Theses authorised for defence

DOCTORAL DEGREE IN APPLIED MATHEMATICS

BOSCH PADRÓS, MIQUEL: Optogenetic control of force transmission in puripotent epithelia
Author: BOSCH PADRÓS, MIQUEL
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: 16/12/2025
Reading date: 27/01/2026
Reading time: 15:00
Reading place: Sala d'Actes de l'FME, Edifici U, Campus SudEnllaç MEET: meet.google.com/wda-kfee-saf
Thesis director: ARROYO BALAGUER, MARINO | TREPAT GUIXER, XAVIER
Thesis abstract: Development requires a combination of three phenomena: increasing the number of cells, specifying their fates and undergoing morphogenesis, which means acquiring the correct shapes. Apical constriction is an important driving mechanism of morphogenesis, occurring within a cell but bridging with tissular scale to acquire and maintain shape. Apical constriction is well studied at the cellular level and conserved through the animal kingdom, but the forces that need to be generated and transmitted through the tissue in the process have never been measured and described. To fill this gap, we used a novel optogenetic tool to induce apical constriction in human pluripotent stem cells, combined with traction force microscopy to measure the mechanical forces involved in the process. With this techniques, we discovered that constriction creates a consistent but small signature in traction maps, compatible with apical contractility increase and volume conservation. In addition, we subjected regions of a monolayer to apical constriction and revealed that the cellular displacement field obeys a screened Poisson equation in two dimensions, which implies the existence of a lengthscale with a rheological origin and allows to obtain the Green's function of the tissue. While deformations can be tailored in space and time, we also find that jamming transitions cannot be engineered through apical contractility, which exposes a strong unjammed nature of this pluripotent epithelium. These insights reveal key rheological aspects of human pluripotent stem cells at timescales relevant for morphogenesis, inaccessible through other techniques. Because this cells are used around the globe to derive organoids and embryo models but are highly understudied mechanically, this work establishes a key building block for future works that require shape or force control in stem cell-derived tissues.

DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE

FERRANDO MONSONÍS, JAVIER: Interpretability in Natural Language Processing and Machine Translation
Author: FERRANDO MONSONÍS, JAVIER
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 ARTIFICIAL INTELLIGENCE
Department: Department of Computer Science (CS)
Mode: Normal
Deposit date: 13/11/2025
Reading date: 13/02/2026
Reading time: 12:00
Reading place: Sala MERIT D5010, Edifici D5, Campus Nord UPC, Barcelona
Thesis director: RUIZ COSTA-JUSSA, MARTA
Thesis abstract: This thesis presents a set of methods and analyses designed to improve our understanding of the internal mechanisms of Transformer-based models in natural language processing and machine translation.This work first investigates the role of attention weights in encoder-decoder Transformers, showing that while they do not provide accurate word alignments, they nonetheless help explain model predictions and contribute to a deeper understanding of translation quality.A central contribution of the dissertation is the development of ALTI and its extensions, which offer a new approach to input attribution. These methods challenge prior assumptions about the explanatory power of attention mechanisms and reveal how information propagates between encoder and decoder components. In doing so, they also shed light on sources of hallucinations in translation systems.Further, the thesis introduces techniques to attribute predictions to individual components and positions, enabling contrastive explanations of linguistic behavior. These explanations clarify how language models represent and solve different linguistic phenomena.The dissertation also proposes a methodology for tracking information flow during inference, offering insight into how various components contribute to model predictions. This allows for the identification of domain-specialized components and a better understanding of how representations are transformed across layers.Lastly, the analysis of cross-lingual circuit similarities reveals shared structural patterns in how models handle different languages. These findings point to potential universal mechanisms in language models.Collectively, this thesis advances the interpretability of Transformer models by providing tools and frameworks for probing, attributing, and understanding the behavior of complex NLP systems.
