: 22/01/2026
  Reading date: 10/04/2026
  Reading time: 11:00
  Reading place: Dia 10 d’ abril de 2026 a les 11h del matí a la Sala de Juntes de la FIB
  Thesis director: MONLEON GETINO, ANTONIO | GIBERT OLIVERAS, CARINA
  Thesis abstract: Machine learning (ML) is a branch of artificial intelligence that allows human capabilities to be imitated through various algorithms and techniques that learn from data using learning processes (supervised, unsupervised, or reinforcement) for decision-making with minimal human intervention. Classic ML models have generated great results in the automation of classification and regression processes in various areas. Within classification, artificial neural networks (ANN) have gained relevance due to their ability to learn and model complex nonlinear relationships. Similarly, the XGBoost model based on decision trees has demonstrated great efficiency, speed, scalability, and performance, winning several competitions. On the other hand, Bayesian inference has provided a probabilistic and revolutionary framework for optimizing machine learning models, with the implementation of uncertainty in the estimation process, combining evidence with prior beliefs, in order to reduce overfitting and improve predictions by adjusting parameters and hyperparameters.This research aims to optimize two classic machine learning techniques (artificial neural networks and XGBoost) for classification using Bayesian inference and to build a diabetes prevention model for the Ecuadorian population. The study begins with a theoretical and mathematical conceptualization of each algorithm, followed by an analysis of the various points of intervention, programming, and implementation of Bayesian models using Markov chain Monte Carlo (MCMC) estimation techniques and variational inference (VI), validation using public databases, implementation of a client-server system with multiple specialized backends, and, finally, the development of a real application as predictors of type 1, type 2, and gestational diabetes.As a result, a Bayesian model was implemented in artificial neural networks (ANN) at two inference points. The first adjusted the parameters at each backpropagation step; however, it presented itself as an option with a prohibitive computational overhead. As a second intervention, an adjustment was made to the activation function in the final layer, obtaining positive and computationally viable results. In the case of XGBoost, the predictions were adjusted at each boosting step before vectorization, demonstrating high predictive power in both the use of the MCMC technique and IV. Validation with the Pima Indians Diabetes database and the use of various distribution functions demonstrated the robustness and sensitivity of the implemented models, while generalization and consistency were verified through application to various databases. In all cases, results superior to or equal to those obtained using the traditional model were obtained, depending on the characteristics of the data.In addition, a web application (client-server) was implemented with Bayesian proposals, allowing users to interact with the models in an easy and intuitive way, with options for data loading, parameter configuration and probability distributions, estimation techniques (MCMC or IV), training-validation process or use of cross-validation, real-time results, and model download options. The application of the Bayesian proposal to a real case, such as the prediction of type 1, type 2, and gestational diabetes, with data from Ecuadorian patients, presented encouraging results (accuracy = 99.47%), becoming the first predictive model for the three types of diabetes at the regional and national level, confirming that the use of this approach is an excellent alternative for the optimization of machine learning models.
  

DOCTORAL DEGREE IN STRUCTURAL ANALYSIS

• ALCAYDE ROMO, BARBARA: Numerical modelling of the fatigue behaviour of composites. Application to the automotive industry.
  
  Author: ALCAYDE ROMO, BARBARA
  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: 19/12/2025
  Reading date: 06/03/2026
  Reading time: 11:00
  Reading place: Sala Zienkiewich (CIMNE) Building C1, UPC - Campus North Gran Capitan S/N 08034 Barcelona
  Thesis director: BARBU, LUCIA GRATIELA | CORNEJO VELÁZQUEZ, ALEJANDRO
  Thesis abstract: In an engineering landscape increasingly focused on optimized design, lightweight materials, and multifunctional performance, accurately predicting the fatigue behaviour of composite materials under realistic service conditions is essential. Traditional approaches to fatigue analysis in Fibre Reinforced Polymers (FRP) often rely on simplified extrapolations of laboratory data or homogenized models that neglect the complex interactions between constituent materials and environmental influences. Moreover, these approaches typically fail to account for temperature variations. Such reductionist perspectives limit the ability to capture the coupled mechanical and thermal degradation mechanisms inherent to advanced materials. This thesis proposes a unified numerical framework grounded in the Finite Element Method (FEM), integrating a phenomenological homogenization strategy, the Serial Parallel Rule of Mixtures Law (SP-RoM), with a High Cycle Fatigue (HCF) Constituive Law (CL). This approach enables the simultaneous representation of the distinct fatigue responses of fibres and matrix within layered composite laminates, accounting for variations in stacking sequence and fibre orientation. A key innovation is a calibration methodology that infers fatigue parameters at constituent level from experimental data at laminate scale, thus overcoming the challenges of direct testing of individual components. Furthermore, the work presents a thermomechanically coupled fatigue model incorporating temperature dependent material properties and thermal expansion, generalizing classical fatigue life prediction curves to fluctuating and spatially varying temperature fields. To address the significant computational demands of fatigue simulations, an Advance in Time Strategy (AITS) Cycle Jump (CJ) is developed, enabling efficient simulation of long-term fatigue damage evolution without sacrificing accuracy. Validated against experimental benchmarks and literature data, the proposed methodology advances fatigue life prediction in composite materials by delivering a flexible, robust, and computationally efficient tool. Additionally, the fatigue formulation has been enhanced to capture complex thermomechanical effects. This work lays the foundation for future research on integrated modelling of fatigue and multiphysics deterioration phenomena in advanced composite structures.
  

DOCTORAL DEGREE IN SUSTAINABILITY

• VALLEJOS CARTES, ROSANA: Examinando preferencias, motivaciones y actitudes de los consumidores para mejorar la sostenibilidad de los sistemas agroalimentarios. Una aplicación a los sistemas agropastorales extensivos.
  
  Author: VALLEJOS CARTES, ROSANA
  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: 22/12/2025
  Reading date: 20/03/2026
  Reading time: 12:30
  Reading place: Salón de grados de la EEABB en Castelldefels
  Thesis director: GIL ROIG, JOSE MARIA
  Thesis abstract: In the context of global transformations in the agri-food system—marked by environmental pressures, biodiversity loss, market concentration, and dietary homogenization—a critical scenario for sustainability has emerged. Within this landscape, extensive livestock farming, based on grazing and traditional management practices, constitutes a viable alternative to intensive production by integrating ecological, economic, and sociocultural dimensions. Nevertheless, its long-term viability depends largely on consumer recognition, as purchasing decisions can drive the transition toward more sustainable systems. This thesis assumes that consumers operate as agents of change but face constraints linked to limited information, perceptions of high prices, and insufficient market differentiation. Accordingly, the general objective was to assess the economic and social viability of extensive livestock systems through an examination of consumer preferences, motivations, and attitudes toward sustainably produced lamb meat, generating evidence to inform differentiation strategies and public policies that support agri-food sustainability. The research employed a mixed-methods design developed in two complementary phases. The qualitative phase comprised semi-structured interviews and participatory workshops with sheep producers to identify sustainability drivers and market-valued attributes. The quantitative phase implemented Discrete Choice Experiments (DCEs) among consumers in Catalonia, carried out in two stages: an exploratory study (n = 396) to refine attributes and optimize the experimental design, followed by a larger study (n = 1,003) incorporating attitudinal measures through the New Ecological Paradigm (NEP) scale. Data were analyzed using mixed logit and latent class models, enabling the identification of heterogeneous preferences, the estimation of willingness to pay, and the integration of environmental and ethical attitudes into consumer choice modeling.The findings reveal a complex interaction between knowledge, attitudes, and values in shaping preferences for sustainable meat. Results indicate limited consumer knowledge of production systems—particularly extensive livestock farming—despite the strong symbolic valuation of local origin, animal welfare, and territorial authenticity. Labeling and certification mechanisms emerge as essential tools for building trust and supporting informed decisions. The highest willingness to pay is associated with organic production and animal welfare, while sensory cues such as color and visible fat exert a complementary influence.The research confirms a persistent gap between stated attitudes and actual behaviors, shaped by economic constraints, purchasing routines, and information availability. However, it also identifies a segment of consumers who are informed and value-consistent, suggesting opportunities for differentiation through targeted communication, certification, and education initiatives. Overall, the thesis provides an integrated understanding of the relationship between consumer behavior and sustainability, advocating for a renewed appreciation of agro-pastoral systems as public goods that deliver not only food but also essential ecosystem and cultural services. Its results contribute to the development of agri-food policies and market strategies that acknowledge the role of consumer demand in advancing sustainable production models, reinforcing consumers as central actors in the transition toward an ethical, territorially grounded, and environmentally responsible agri-food economy.
  

DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE

• ROGER GONCE, JOAN: “El barrio que (nos) construimos” Creixement i desenvolupament urbà del barri de Roquetes de Barcelona, a través del Padró Municipal d’Habitants (1940-1978)
  
  Author: ROGER GONCE, JOAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE
  Department: Department of History and Theory of Architecture and Communication Techniques (THATC)
  Mode: Normal
  Deposit date: 13/01/2026
  Reading date: 27/03/2026
  Reading time: 11:00
  Reading place: ETSAB (Escuela Técnica Superior de Arquitectura de Barcelona) - Planta Baja - Sala de GradosAv. Diagonal, 649-651 - 08028 - Barcelona
  Thesis director: ROSSELLO NICOLAU, MARÍA ISABEL | OYON BAÑALES, JOSE LUIS
  Thesis abstract: This study addresses the urban history of the Roquetes neighborhood of Barcelona during the Franco period, with the aim of analyzing its formation, consolidation and transformation over the course of more than forty years of dictatorship. The work aims to provide data and a critical reflection on the social, economic and urban processes that shaped this working-class and markedly immigrant neighborhood, in a context of accelerated growth, precarious infrastructure and territorial inequalities.The meticulous analysis of the municipal population register, systematically cross-referenced with other demographic, labor and urban sources, has allowed us to delve deeper into key issues for understanding the neighborhood's trajectory: the migratory networks and chains that sustained its growth; the forms of work and the opportunities —or limits— of social mobility for its residents; the housing conditions and models of urban production; and, finally, the construction of the neighborhood as a space for coexistence, identity and sociability in a framework of institutional abandonment and neighborhood responses.Through this combination of perspectives and sources, the research provides an integrated look at Roquetes that contributes to the broader debate on urban peripheries, Franco's socialist regime and the everyday experiences of popular sectors in 20th-century Barcelona.
  

DOCTORAL DEGREE IN URBAN AND ARCHITECTURAL MANAGEMENT AND VALUATION

• SIFUENTES MUÑOZ, BLANCA CAROLINA: Transformación urbana y movilidad sostenible: construyendo una Barcelona car-free
  
  Author: SIFUENTES MUÑOZ, BLANCA CAROLINA
  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 URBAN AND ARCHITECTURAL MANAGEMENT AND VALUATION
  Department: Department of Architectural Technology (TA)
  Mode: Normal
  Deposit date: 15/12/2025
  Reading date: 02/03/2026
  Reading time: 16:30
  Reading place: ETSAB - Pl. Baja - Sala GradosAv. Diagonal, 649-BCN(Enlace a videoconf: https://meet.google.com/uko-xgpp-byk - Inicio conexión: 16:00 hora Bcn)
  Thesis director: ROCA CLADERA, JOSE NICASIO | ARELLANO RAMOS, BLANCA ESMARAGDA
  Thesis abstract: The configuration of contemporary cities has been deeply shaped by the hegemony of the automobile as a structuring axis of territory, mobility, and public space. This model, consolidated since the mid-20th century, has led to dispersed, exclusionary, and unsustainable urban forms, limiting quality of life and hindering the creation of more equitable and resilient environments. In response, critical approaches have emerged advocating for a paradigm shift toward people-centered cities, the right to the city, and sustainable mobility.In this context, this doctoral thesis aims to construct prospective scenarios for a car-free Barcelona by 2050, through a structural and multiscalar analysis of its mobility system, urban planning, and use of public space. A mixed-methods approach is adopted, integrating six methodological lines: (1) collection and preprocessing of mobility data from the Barcelona Metropolitan Area (AMB); (2) exploratory factor analysis (EFA) on a longitudinal AMB database; (3) trend analysis using regression and ARIMA models to project modal shifts; (4) comparative analysis of Amsterdam and Copenhagen as international car-free transition benchmarks; (5) expert consultation through a disaggregated Delphi method; and (6) construction of contrasted future scenarios.The results identify latent structures in the mobility system, tensions between urban policies and actual mobility practices, and institutional challenges linked to multilevel governance. The developed scenarios outline alternative urban futures, from continuity-based models to deep transformations, highlighting their implications in terms of equity, sustainability, and the right to the city.This research provides an original contribution by integrating approaches from sustainable mobility, prospective planning, and multiscalar analysis. Its findings guide the formulation of public policies and urban strategies toward more just, healthy, and sustainable post-car cities. Ultimately, it proposes conceptual and methodological tools to rethink urbanism through the lens of deep transformation in the face of climate, social, and territorial uncertainty.
  

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

• CARRIZOSA RENDÓN, ÁLVARO: Advances in Set-Based Motion Planning for Safe Interaction of Autonomous Vehicles
  
  Author: CARRIZOSA RENDÓN, ÁLVARO
  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: Department of Automatic Control (ESAII)
  Mode: Normal
  Deposit date: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: PUIG CAYUELA, VICENÇ | NEJJARI AKHI-ELARAB, FATIHA
  Thesis abstract: This thesis presents several contributions in the field of safe driving of autonomous vehicles, focusing on motion planning and prediction of environmental agents based on their behaviour. The methodologies combine set-based techniques, LPV models and optimisation, seeking to ensure safety with low computational cost in realistic scenarios.First, a comprehensive review of the literature on the use of set-based methods to address safety in autonomous driving is presented. The study focuses on three main families of techniques: reachability analysis, invariant sets, and feasibility theory, describing how they have been applied to different planning, control, and supervision problems. Their advantages, disadvantages, differences and similarities are analysed. With this review, a unified framework for interpreting the existing literature is proposed, which serves as a basis for justifying the design decisions adopted in the subsequent contributions of the thesis.The following contribution consists of a safe motion planner designed for structured convex scenarios with complete knowledge of the environment and the actions of the agents surrounding it. To this end, a formulation based on LPV models and reachability analysis using zonotopes with constraints is proposed, which is integrated into a predictive control scheme formulated as a quadratic problem. This approach allows explicit safety constraints to be imposed on the optimiser, ensuring collision avoidance and achieving safe trajectories with lower computational cost and less conservatism than classical robust approaches.Subsequently, an efficient prediction method is proposed to estimate the future occupancy of surrounding vehicles online, based solely on their observed actions. The approach is based on optimisation and zonotopic propagation techniques to construct occupancy sets that adapt dynamically without the need for trained models or prior assumptions. The result is a refined and computationally lightweight estimator, designed to be integrated into real-time planners.Finally, a motion planner capable of working in complex urban scenarios is presented, extending the two previous contributions. Based on the first safe planner, a new structure is formulated that maintains the QP problem but now employs a purely zonotopic reachability analysis combined with constraints, allowing it to work in non-convex environments and with partial knowledge of the intentions of surrounding vehicles. The prediction module is proposed as an evolution of the previous one, taking advantage of the known geometry of the road to obtain more refined occupancy sets.
  

DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING

• FUENTES LLANOS, JUDITH: Development of 3D Bioengineered Skeletal Muscle-based Bioactuators for Biorobotic and Biomedical Applications
  
  Author: FUENTES LLANOS, JUDITH
  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 Materials Science and Engineering (CEM)
  Mode: Article-based thesis
  Deposit date: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: SÁNCHEZ ORDÓÑEZ, SAMUEL | GUIX NOGUERA, MARIA
  Thesis abstract: Biohybrid systems are engineered constructs that integrate living materials, like cells or tissues, with synthetic components, such as electronics, mechanical structures, or other artificial materials. This integration aims to leverage the unique capabilities of biological materials, including self-assembly, responsiveness to certain stimuli, adaptability, and self-repair, being features challenging to replicate in their synthetic counterparts. By combining these traits with the robustness and compliance of synthetic structures, biohybrid systems emerge as versatile platforms capable to both adapt and actuate in dynamic environments. Among the various biological components explored, skeletal muscle stands out due to its high force-to-weight ratio, controllable contraction, and compatibility with 3D biofabrication strategies, making it ideal for applications in soft robotics, drug testing, and regenerative medicine.This PhD thesis focuses on the development of 3D bioengineered skeletal muscle bioactuators, addressing key aspects from the biofabrication to functionality improvement, actuation control, and regenerative capacity.We developed and optimized a Pluronic-Assisted Coaxial 3D bioprinting (PACA-3D) method capable of biofabricating fascicle-like skeletal muscle bioactuators with improved maturation, sarcomere formation and contractile force when compared to muscles generated using conventional extrusion-based 3D bioprinting. To improve actuation and directional control, we introduced magnetic responsiveness into the bioactuators by developing a biocompatible ferrofluid-based bioink, used to fabricate the Ferromuscle, in collaboration with Waterloo and Aalto Universities. Such bioactuators exhibited improved cell alignment and force output, as well as magnetically guided actuation. In collaboration with the University of Cagliari (UniCa), we also evaluated the integration of flexible Organic Field-Effect Transistor (OFET)-based strain sensors for real-time monitoring of contractile behavior. These devices allowed tunable force sensing, showing no signal cross-talk when using standard electrical stimulation protocols, which is paving the way for closed-loop stimulation strategies and automated drug screening platforms. Moreover, we evaluated the self-healing capacity of the bioactuators after damage conditions, designed to mimic the mechanical stress that they typically undergo during manipulation of biohybrid systems. We observed partial to full force recovery and structural remodeling without external interventions, although the underlying biological mechanisms remain to be elucidated.Finally, additional collaborative work that enriched this thesis will be also discussed. Such studies include the integration of tendon-like structures to develop muscle-tendon unit (MTU) actuators with enhanced biomimicry, performance, and stability (ETH Zurich). Moreover, it will also be covered the design of biohybrid flexure mechanisms powered by skeletal muscle, evaluating how skeleton architecture and voltage- or current-based stimulation influence actuation output (SSA and UniCa).Altogether, the work presented in this thesis contributes to the field of biohybrid robotics by combining advanced fabrication, actuation control, integrated sensing, and regenerative capacity. These developments move us closer to robust, autonomous, and functional biohybrid machines for applications in soft robotics, tissue engineering, and biomedical research.
  
• PRIOR PALOMARES, OLIVIA: Quantifying Tumor Heterogeneity in Colorectal Liver Metastases with CT-Derived Habitats
  
  Author: PRIOR PALOMARES, OLIVIA
  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 Strength of Materials and Structural Engineering (RMEE)
  Mode: Normal
  Deposit date: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: PÉREZ LÓPEZ, RAQUEL
  Thesis abstract: In colorectal cancer, mortality is primarily driven by metastatic disease, most commonly to the liver. Colorectal liver metastases are biologically heterogeneous, composed of varying proportions of viable tumor cells, fibrosis, and necrosis. Both the presence and spatial organization of these tissue components influence treatment response and patient outcome. In clinical practice, however, such information is available only through biopsy, which samples a limited tumor region, or after surgical resection, which is feasible in only a minority of patients. As a result, most patients receive systemic therapy without direct knowledge of whole-tumor tissue composition.Computed tomography (CT) is the standard imaging modality for managing colorectal liver metastases and is acquired repeatedly throughout the disease course. Despite providing non-invasive, spatially resolved information at the whole-tumor level, clinical interpretation continues to focus largely on lesion size, number, and location. Consequently, the ability of CT to characterize intratumor heterogeneity has not yet been fully leveraged.Habitat imaging has been proposed as a framework for capturing tumor heterogeneity by partitioning tumors into spatial subregions with similar imaging properties (habitats). Most habitat imaging studies rely on multiparametric MRI (mpMRI), whose quantitative maps are biologically interpretable, while applications to CT remain limited despite its widespread clinical use. In addition, existing studies rarely assess the robustness of CT-derived features, often define habitats through purely data-driven optimization without biological grounding, and generally do not report clinical relevance beyond tumor volume.This thesis addresses these gaps by investigating whether routine CT can capture biologically and clinically meaningful intratumor heterogeneity in colorectal liver metastases. First, we identified 26 radiomic features suitable for robust CT-based habitat computation based on repeatability and reproducibility criteria. Second, we developed a biologically anchored CT habitat model by incorporating co-registered mpMRI as a reference during habitat definition, rather than relying solely on statistical optimization. Within this framework, we compared multiple CT representations, including handcrafted radiomic features and deep learning embeddings, and found that handcrafted features produced more biologically coherent habitats. The resulting three habitats reflected vascular architecture: an avascular core, a cellular, perfused intermediate zone, and a highly vascularized outer rim.Third, we evaluated clinical relevance by assessing associations between habitat-derived metrics and patient outcomes in two independent cohorts. Habitat metrics provided prognostic information beyond tumor volume, but only in specific treatment contexts. In particular, habitat entropy at the tumor–liver interface predicted survival in settings in which treatment may alter tissue composition without inducing measurable size changes. Across all treatment contexts, prognostic information consistently localized to the invasive tumor rim rather than being uniformly distributed throughout the lesion.Overall, this thesis contributes both methodological and clinical advances: an open-source CT habitat imaging pipeline, a comprehensive assessment of handcrafted radiomic feature robustness, the first comparison of CT representations for habitat computation, biological grounding of CT-derived habitats using mpMRI, and demonstration of their context-dependent clinical relevance. Together, these findings establish that routine CT scans contain clinically meaningful information about tumor heterogeneity that current assessment strategies do not capture, and provide a framework for extracting it.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• JEBBAD, RAGHDA: Impacts of climate change on the ports of the Southwestern coast of the Alboran Sea
  
  Author: JEBBAD, RAGHDA
  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: 18/02/2026
  Deposit END date: 03/03/2026
  Thesis director: MÖSSO ARANDA, OCTAVIO CESAR | SIERRA PEDRICO, JUAN PABLO
  Thesis abstract: Climate change is altering the coastal conditions that ports are designed to withstand, through sea-level rise and changes in storm-driven wave regimes. These changes can reduce operability, increase overtopping impacts on exposed structures, and affect harbour agitation and breakwater performance. This thesis develops an applied and integrated framework to translate offshore climate projections into port‑scale impact indicators and adaptation pathway planning for Moroccan Mediterranean ports along the southwestern Alboran Sea.Offshore wave conditions are characterised using a four‑dataset Med-CORDEX ensemble under RCP4.5 and RCP8.5, and propagated to the nearshore with a regional SWAN model featuring port‑scale nesting. Combined with sea level rise projections, these forcings are used to quantify four port‑impact indicators: berthing inoperability based on still‑water‑level exceedance relative to minimum freeboard requirements; wave overtopping discharge at exposed structures; harbour agitation exceedance within the basin; and breakwater stability under extreme forcing. The overtopping assessment is applied across eight ports to establish relative exposure and identify the most exposed sites. Berthing inoperability and an indicative dock‑raising cost estimate are developed for Tangier‑Med. A multi‑process assessment is carried out for Al Hoceima, together with an applied adaptation‑pathways case study that links impact levels to response options over time. The thesis also develops an uncertainty‑evaluation framework to support the interpretation of wave‑driven port impact projections.
  

DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS

• BLANCO CASARES, ANTONIO: A Numerical Framework for Solving Complex Flow Regimes with Continuous Galerkin
  
  Author: BLANCO CASARES, ANTONIO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 18/02/2026
  Deposit END date: 03/03/2026
  Thesis director: LEHMKUHL BARBA, ORIOL | MIRA MARTÍNEZ, DANIEL
  Thesis abstract: This thesis investigates a stable and high-order numerical formulation for solving a variety of flow problems using the continuous Galerkin method, including reacting, compressible, and incompressible flows. Reliable and accurate numerical tools for such problems are crucial in many real-world applications, ranging from aerodynamics and industrial processes to medical studies, where high-fidelity and computational efficiency are simultaneously required. Achieving stable solutions in advection-dominated problems, particularly on nonuniform meshes, remains a fundamental challenge.To address this, the thesis develops a stabilization strategy well-suited for high-order elements, such as the spectral ones, designed to effectively eliminate numerical instabilities while introducing minimal numerical dissipation to achieve a high accuracy solution. Based on recent literature, we have focused on stabilization methods based on gradient projection, which allows to detect the numerical fluctuations to effectively stabilize the system. The numerical stencil features a combination of a high- and low-order stabilization ruled by a smoothness sensor. High-order stabilization is applied in smooth regions to maintain physical profiles, while low-order stabilization is activated only near strong gradients to suppress non-physical oscillations. This methodology is formulated for a generic conservation law and tested across linear advection, scalar transport in reacting flows, compressible, and incompressible Navier–Stokes problems.The numerical results show that, for turbulent premixed combustion under the low-Mach assumption, the approach handles tabulated chemistry with the flamelet model, delivering a proper representation of the flame-front. For compressible flows, a Mach-number-based smoothness sensor has been developed, effectively handling complex flow features such as shock waves. For incompressible flows, the algorithm employs a fractional step method with well defined boundary conditions, maintaining the same stabilization principles inherent to this method. In all cases, the stabilization introduces diminishing numerical dissipation with increasing polynomial order, achieving optimal convergence under both mesh refinement and polynomial order increase.These developments contribute to practical, large-scale numerical simulations that balance computational efficiency with high-fidelity results, enabling accurate prediction of real-world physical phenomena. The proposed framework provides a robust and scalable tool for computational fluid dynamics applications, with potential impact across scientific research, and industrial modeling.
  
• PUCH GINER, IGNASI: Optimization of Monte Carlo and Molecular Dynamics Techniques for Receptor–Ligand Binding Studies
  
  Author: PUCH GINER, IGNASI
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 16/02/2026
  Deposit END date: 27/02/2026
  Thesis director: GUALLAR TASIES, VÍCTOR
  Thesis abstract: Drug discovery is a complex and resource-intensive process that requires the identification of molecular candidates with optimal binding properties to their corresponding targets. Computational techniques play a central role in streamlining this process by predicting biomolecular interactions, optimizing molecular properties, and accelerating early-stage drug development.This thesis focuses on advancing computational strategies for biomolecular modeling, integrating molecular mechanics techniques—such as Monte Carlo and molecular dynamics simulations—with state-of-the-art machine learning tools. The objective is to improve scoring functions, enhance simulation accuracy, and develop a framework that enables the application of these methods to real-world pharmacological challenges.A key contribution of this work is the systematic characterization of the PELE (Protein Energy Landscape Exploration) simulation framework, including the rationalization of binding energy estimators and the assessment of their predictive performance and computational efficiency. These benchmarks address existing knowledge gaps in scoring functions and facilitate more accurate predictions of protein–ligand interactions, thereby supporting the prioritization of promising molecules for experimental evaluation.Beyond methodological advances, this thesis applies the developed computational approaches to pharmacologically relevant case studies. The structural characterization of the amino acid transporter Asc1/CD98hc was carried out using an integrated computational pipeline, providing new insights into its binding and transport mechanisms. Furthermore, the study of the Meis1–Hoxb13 transcription factors explores novel drug–DNA interactions with potential implications for targeted therapies. Another application focuses on Charcot–Marie–Tooth disease, where computational simulations contributed to understanding GDAP1–LAMP1 tethering dysfunction and possible therapeutic interventions. These examples highlight the versatility of the proposed computational strategies across diverse biological contexts.The results of this research propose a practical framework for improving ligand-binding predictions. The explored methodologies strengthen molecular modeling by combining physics-based techniques with varying speed–accuracy trade-offs and data-driven approaches, bridging the gap between traditional simulation methods and AI-driven predictions. The findings have implications for both academic research and industrial drug discovery, offering scalable and generalizable solutions for structure-based and ligand-based design.
  

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

• DOBLAS FONT, MAX: High-Performance Sequence Alignment: Co-Designing Algorithms and Hardware Architectures for Efficient and Scalable Acceleration
  
  Author: DOBLAS FONT, MAX
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 20/02/2026
  Deposit END date: 05/03/2026
  Thesis director: MORETÓ PLANAS, MIQUEL | MARCO SOLA, SANTIAGO
  Thesis abstract: Over the past decade, the exponential growth of genomic data has driven significant advancements in genomics and healthcare, enabling breakthroughs in large-scale genomic studies, personalized medicine, and epidemiological surveillance. However, this rapid data expansion has also posed substantial computational challenges, particularly in sequence alignment, a cornerstone of genomic analysis. Sequence alignment is critical for applications such as disease diagnostics, population-wide genetic research, and outbreak tracking, yet it demands scalable and efficient solutions to handle the increasing data volumes and diverse use cases.This thesis addresses the efficiency-flexibility gap in sequence alignment through three key contributions. First, it introduces QuickEd, a novel sequence alignment algorithm that reduces computational complexity by combining heuristic bounding with optimal alignment. QuickEd achieves O(nŝ) complexity, where n is the sequence length and ŝ is an estimated upper bound of the alignment score, significantly improving upon the O(n²) complexity of traditional dynamic programming algorithms. By efficiently bounding the maximum alignment score, QuickEd reduces the computational burden while maintaining accuracy, making it well-suited for long-read sequencing and other demanding applications.Second, this thesis proposes GMX, a set of instruction set architecture (ISA) extensions designed to enhance the efficiency of dynamic programming-based alignment algorithms. GMX provides fundamental building-block operations for fast, tile-wise computations of the DP matrix, reducing memory footprint and computational overhead. These extensions enable seamless integration into widely used algorithms and tools, offering a cost-effective alternative to domain-specific accelerators (DSAs) while achieving comparable performance improvements.Third, the thesis presents SMX, a heterogeneous architecture that balances flexibility and performance to address the diverse requirements of real-world sequence alignment tasks. SMX integrates an ISA extension (SMX-1D) for irregular and sequential tasks and a specialized coprocessor (SMX-2D) for regular and parallel tasks, all orchestrated by a general-purpose core. This architecture supports various configurations for different sequence types (DNA, protein, and ASCII text) and alignment models, including weighted gaps and substitution matrices. By combining high performance with adaptability, SMX enables efficient acceleration of a wide range of sequence alignment applications.Together, these contributions advance the state of the art in sequence alignment, providing scalable, flexible, and efficient solutions to meet the demands of modern genomic analysis. The innovations presented in this thesis pave the way for faster and more reliable genomic analyses, facilitating critical applications such as personalized medicine, population-scale sequencing, and epidemiological surveillance in the era of long-read sequencing technologies.
  

DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING

• CUADROS ROJAS, EMERSON JULIO: Out-of-Plane Flexural Behaviour of Masonry Walls Reinforced with High-Strength Steel Cord Mesh
  
  Author: CUADROS ROJAS, EMERSON JULIO
  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: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: PELA, LUCA | ROCA FABREGAT, PEDRO
  Thesis abstract: Perforated brick masonry facades with exposed brickwork are a common feature in contemporary construction, yet they frequently demonstrate an out-of-plane response that renders them suscep-tible to wind and seismic action. Concurrently, innovative horizontal joint reinforcement systems utilising high-strength steel meshes are being adopted in increasing numbers in practice, although specific design provisions are still lacking. The present thesis investigates the mechanical behav-iour of perforated brick masonry walls reinforced with high-strength steel meshes. The investiga-tion focuses on out-of-plane bending response, and the thesis combines three different experi-mental programs in the laboratory, and numerical modelling.Initially, the experimental characterisation of the constituent masonry materials was conducted. Tests were carried out on perforated clay bricks and M5 mortar to provide their compressive and flexural strengths. Masonry prisms were subjected to compression tests and monitored using digi-tal image correlation (DIC) to determine the compressive strength, Young’s modulus and Pois-son's ratio. A methodology was proposed that utilised a co-barycentric effective area approach in order to account for the eccentricity induced by the asymmetric perforation pattern when evalu-ating compressive strength and stiffness.The shear behaviour of perforated brick masonry was the subject of a second experimental pro-gramme that involved triplet tests performed at three levels of pre-compression. The employment of DIC facilitated the observation of damage mechanisms and the estimation of Mohr-Coulomb strength parameters. The core of the research focuses on the execution of out-of-plane flexural tests of five unrein-forced masonry walls and six walls reinforced with high-strength steel mesh arranged with two different separations (0.6 m and 0.4 m, corresponding to geometric reinforcement ratios of 0.015% and 0.022%). The experimental programme was conducted in accordance with the four-point bending method specified in the standard EN 1052-2, and the damage process was moni-tored with three-dimensional digital image correlation (3D DIC). The reinforced walls demon-strated a substantial enhancement in strength and ductility in comparison to the unreinforced walls, higher overstrength ratios, and significantly greater ultimate displacements. The walls with a higher amount of bed-joint reinforcement exhibited a more distributed cracking with reduced crack widths, demonstrating crack control at low geometric reinforcement ratios compared to traditional reinforcement systems.An analytical model for the moment-curvature response and finite element micro-models were developed and calibrated based on the experimental results.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• FORERO QUINTERO, JOSE FERNANDO: Flexibility Management System with Distributed Energy Resources
  
  Author: FORERO QUINTERO, JOSE FERNANDO
  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: Article-based thesis
  Deposit date: 19/02/2026
  Deposit END date: 04/03/2026
  Thesis director: VILLAFÁFILA ROBLES, ROBERTO | MONTESINOS MIRACLE, DANIEL
  Thesis abstract: The challenge of climate change is ever demanding more technological and political efforts to respond adequately to its adverse effects, which could put life on the planet at risk. Diverse plans have been proposed to incorporate more renewable generation and digitalize the power system in a decarbonizing energy transition framework. However, such plans are either not being accomplished or are insufficient according to the Paris Agreement. At the same time, emerging technologies such as artificial intelligence, high-performance sensing and automation, and real-time information and communication systems, among others, are transforming electrical networks into smart grids, aggregating more complexity.This thesis, based on a papers compendium, first surveys the existing energy management systems with distributed energy resources, delving into their configuration, energy and flexibility sources, information and communication systems, profitability analysis and indicators, and flexibility services. After reviewing the state of the art, this thesis focuses on boosting management systems towards the real-time horizon, proposing a flexibility management system. This system is a hierarchical three-level management system based on an adaptive autoregression algorithm, cost-benefits analysis, and redispatching and unit recommitment submodules to control and manage the power, and short-term flexibility requests.To validate the proposed system, not only several simulations and sensitivity analyses are carried out, but real-world energy assets are addressed in PVZEN microgrid lab in Torino, Italy. The results demonstrate that proposed system can reduce the cost overruns of real-time power deviations of the distributed resources, leverage the excess of renewable energy, and generate profits providing flexibility services to the grid. Chapters 2, 3, and 4 show the papers related to this thesis, starting with reviewing the art status, passing through the simulations and analysis, and finishing with the essays on real-world energy assets. Main conclusions and future work are depicted at the end of the document.
  

DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING

• SOUSSE VILLA, RUBEN: Dust in the atmosphere: Integrated modeling of heterogeneous chemistry, mineralogy, and optical properties
  
  Author: SOUSSE VILLA, RUBEN
  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 ENVIRONMENTAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 16/02/2026
  Deposit END date: 27/02/2026
  Thesis director: PEREZ GARCIA-PANDO, CARLOS | JORBA CASELLAS, ORIOL
  Thesis abstract: Airborne mineral dust is one of the dominant aerosol components in the atmosphere and plays a central role in the Earth system through its interactions with atmospheric composition and radiation. Despite its importance, large uncertainties remain in its representation in atmospheric and climate models, particularly concerning dust heterogeneous chemistry. These reactions between dust particles and gas species play a dominant role over dust affected regions in the formation of secondary inorganic aerosols such as particulate nitrate, ammonium, and sulfate. Yet, they are still subject to strong simplifications and parameterizations in atmospheric models, which still show significant discrepancies in their representation.This Thesis aims to advance the understanding of dust atmospheric chemical processes, their dependence on mineralogical composition, and their implications for aerosol optical properties. To this end, multiple dust heterogeneous chemistry mechanisms and mineralogical representations are implemented and systematically evaluated within the MONARCH atmospheric chemistry model. Their impacts on atmospheric composition, aerosol acidity, and optical properties are assessed and evaluated against observations. Notably, this work represents the first integration into an atmospheric chemistry model of observationally constrained maps of surface mineral composition of arid surfaces derived from the recently launched NASA’s Earth Surface Mineral Dust Source Investigation (EMIT) spectrometer.The evaluation of different dust heterogeneous chemistry mechanisms highlights the importance of representing reversible secondary inorganic aerosol formation in both fine and coarse particle modes, together with an accurate treatment of dust and sea-salt alkalinity. This combined approach is shown to be necessary to achieve consistent nitrogen budgets and aerosol acidity, and to better reproduce observed atmospheric nitrate concentrations.The comparison of different mineral atlases focuses on calcite as the primary contributor to dust alkalinity, demonstrating that EMIT provides the most consistent representation of the atmospheric calcite cycle. The use of source-resolved mineralogy compared to the common assumption of globally averaged dust mineral content, reveals strong geographical contrasts in calcite abundance, particularly between the Middle East and other major dust regions such as the Sahara and East Asia. These differences in calcite lead to marked regional and size-dependent implications for aerosol acidity and secondary inorganic aerosol formation. Impacts on particulate nitrate are found to be most pronounced during short-lived, intense formation events in regions affected by both dust and anthropogenic pollution, while global burdens and long-term trends are less sensitive.The implications of dust chemistry and mineralogical representation for aerosol optical depth and single scattering albedo are generally modest, with fine-mode aerosols exerting a larger influence than coarse particles, though both remain secondary compared to strongly absorbing minerals such as iron oxides. Limitations related to the representation of absorbing carbonaceous aerosols and the absence of cloud–aerosol interactions constrain the assessment of radiative effects.Overall, this Thesis demonstrates that combining reversible dust heterogeneous chemistry with source-resolved mineralogical information from EMIT substantially improves the representation of dust–gas interactions and their impacts on atmospheric composition and aerosol optics. Remaining uncertainties highlight the need for continued development of mineralogical datasets and chemical parameterizations, as well as the inclusion of anthropogenic dust sources and additional reactive gas species. Further progress would also benefit from high-resolution modeling of small-scale dust events and from expanded observational coverage over dust-affected urban regions.
  

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

• MORALES FLAUZÍN, GERARDO ABEL: Advances in geotechnical experimental techniques for unsaturated and liquefactable soils and tailings under different gravity accelerations (1g-Ng)
  