GONZÁLEZ GUTIÉRREZ, CÉSAR: Analyzing and Leveraging the Structure of Pre-trained Embeddings
Author: GONZÁLEZ GUTIÉRREZ, CÉSAR
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 ARTIFICIAL INTELLIGENCE
Department: Department of Computer Science (CS)
Mode: Normal
Deposit date: 27/11/2025
Reading date: 10/02/2026
Reading time: 13:00
Reading place: Sala Juntas, Edificio B6, Campus Nord.
Thesis director: QUATTONI, ARIADNA JULIETA
Thesis abstract: Developing models with limited annotation budgets (few-shot learning) is of great importance due to the high costs associated with data annotation.Recent advances in text classification have demonstrated that representations derived from pre-trained language models play a crucial role, especially in few-shot learning settings. These new advancements raise two natural questions:1) What properties of pre-trained representations can explain their effectiveness in few-shot learning?, and2) Can we leverage these properties to further enhance performance under limited annotation conditions? In the first part of this work, we address the first question and show that the effectiveness of pre-trained representations in few-shot scenarios can be explained by the degree of alignment between supervised task labels and the hierarchical structure of the pre-trained embedding space. In the second part, we propose a label propagation method designed to exploit this alignment, leading to improved performance in few-shot classification tasks.
ZHAO, RUI: Improving SAT and Pseudo-Boolean Solving Technology
Author: ZHAO, RUI
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 ARTIFICIAL INTELLIGENCE
Department: Department of Computer Science (CS)
Mode: Normal
Deposit date: 15/12/2025
Reading date: 05/02/2026
Reading time: 11:30
Reading place: Sales d'Actes de la FIB, Campus Nord UPC, Barcelona
Thesis director: OLIVERAS LLUNELL, ALBERT
Thesis abstract: The Boolean satisfiability (SAT) problem has seen remarkable progress, from early DPLL and resolution methods to the modern Conflict-Driven Clause Learning (CDCL) paradigm. Nevertheless, significant challenges remain. Theoretically "simple" yet structurally complex problems, such as the pigeonhole principle, continue to challenge state-of-the-art SAT solvers, revealing inherent limitations in core algorithms like CDCL. Although CDCL-based Pseudo-Boolean (PB) solving extends SAT with 0-1 linear arithmetic constraints—enabling more natural modeling and offering exponential speedups in theory—its added complexity introduces computational bottlenecks in propagation, conflict analysis, and optimization. These challenges underscore the need for deeper algorithmic insights and innovative techniques to advance SAT and PB solver performance. This thesis addresses these gaps by advancing the core algorithms and implementation techniques underlying modern SAT and PB solvers. It is structured in two parts:• Part I: SAT Solving – We analyze the limitations of CDCL through both theoretical and practical lenses. The contributions are: (i) new insights from analyzing multiple conflicts, aimed at identifying opportunities to enhance CDCL or understanding the fundamental reasons for the failure of this particular idea; (ii) an empirical study on the equivalence between CDCL solvers and resolution, examining how solvers reproduce unsatisfiability proofs and how decision heuristics and resolution proofs interact.• Part II: Pseudo-Boolean Solving – We introduce optimizations in unit propagation and conflict analysis. Propagation is accelerated through a carefully engineered hybrid technique, while enhanced conflict analysis produces some stronger constraints for more effective search pruning.Beyond performance gains, this work offers profound insights into Boolean constraint reasoning, bridging theoretical gaps and opening new research avenues in SAT, PB, and beyond.