  Author: MORALES FLAUZÍN, GERARDO ABEL
  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 GEOTECHNICAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 16/02/2026
  Deposit END date: 27/02/2026
  Thesis director: PINYOL PUIGMARTI, NURIA MERCE | OLIVELLA PASTALLE, SEBASTIAN
  Thesis abstract: Flow liquefaction in contractive granular materials represents one of the most complex and hazardous failure mechanisms in geotechnical engineering, particularly in tailings dams. It is characterised by a sudden loss of shear strength under undrained conditions and by the rapid mobilisation of large volumes of material. Despite its practical relevance and the many documented failures, a detailed understanding of the internal processes governing the transition from sliding to flow remains limited, mainly due to the difficulty of obtaining experimental evidence during large deformations and post-failure stages.This doctoral thesis addresses the experimental study of post-failure behaviour, including strain localisation, retrogressive failure and flow liquefaction, through the development and application of non-invasive image-based measurement techniques. The main objective is to improve the observation, quantification and interpretation of deformation mechanisms and hydro-mechanical processes under large deformation conditions, and to apply these tools to the study of tailings failures.From a methodological perspective, the thesis refines the Eulerian–Lagrangian PIV-NP method. Its main limitations are systematically analysed, with particular emphasis on border-related errors, and specific correction strategies are proposed to enhance robustness and accuracy. These developments are validated using synthetic cases involving rigid motion and controlled deformation. In addition, PIV-NP is integrated with short-wave infrared (SWIR) imaging to allow non-intrusive measurement of surface moisture and degree of saturation in moving soils. This combined methodology, referred to as PIV-NP-Sr, is based on homographic transformations ensuring accurate spatial correspondence between visual and infrared images.The proposed techniques are first applied to a 1g test involving wetting-induced failure of a sand dam. Subsequently, a comprehensive experimental programme based on geotechnical centrifuge modelling is presented, conducted within the Geolab–SLIDAM project. This programme includes the characterisation of a mine tailing and seven small-scale centrifuge models tested under different acceleration levels, saturation conditions and failure activation mechanisms. Conventional instrumentation was deliberately minimised in favour of non-invasive imaging, allowing the full evolution of failure to be captured without disturbing material behaviour.The results enable detailed interpretation of shear band development, volumetric strain evolution and the progressive transition from sliding to flow-type behaviour. A novel observation is the occurrence of surface eruptions during post-failure stages, resembling miniature volcanoes. These events are shown to be preferentially located in zones of concentrated extensional strain. Based on the tracking of individual gas bubbles and their correlation with deformation fields, a preliminary interpretation involving gas entrapment, migration and pressurisation within the saturated granular medium is proposed.
  

DOCTORAL DEGREE IN NETWORK ENGINEERING

• KUMAR, SUNEEL: Leveraging Multi-Link Diversity for Reliable, Low-Latency Industrial Wi-Fi
  
  Author: KUMAR, SUNEEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN NETWORK ENGINEERING
  Department: Department of Network Engineering (ENTEL)
  Mode: Normal
  Deposit date: 20/02/2026
  Deposit END date: 05/03/2026
  Thesis director: GARCIA VILLEGAS, EDUARDO | CAMPS MUR, DANIEL
  Thesis abstract: Industrial Internet of Things (IIoT) applications, such as motion control, robotics, and functional safety, are increasingly deployed over Wi-Fi to gain flexibility, mobility, and improved operational adaptability compared to wired alternatives. However, current Wi-Fi deployments struggle to deliver the strict latency, reliability, and availability guarantees demanded by these safety and time-critical workloads. This thesis addresses how Wi-Fi can be made SLA-aware, i.e., capable of meeting per-flow Service Level Agreements (SLAs) expressed in terms of delay bounds for heterogeneous industrial traffic. To this end, it investigates the combination of Time-Sensitive Networking (TSN) features, specifically Frame Replication and Elimination for Reliability (FRER) and adaptive redundancy, with emerging Wi-Fi 7/8 features such as Multi-Link Operation (MLO) and Multi-AP Coordination (MAP-Co), aiming to provide predictable and efficient wireless connectivity in demanding industrial environments.First, the thesis focuses on SLA-driven scheduling for Wi-Fi 7 MLO. An SLA-MLO scheduler is proposed that adjusts per-flow link-selection probabilities based on measured per-link delay and SLA deviation, targeting per-flow SLA compliance rather than only minimizing average delay. This is extended to a cooperative variant, C-SLA-MLO, in which multiple MLO stations share SLA status information to prioritize flows that are at risk of not meeting their SLAs. Finally, a Graph-driven Min-Max Link Scheduling (GMMLS) framework is presented for dense multi-AP deployments with overlapping basic service sets, coordinating MLO link usage across APs to minimize maximum SLA stress in the network. NS-3-based simulation results in industrial-like scenarios show that the proposed mechanisms significantly improve SLA compliance (up to ≈90% reduction in SLA deviation).However, these MLO-based mechanisms require MAC-level support in Wi-Fi chipsets and are therefore tightly coupled to vendor implementations and future Wi-Fi 7/8 hardware. To complement this long-term direction with a solution that can be deployed immediately on existing Wi-Fi infrastructure, the second part of the thesis turns to TSN mechanisms operating above the MAC layer.The second part of the thesis evaluates TSN FRER for safety-critical applications such as Open Platform Communications Unified Architecture (OPC UA) Safety traffic over Wi-Fi. Using an emulation framework that couples real OPC UA Safety stacks with Wi-Fi models, the thesis shows that FRER over disjoint WLAN paths can drastically reduce safety-message round-trip times and raise communication availability from nearly zero in a single-WLAN configuration to above 90% under high load, at the expense of significant spectrum overhead. As a next step to address this overhead, an SLA-Aware Adaptive Redundancy (SAAR) scheduler is introduced, which dynamically activates FRER only when required to protect the application’s SLA, defined in terms of delay bounds and loss/SLA violation constraints. SAAR uses application-level feedback (e.g., OPC UA Safety round-trip times and availability) and channel utilization to decide when and where to replicate packets, preserving safety-grade reliability while cutting replication overhead by nearly two orders of magnitude compared to static FRER. Overall, this thesis charts a path from today’s best-effort wireless links to tomorrow’s SLA-guaranteed industrial Wi-Fi, unifying safety-critical redundancy, multi-link operation, and multi-AP coordination into a coherent toolkit for heterogeneous IIoT requirements.
  

DOCTORAL DEGREE IN PHOTONICS

• ABDULLAH, SAAD: Extreme nanophotonics architectures for the control of light at deep-subwavelength scales
  
  Author: ABDULLAH, SAAD
  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: 20/02/2026
  Deposit END date: 05/03/2026
  Thesis director: GARCÍA DE ABAJO, JAVIER | MKHITARYAN, VAHAGN
  Thesis abstract: Technological progress in the twenty first century increasingly relies on the ability to control light and electromagnetic fields across multiple spatial and spectral scales. As device dimensions shrink, strong confinement becomes essential, and plasmons, the collective oscillations of conduction electrons in metals, provide an efficient route to concentrate optical fields far below the diffraction limit and enhance light matter interactions. In this thesis, we engineer and study strongly confined optical fields in nanoengineered metallic systems, where plasmonic resonances play a central role in shaping both linear response and nonlinear emission.In the first part, we study scatterer assisted coupling of free space radiation into surface supported plasmonic modes, which cannot be efficiently excited by direct illumination due to strong momentum mismatch. We show that metallic nanodisks placed near a plasmon supporting interface can launch surface plasmons, with coupling governed by disk position and distance from the surface. By tuning the nanodisk size, we control its resonance wavelength and access a wide near infrared to infrared spectral region. We further investigate periodic nanodisk arrays, where lattice resonances reshape the scattering response and shift the optimal scatterer to substrate distance. By tuning the array geometry, we identify configurations that maximize coupling and determine optimal launching conditions. Results are supported by analytical modelling and numerical simulations.The second part focuses on ultrathin epitaxial crystalline silver films with thicknesses of only a few tens of monolayers, approaching the monolayer limit. These films provide strong intrinsic confinement and support high quality resonances over a broad spectral range spanning the visible and near infrared. We investigate patterned geometries including ribbons, nanotriangles, bow tie antennas, and rods, and demonstrate robust tunability with quality factors approaching, and for optimal configurations reaching, values on the order of 11. We compare pre patterned and post patterned fabrication approaches and show that suitable capping layers suppress dewetting and ensure long term stability. Despite their reduced thickness, we show that their optical response can be described using a modified Drude model with increased damping to account for confinement and fabrication related losses.Finally, we investigate the nonlinear optical response of these ultrathin metal systems with emphasis on second harmonic generation. In ultrathin crystalline films, strong interfacial symmetry breaking and vertical confinement enable a measurable nonlinear response. We show that decreasing film thickness enhances the second harmonic signal, and that resonant nanopatterning, particularly using stable capped silver nanoribbon arrays, yields broad tunability and strong plasmon enhanced near fields, producing conversion efficiencies a few orders of magnitude higher than planar films under resonant excitation.Overall, this work highlights plasmon enabled nanoengineering as a powerful route to control and concentrate light beyond the diffraction limit, enabling compact nonlinear photonic architectures, silicon compatible frequency conversion, and emerging quantum photonic technologies.
  
• CAGETTI, MARTA: Integrated Charge Sensing and Electromechanics in Suspended Carbon Nanotube Quantum Devices
  
  Author: CAGETTI, MARTA
  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: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: BACHTOLD, ADRIAN | FORSTNER, STEFAN
  Thesis abstract: In this thesis we present an ultrasensitive, fast and widely tunable charge detection architecture, suitable for the readout of both electronic states and mechanical motion. The platform is implemented in suspended carbon nanotube (CNT) devices. Our approach employs a radiofrequency (RF) readout scheme operating without impedance matching, thereby avoiding one of the main practical limitations of conventional reflectometry. The readout achieves charge sensitivities exceeding state of the art RF detection techniques, while relying on a comparatively simple measurement setup. The device is based on an integrated single nanotube platform, in which a system of gate defined quantum dots and a proximal quantum dot based charge sensor are hosted in the same suspended CNT and separated by a short metallic drain electrode. The drain is connected to an RLC resonator with a resonance frequency fRLC approximately 1.25 MHz and a bandwidth of 50 kHz, enabling RF readout of the charge sensor current at the circuit resonance. This geometry provides strong capacitive coupling while maintaining independent electrostatic control of the sensor operating point and of the target quantum dots. Using this platform, we achieve self charge sensitivities of order 10^-7 e/sqrt(Hz) and an exceptionally low single shot infidelity, 1 - F approximately 10^-15, for an integration time tau approximately 3.5 microseconds. Beyond the readout of electronic charge transitions in the target quantum dots, the same charge sensor provides highly sensitive access to the mechanical degrees of freedom of the suspended nanotube in the system region. Mechanical displacement is transduced into variations of the charge sensor quantum dot conductance, enabling measurements ranging from driven nonlinear dynamics to thermomechanical motion in the few phonon regime. Crucially, our platform allows operation in a regime where electromechanical backaction, which is typical of suspended carbon nanotubes hosting quantum dots, is strongly suppressed. This addresses one of the central challenges of CNT based nanomechanics: in single dot electromechanical architectures, achieving strong or ultrastrong coupling generally requires operation near charge degeneracy, where coupling to electronic reservoirs and stochastic tunneling lead to excessive dissipation, frequency noise and a pronounced reduction of the mechanical quality factor. Indeed, in previous experiments in the ultrastrong coupling regime, measurement backaction broadened the mechanical response to the point of obscuring access to the intrinsic mechanical properties. In contrast, in our devices we maintain high readout sensitivity without any observable degradation of the mechanical quality factor Q, enabling quantitative spectroscopy of the resonator while preserving its intrinsic mechanical properties. This capability to perform quantitative spectroscopy of a nanomechanical resonator coupled to a two level system in the few phonon regime constitutes a key requirement for advancing towards experiments in the quantum regime, where preserving intrinsic mechanical coherence is essential. The high degree of tunability of our platform enables precise control of charge occupation, tunnel couplings and electrostatic potentials, allowing systematic studies of electromechanical coupling from the single electron regime in a simple quantum dot to the double quantum dot configuration. We demonstrate ultrastrong electromechanical coupling, opening the door to future work on nonlinear nanomechanics, mechanical qubits, quantum delocalization and carbon nanotube based quantum simulation.
  

DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS

• CASTREJON COMAS, VICTOR: Electroresponsive hyaluronic acid-based hydrogel for wound healing with real-time monitoring of bacterial metabolism to prevent infection
  
  Author: CASTREJON COMAS, VICTOR
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: ALEMAN LLANSO, CARLOS ENRIQUE | PÉREZ MADRIGAL, MARIA DEL MAR
  Thesis abstract: Chronic skin wounds represent a major healthcare and socioeconomic challenge due to their high prevalence, prolonged healing times, and elevated risk of complications, particularly in conditions such as diabetic foot ulcers and vascular ulcers. In this context, the development of advanced wound dressings capable of promoting tissue regeneration while simultaneously monitoring the wound status constitutes a critical clinical need. Hyaluronic acid (HA), as a natural component of the skin extracellular matrix, stands out as an ideal biomimetic platform for the design of hydrogels intended for cutaneous wound healing, owing to its excellent biocompatibility, high water-retention capacity, and regulatory role in the wound-healing process.In this thesis, HA-based hydrogels crosslinked via click chemistry are developed using a three-arm polyethylene glycol (PEG) as a crosslinking agent, enabling the formation of well-defined three-dimensional networks under mild and biocompatible conditions. These hydrogels (clickHA) are designed to maintain a favorable moist environment, absorb wound exudate, and promote autolytic debridement, thereby contributing to the removal of necrotic tissue and to the reduction of bacterial burden. The trifunctional architecture of PEG allows precise control over the crosslinking density and, consequently, over the mechanical and structural properties of the hydrogel, ensuring adequate mechanical compliance with skin tissue and ease of clinical handling.The incorporation of a semi-interpenetrating network of a conducting polymer, poly[3,4-ethylenedioxythiophene-2-yl methanol] (PEDOT-MeOH), obtained by chemical oxidative polymerization of EDOT-MeOH monomers infiltrated into the clickHA matrix, endows the system with electro-responsive properties without compromising its structural integrity or biocompatibility. The influence of the infiltrated monomer concentration is systematically analyzed, demonstrating a progressive increase in electroactivity and the onset of electronic percolation at an EDOT-MeOH concentration of 0.05 M, above which effective conductive connectivity and reproducible electrochemical responses are achieved.Molecular dynamics simulations provide a mechanistic understanding of the internal organization of the system, revealing that EDOT-MeOH monomers aggregate into domains stabilized by π–π interactions that act as nucleation sites for polymerization, resulting in a homogeneous distribution of the conducting polymer within the HA matrix without altering its global structure. Finally, the electrochemical stability of the system and its application as an electrochemical sensor for the detection of NADH, a relevant biomarker of bacterial infection, are evaluated. ClickHA/PEDOT-MeOH hydrogels exhibit stable and selective electrochemical responses in the presence of interferents, both in model solutions and in bacterial culture media, enabling the early detection of infections. Overall, this thesis validates the clickHA/PEDOT-MeOH system as a robust multifunctional platform that integrates skin regeneration and electrochemical diagnostics, with high potential for translation into advanced smart wound dressings.
  
• COLOMBI, SAMUELE: Soft and Conductive Material Architectures for Flexible Electronics: from Hydrogels to Nanomembranes
  
  Author: COLOMBI, SAMUELE
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 20/02/2026
  Deposit END date: 05/03/2026
  Thesis director: ALEMAN LLANSO, CARLOS ENRIQUE | GARCÍA TORRES, JOSÉ MANUEL
  Thesis abstract: Soft materials are key enablers of the next generation of flexible and multifunctional systems for applications spanning biomedicine, energy, and environmental technologies. This thesis focuses on the design, fabrication, and implementation of (nano)engineered polymeric materials with tailored properties for use in soft electronic devices, drug delivery systems, solar-driven water evaporators, and functional scaffolds for tissue engineering. To this end, three main families of materials were developed: composite alginate (Alg)-based hydrogels, composite gelatin methacrylate (GelMA)-based hydrogels, and polylactic acid (PLA)-based nanomembranes. For each material platform, structure–property–function relationships were systematically investigated across distinct biotechnological scenarios to achieve enhanced performance. Alg-based composite hydrogels were engineered as versatile, water-rich platforms through the incorporation of functional nanomaterials (such as PLA nanofibers and gold nanoparticles), enzymes, and conducting polymers (e.g., PEDOT:PSS). These systems were designed to exhibit improved mechanical robustness, controlled porosity, and tunable physicochemical and functional properties while maintaining their intrinsic biocompatibility. By modulating composition, the Alg-based hydrogels were successfully applied as drug delivery matrices for the sustained release of lactate, as soft electronic platforms for temperature and H₂O₂ sensing, and as flexible energy-storage devices. In addition, the introduction of secondary covalent crosslinking was explored as a strategy to enhance operational stability in H₂O₂ biosensing and solar-driven steam generation applications. In parallel, bilayered PANI–PLA nanomembranes incorporating aligned gold nanopillars were fabricated as free-standing, lightweight, conformable, and mechanically stable platforms for skin electronics. These nanomembranes enabled simultaneous pH and non-enzymatic NADH sensing, demonstrating their suitability for monitoring skin physiology and infection-related biomarkers. Finally, GelMA hydrogels were nanoengineered with magnetoelectric and/or graphene-based nanomaterials to develop bioactive scaffolds for cardiac tissue regeneration. The incorporation of these nanomaterials allowed precise tuning of the mechanical, electrical, magnetic, and biological properties of the hydrogels. Their ability to support cell adhesion and proliferation, combined with their capacity to sense cellular activity, highlights their potential as multifunctional scaffolds for engineered tissues and bioelectronic interfaces. Overall, this thesis demonstrates that rational materials design across multiple length scales enables the development of soft matter systems with tailored and synergistic functionalities, paving the way toward next-generation flexible electronic devices, controlled therapeutic platforms, and sustainable water-treatment technologies.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• GHAFOURI JESHVAGHANI, NAVIDEH: Reinforcement Learning-Based Energy Efficient Network Orchestration, Slicing, and Resource Management for 6G Intelligent Networks
  