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

ARANGO RESTREPO, JUAN PABLO: Recent Engineering Advances for OSL-QIB Nonlinear Systems
Author: ARANGO RESTREPO, JUAN PABLO
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: Change of supervisor
Deposit date: 24/12/2025
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: PUIG CAYUELA, VICENÇ | DUVIELLA, ERIC | SEGOVIA CASTILLO, PABLO
Thesis abstract: This thesis presents a comprehensive framework for the state estimation, control, and observer-based control of nonlinear systems described by One-Sided Lipschitz and Quadratically Inner Bounded (OSL-QIB) properties. The main objective is to exploit the reduced conservatism and modeling flexibility of the OSL-QIB representation to design robust, and computationally efficient algorithms applicable to practical nonlinear processes affected by uncertainties, noise, and unknown inputs.The first part of the work focuses on observer design. Several estimation schemes are developed, including Luenberger-like observers and Unknown Input Observers (UIO) for OSL-QIB systems, extended later to the Linear Parameter-Varying (LPV) OSL-QIB framework. These LPV observers preserve the OSL-QIB structure while explicitly accounting for parameter variations, leading to improved convergence and robustness over conventional formulations. All observer designs are derived through LMI-based synthesis conditions, guaranteeing exponential stability and robustness to noise and modeling errors. Their effectiveness is validated through nonlinear benchmarks such as chemical reactors, flexible robotic systems, and open-channel irrigation networks.The second major contribution addresses the control design for OSL-QIB and LPV OSL-QIB systems. Two complementary strategies are proposed: a state-feedback controller with integral action for accurate reference tracking and disturbance rejection, and a Nonlinear Model Predictive Control (NMPC) formulation entirely expressed as LMI constraints. This LMI-based NMPC introduces Lyapunov stability inequalities into the optimization problem, ensuring convexity, guaranteed feasibility, and improved transient performance compared to standard NMPC approaches.Finally, the thesis integrates the estimation and control frameworks into observer-based control (OBC) structures. Two unified schemes are proposed: an OBC for noisy OSL-QIB systems and an Unknown Input Observer-Based Predictive Controller (UIOBPC) for LPV OSL-QIB systems. Both rely on a separation principle ensuring joint stability and robustness. Simulation results on the Corning Channel benchmark confirm the effectiveness of the proposed methods in achieving precise tracking, strong disturbance rejection, and resilience to unknown inputs.Overall, the thesis establishes a unified, convex, and practically implementable framework for the estimation and control of nonlinear and LPV OSL-QIB systems, narowing the gap between theoretical developments with engineering applications.
CHEN, MINGRUI: State of Charge Estimation for Metal Hydride Storage Tanks
Author: CHEN, MINGRUI
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: 17/12/2025
Reading date: 27/01/2026
Reading time: 16:00
Reading place: Aula 28.8 de l'Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB), Edifici PI (Pavelló I). Av. Diagonal, 647, 08028 Barcelona
Thesis director: COSTA CASTELLO, RAMON | NA, JING
Thesis abstract: The growing global energy demand and the urgent need for sustainability have highlighted hydrogen as a clean energy carrier. Among various storage methods, metal hydride (MH) tanks are promising due to their high volumetric density, safety, and reversible absorption/desorption properties. However, complex thermodynamics, kinetic hysteresis, and unobservable internal states make accurate real-time estimation of the state of charge (SOC) challenging. Reliable SOC estimation is essential for efficient operation, safety, and integration with renewable systems.This thesis applies nonlinear observer theory to estimate the SOC of MH tanks. A comprehensive physical model is first developed based on mass and energy balances and reformulated into 3D and reduced 2D state-space models, including a modified version accounting for pipeline effects. Parameter identifiability and sensitivity analyses are performed to ensure model reliability, followed by parameter calibration using experimental data and optimization techniques such as particle swarm and multi-objective optimization.Several nonlinear observers are then designed for real-time SOC estimation. These include a Luenberger-like observer, a neural network-based inversion estimator for reduced computation, and switched nonlinear observers addressing the mode-dependent behavior of MH tanks. Stability and convergence are guaranteed through differential detectability and contraction theory.Numerical simulations and experiments on commercial MH tanks demonstrate that the proposed models and observers provide accurate, robust, and computationally efficient SOC estimation, offering a practical foundation for intelligent hydrogen storage management.