  Author: GHAFOURI JESHVAGHANI, NAVIDEH
  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 SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 16/02/2026
  Deposit END date: 27/02/2026
  Thesis director: VARDAKAS, JOHN | VERIKOUKIS, CHRISTOS
  Thesis abstract: This dissertation responds to the emerging challenges of AI-driven 6G network management, aiming to devise smart, adaptive strategies that optimize network performance while reducing complexity and energy consumption. Through the lens of Reinforcement Learning, the study lays the foundation for self-organizing, cost-efficient, and scalable wireless communication systems that can meet the diverse demands of next-generation applications.
  

DOCTORAL DEGREE IN SUSTAINABILITY

• RAMIREZ RODRIGUEZ, MARIA SARAY: Fisheries Sustainability: Environmental, Economic, and Social Vulnerabilities, Addressing the Problem Through Food Waste
  
  Author: RAMIREZ RODRIGUEZ, MARIA SARAY
  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: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: REIG PUIG, MARIA LOURDES | FERNÁNDEZ GUERRERO, DAVID
  Thesis abstract: Food security and a resilient food system are aims to ensure the future of humanity in a scenario of several threats, such as climate change, the decreasing trend in available resources, the emergence of virulent diseases, global conflicts affecting supply chains, etc. Providing solutions to these issues is so vital that within the Sustainable Development Goals (SDG), sustainable production and consumption is a stated goal (nº 12), and the reduction of Food Losses and Waste (FLW) has become one of the tools for achieving this goal (nº12.3). . This study aims to contribute in FLW reduction for the fish sector, decreasing its negative impacts and increasing the sustainability of the fish sector activity. Moreover, the goal of the thesis is also to reduce fish sector vulnerability, by identifying weak points and possible areas of improvements with a focus on economic and social sustainability, but without forgetting an environmental approach.The methodology combines qualitative and quantitative methods. Public databases were used but also own data was generated by including fish sector stakeholders in the study’s development by surveys, interviews and participatory dynamics. Spain was chosen for the geographical scope due to several factors, such as its high volume of catches, consumption and international trade in fishery and aquaculture products, both in the European and global contextThe thesis is structured in the following way. Chapter 1 was developed as a diagnosis of FLW in the fisheries sector. FLW were quantified and causes, and prevention measures were detected through the use of a standardized methodology. Furthermore, two species were selected to represent Spanish fish sector based on consumption and catches. Anchovy (Engraulis encrasicolus) was chosen to represent oily fish and Hake (Merluccius merluccius) for representing lean fish. As a result, we provided FLW estimations using standardized methodologies, which allows for comparison with future research. Furthermore, our contribution enables the formulation of mitigation and prevention actions. After the diagnosis stage, interventions were designed and tested, trying to approach the problems identified in the diagnosis stage.Chapter 2 tries to improve the resilience of the fisheries sector in Catalonia by developing a market intervention for the expansion of target species. Priority was given to local species, favored by climate change, and which are currently being wasted both nutritionally and economically, due to their low commercial interest. The selected species was Sardinella aurita, which was also validated by local fishermen as a good candidate for the market intervention. The market intervention contributes to increase the economic value of catches by offering alternative products made from low-value species. Moreover, it approached consumers toward local species by adding value to proximity and offering more convenient consumption methods for unskilled consumers. On the other hand, in Chapter 3 another mitigation action was proposed in order to reduce FLW and the economic devaluation of products due to consumer concerns about food safety and aesthetic reasons. As was detected during the diagnostic stage, Anisakis negatively affects the fish sector. It is necessary to inform consumers correctly by developing communication tools that focus on risk avoidance and the social and health benefits of consuming fish. This chapter proposed and tested communications to decrease the perception of food risk towards Anisakis and increase fish consumption.Finally, recommendations have been formulated for each stage of the fish FSC to reduce FLW and increase economic profit, as well as to propose strategies to promote sector’s resilience. These recommendations include strong collaboration and better communication between stages and withpolicymakers, as well as promoting fish culture to increase consumption and reduce food safety concerns.
  

DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE

• ZIAIEBIGDELI, MOHAMMADAMIN: Computing quality in housing: examining the evolution and systematization in computational design in architectural plan design and analysis
  
  Author: ZIAIEBIGDELI, MOHAMMADAMIN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE
  Department: Department of History and Theory of Architecture and Communication Techniques (THATC)
  Mode: Normal
  Deposit date: 19/02/2026
  Deposit END date: 04/03/2026
  Thesis director: ROSSELLO NICOLAU, MARÍA ISABEL | HERNÁNDEZ FALAGÁN, DAVID
  Thesis abstract: This research undertakes a meticulous exploration into the systematization and analysis of architectural plans, tracing their evolution through the lens of computational design thinking from the 20th century to the present. The specific context is living spaces, where the quality and functionality are intrinsically tied to the systematic extraction and application of design parameters. This dissertation explores the evolution of computational thinking in architecture by bridging the theoretical paradigms introduced by pioneers Alexander Klein, Cedric Price, Christopher Alexander, and Nicholas Negroponte with contemporary design practices. Through an inductive methodology, three case studies are analyzed to demonstrate how computational tools and technologies enhance spatial quality, adaptability, and user engagement. Each case study corresponds to the key indicators established by these pioneers—spatial geometry, temporal adaptability, participatory design, and digital computation—illustrating their enduring influence on modern architecture. By mapping these foundational ideas to advanced practices such as parametric modeling, smart systems, and digital fabrication, this research highlights the practical relevance of these paradigms in addressing contemporary architectural challenges and shaping innovative, human-centered spaces.The journey begins with Alexander Klein’s Existenzminimum concept in the 1920s-1930s. His scientific approach to design emphasized space optimization and the systematization of plans using both qualitative and quantitative parameters, laying the groundwork for future computational design methods. As we move into the 1960s, we encounter Christopher Alexander’s ‘Pattern Language.’ Alexander brought a new perspective to plan systematization, employing rules and systems to extract design parameters and analyze architectural planning. His methodologies form a vital cornerstone of computational design as we know it today.In the 1970s, Cedric Price introduced a more dynamic approach. His vision of architecture, as exemplified in the 24 hour living toy project, accommodated changing user needs and behaviors. His focus on user-centric parameters marked a shift in computational design thinking towards adaptability and flexibility. Presently, computational design thinking in the context of living spaces aims to synthesize the lessons from these key figures, emphasizing the analysis and extraction of design parameters. These parameters, enriched by the advancements in technology and the increasingly user-centric approach, are utilized to optimize and improve the quality of living spaces This research’s trajectory, from past methodologies to contemporary practices, provides an in-depth understanding of how computational thinking and plan analysis have evolved. By extracting and studying the diverse parameters used across time, this research aims to enrich the computational design discourse and advance the design of living spaces.