CHICO VILLEGAS, JOSÉ PASCUAL: Técnicas Avanzadas de Control Aplicadas a Convertidores de Potencia
Author: CHICO VILLEGAS, JOSÉ PASCUAL
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: 19/12/2025
Reading date: 02/02/2026
Reading time: 10:00
Reading place: E.P.S.E. Aula Ferroviària Av. de Víctor Balaguer, 1, Vilanova i la Geltrú
Thesis director: GUZMAN SOLA, RAMON | GARCIA DE VICUÑA MUÑOZ DE LA NAVA, JOSE LUIS
Thesis abstract: This doctoral thesis focuses on the control of two-level three-phase power converters and is structured around two main lines of research, with a third currently under development. First, a novel control technique is proposed, based on a nonlinear transformation combined with first-order sliding mode control. This transformation enables exact decoupling between control loops and extends the converter’s control range, improving dynamic performance and robustness against disturbances when compared to existing sliding mode control techniques implemented in the abc reference frame. The proposed strategy has been successfully applied to three representative two-level three-phase converters: a unity power factor rectifier, an active power filter, and an inverter. Second, a continuous model predictive control approach is developed for a three-phase inverter with an LCL output filter. In this case, constraints are introduced directly into the cost function to limit the injected current, thus ensuring compliance with the physical limitations of the system while maintaining dynamic behavior in accordance with the design specifications. Finally, a third line of research focuses on the design of a controller for a unity power factor rectifier using a single-loop control structure that avoids the conventional hierarchical approach. This proposal employs a linearized model and capacitor current feedback from the output filter to improve control performance. This allows for a simpler implementation without compromising system stability or accuracy. The control strategies presented in this thesis have been validated through simulation, and some have also been experimentally tested, demonstrating their applicability in real-world scenarios.

DOCTORAL DEGREE IN BUSINESS ADMINISTRATION AND MANAGEMENT

TORRES SOTO, JOSE LUIS: Talent Retention practices in Spanish IT SMEs
Author: TORRES SOTO, JOSE LUIS
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 BUSINESS ADMINISTRATION AND MANAGEMENT
Department: Department of Management (OE)
Mode: Normal
Deposit date: 19/12/2025
Reading date: 10/02/2026
Reading time: 11:00
Reading place: Sala de conferencias del edificio TR5 (Terrassa)
Thesis director: GALLARDO GALLARDO, EVA | FERNANDEZ ALARCON, VICENÇ
Thesis abstract: Context: Hiring and retaining the best employees is one of the most important business activities for keeping a sustainable advantage for companies over time. Besides, these business activities are more crucial in knowledge-intensive industries, such as IT, where the employee’s knowledge, skills and attitudes define the company's real ability to adapt and compete in the existing markets. This Ph.D. thesis explores the existing Talent Retention challenges faced by IT SMEs in Spain, proposing a framework to help companies in the industry to cope with this relevant challenge.Purpose: to help in the advancement of the understanding of the Talent Management (TM) field by identifying Talent Retention practices adopted by a cohort of Small and Medium-sized Enterprises (SMEs) in the Information Technology (IT) industry SMEs in Spain. Challenges in TM are higher for companies of this kind as they face higher constraints than multinational enterprises (MNEs), and their success is highly tied to their people.Method: the research uses an inductive approach based on semi-structured interviews. A list of companies was obtained from a business directory by selecting those candidates that fall into the category of SMEs, their activity is linked to software development and are located in the Barcelona area. After curating the list, representatives were contacted, and we held semi-structured interviews with them until we reached sample saturation. Data was then coded and analysed.Results: we identified a set of practices that could be translated into a framework of four blocks that may help IT companies set a Talent Retention agenda and help them remain competitive in the current talent competition scenario.Conclusions / Implications: the proposed framework aims to help companies in this competitive industry to perform better Talent Retention decisions thus help them to survive and grow in a very competitive environment.Originality: this dissertation contributes to the call for more exploratory studies in HRM and TM in SMEs in the EU contexts whilst proposing a framework for practitioners to cope with Talent Retention challenges.

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.
TARIN TOMAS, JUAN CARLOS: Optimización de dispositivos flexoeléctricos.
Author: TARIN TOMAS, JUAN CARLOS
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: 29/10/2025
Reading date: 30/01/2026
Reading time: 14:30
Reading place: UPC Campus North ETSECCPB C/ Jordi Girona 1-3 Building C1, Room 002 Barcelona
Thesis director: ARIAS VICENTE, IRENE | GRECO, FRANCESCO
Thesis abstract: This thesis develops a strategy to study the optimization on flexoelectric devices. There are nowadays many electromechanical devices , sensors, actuators and energy harvesters, that rely on the basis of the well-known piezoelectric effect, but not all materials exhibit this effect. The most widely used piezoelectric materials show limitations in terms of fracture toughness, toxicity, biocompatibility and temperature range of operation. A novel alternative is provided by flexoelectricity, which, unlike piezoelectricity, appears in all dielectric materials. Flexoelectricity is a size dependent electromechanical coupling which manifest itself at submicron scales and relies on the generation of field gradients inside the material. It has been recently shown, that the flexoelectric response to field gradients in the materials can be conveniently accumulated to produce a macroscopic effective piezoelectric-like response by material architecture. Through the suitable geometry of a repeating unit, piezoelectric metamaterials can be conceived to produce a net electromechanical response even when built from non-piezoelectric base materials, and thus devoid of some of the above mentioned limitations. The design of such piezoelectric metamaterials exploiting flexoelectricity poses numerous challenges both theoretical and computational. Flexoelectricity is a gradient-mediated property, and thus requires additional physical and engineering intuition beyond the homogeneous setups of piezoelectricity. The governing equations of flexoelectricity are a coupled system of fourth-order PDEs, which require solution methods beyond standard finite elements providing the required continuity. In recent work, these issues have been addressed in detail, identifying the main design concepts for piezoelectric metamaterials and developing suitable solution methods. In the present thesis, we focus on the systematic rational design of piezoelectric metamaterials and devices exploiting the flexoelectric effect. A useful tool towards this goal is topology and shape optimization with multiple and possibly conflicting objectives. An important challenge is the high-computational cost of solving flexoelectric boundary value problems in general geometries. We will thus aim at devising efficient optimization strategies to reduce the computational cost, introducing machine learning techniques to alleviate the need for detailed and accurate simulations for every design in the optimization process.

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

ALCÓN DOGANOC, MIGUEL: Verification and Validation Solutions for the Safety Compliance of Autonomous Driving Frameworks Performance Aspects
Author: ALCÓN DOGANOC, MIGUEL
Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
Department: Department of Computer Architecture (DAC)
Mode: Normal
Deposit date: 01/12/2025
Reading date: 28/01/2026
Reading time: 11:00
Reading place: C6-E101
Thesis director: ABELLA FERRER, JAIME | MEZZETTI, ENRICO
Thesis abstract: Autonomous Driving (AD) has rapidly evolved from a research concept into an industrial reality. The increasing computational demands of autonomous vehicles have motivated the use of high-performance Multi-Processor Systems-on-Chip (MPSoCs), which offer both performance and energy efficiency. However, ensuring the safety compliance of such complex systems remains a major challenge. The software frameworks used to implement AD functionalities—typically integrating Artificial Intelligence (AI) algorithms—are not designed following a safety-driven development processes, and their non-deterministic behavior conflicts with the strict determinism required by safety standards. This thesis addresses these challenges by developing Verification and Validation (V&V) solutions that improve the safety compliance of AD frameworks, with a particular focus on performance-related aspects.The thesis begins by analyzing the main sources of non-determinism in AD systems across three layers: algorithmic, software architectural, and hardware platform. While variability exists in all layers, the software architecture layer is identified as a key contributor to the overall unpredictability. It not only introduces its own sources of variability but also amplifies those inherited from the other layers. This makes software architecture an effective focal point to improve system determinism and safety assurance.At the foundational level, the thesis addresses the challenge of unit testing within already-integrated AD frameworks, using the open-source Apollo AD framework as a case study. Due to tight coupling and data dependencies among its modules, Apollo does not easily support independent module validation. To enable proper verification of software units, the thesis proposes a systematic methodology to isolate, modify, and reconfigure Apollo modules into standalone, testable units, thus reintroducing unit-level testing capabilities into a complex, AI-based AD framework.The work advances toward system-level safety assurance through the development of dynamic and execution views of Apollo. Dynamic views describe the interactions among software components, linking safety requirements with their implementation and validation tests. However, these views alone fail to capture the concurrent behavior and execution parallelism of the system, which are crucial for verifying performance-related safety requirements. To fill this gap, the thesis introduces execution views, which complements dynamic views by integrating runtime information gathered from execution tracing on MPSoC platforms. Execution views enhance the observability of resource usage, timing behavior, and concurrency, allowing both improved testing and optimized hardware utilization—key aspects for reducing cost and ensuring safety.Finally, the thesis addresses the timing behavior and variability across software components. It identifies, formalizes, and applies a comprehensive set of timing-related metrics capable of capturing inter-module interactions and end-to-end latency properties in AD applications. Traditional timing metrics, such as worst-case execution and response times, fail to capture the interdependencies between components in systems like Apollo. By adopting complementary metrics such as maximum reaction time and maximum time displacement, the proposed approach provides deeper insights into timing dependencies, enabling early detection of timing anomalies and improving validation confidence.Overall, this thesis provides a set of methodologies and tools to improve the V&V of AD software from a safety-performance perspective. The proposed contributions bridge the gap between high-performance AI-based software and the stringent determinism required by safety standards. These advances support the systematic assurance of safety in AD frameworks, ultimately contributing to the reliable and certifiable deployment of autonomous vehicles on high-performance embedded platforms.
ALLKA, XHENSILDA: Enhancing Data Quality in IoT Monitoring Sensor Networks
Author: ALLKA, XHENSILDA
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: 31/10/2025
Reading date: 30/01/2026
Reading time: 11:00
Reading place: Sala C6-E101
Thesis director: BARCELÓ ORDINAS, JOSE MARIA | GARCÍA VIDAL, JORGE
Thesis abstract: In recent years, technological development and an increased number of cars among other factors, have influenced air pollution levels. This increase in levels has also increased the need to monitor them, as they are directly related to human health and the economy. To monitor air pollution, the government has deployed precise monitoring stations, which are expensive to deploy and maintain. Due to their cost, they are not widely distributed. However, since air pollution can change over short distances, the distribution of these stations can be insufficient. Recently, a solution has emerged: the use of low-cost sensors (LCSs), which provide broader coverage at a much lower cost. However, these LCSs have one drawback: the quality of the data they provide is poor.Current research in this field has employed machine learning (ML) models to calibrate these LCSs, thereby enhancing the quality of the data they provide. In an Internet of Things (IoT) monitoring network, the quality of data is closely associated with decision-making processes. This thesis focuses on enhancing the data quality provided by the LCSs from two perspectives: improving calibration performance and detecting anomalies and outliers. The objective of both of these perspectives is to ensure data accuracy and reliability.The first part of the thesis focuses on the improvement of the calibrated data provided by the LCSs and the detection of the concept drift and the update of the parameters of the current calibration model such that it adapts to the new conditions. We are enhancing the quality of the calibrated data by implementing a model pattern-based approach. Our proposed methods, Temporal Pattern Based Denoising (TPB-D) and Temporal Pattern Based Calibration (TPB-C), improve the quality of the calibrated data. Given that environmental conditions are subject to change over time, it is essential to update the parameters of the calibration model. We proposed Window-based Uncertainty Drift Detection and Recalibration (W-UDDR), a system capable of detecting the presence of concept drift (i.e., environmental changes).The second part of the thesis focuses on the reliability of the data. Sensors, regardless of their cost, are often prone to irregularities such as outliers, anomalies, or drift, which can be caused by various factors. It is critical to identify these irregularities, as the data will be incorporated into the training of the model related to other tasks. In this thesis, three distinct scenarios were examined. The first one is related to the detection of outliers in the edge. In this case, we proposed the Edge Streaming Outlier Detection (ESOD) framework. ESOD is a simple and lightweight framework that can identify outliers in the edge with a limited amount of memory. The system offers two approaches: real-time and near real-time. The near real-time approach involves minor delays in decision-making. The second approach is related to the detection of more complex irregularities, such as anomalies in a given sensor. This scenario is distinct from the first one in that it offers offline anomaly detection capabilities. We proposed spatiotemporal correlation recurrent autoencoder anomaly detection (STC-RAAD), which demonstrated satisfactory performance in detecting anomalies in a given sensor. It is worth noting that the third scenario pertains to the detection and localization of anomalies in a network of sensors. This is of particular relevance in scenarios where the identification and precise location of the source of an anomaly are crucial. We hereby propose a pattern-based attention recurrent autoencoder anomaly detection (PARAAD) method. This method is designed to detect and localize anomalies in sensors.
BARRERA HERRERA, JAVIER ENRIQUE: Improving Time Predictability and Code Coverage of Embedded GPUs for Real-Time Systems
Author: BARRERA HERRERA, JAVIER ENRIQUE
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: 07/11/2025
Reading date: 23/01/2026
Reading time: 11:00
Reading place: C6-E101
Thesis director: CAZORLA ALMEIDA, FRANCISCO JAVIER | KOSMIDIS, LEONIDAS
Thesis abstract: This dissertation addresses challenges that the adoption of GPUs in Critical Embedded Systems (CES) faces, namely, Time Predictability and Code Coverage. Different domains that deploy CES are constantly adding Artificial Intelligence (AI)-based features, such as autonomous driving, that demand high performance levels. Multi-Processors Sytem-on-Chip (MPSoCs) are widely used to provide said performance levels, as they are equipped with accelerators, among which, Graphics Processing Units (GPUs) are a common choice. However, CES must undergo a rigorous Verification and Validation (V&V) process, in which a certain level of Execution Time Determinism (ETD) must be guaranteed. The use of several tasks to increase the overall utilization introduces contention in shared resources, which induces time variability. To provide the ETD guarantees, the time variability must be either mitigated or tracked and controlled. Another challenge for the adoption of GPUs in CES, is that the V&V process demands evidence of the thoroughness of the testing phase, for which Code Coverage is used as a test quality indicator. However, Code Coverage, as traditionally understood for sequential CES does not cover all possible scenarios in which a GPU thread might execute.For low-criticality and mixed-criticality CES, we contend that we can allow tasks to share the Last Level Cache (LLC) if hardware support for contention tracking is provided. Providing a clear understanding on how tasks contend with each other enables CES developers to balance performance and time predictability. For high-criticality CES, it is a common practice to implement LLC partitioning as it allows tasks to access LLC without suffering from inter-kernel contention, however, tasks may experience a performance loss due to lack of resources. In this Thesis, we propose Demotion Counters, a novel technique that tightly tracks how much each task has been demoted towards eviction in the LLC, thus, effectively quantifying their impact in CES. Additionally, we also assess the use of NVIDIA’s Multi-Instance GPU (MIG) feature as means to improve ETD in high-criticality CES.Code Coverage is used as a test quality indicator to provide evidence of the thoroughness of the testing, as required by the V&V process. However, if applied as traditionally understood, it will ignore the threading dimension of GPUs. Threads have private regions of memory, as well as shared regions at different granularities. This means that errors that are innocuous to one thread are potentially harmful for another, hence, it does not cover all possible cases under which GPU threads might execute. In this Thesis, we propose the use of Per-Thread Statement Coverage (PTSC), which tracks the Code Coverage at thread granularity. In order to mitigate the overheads caused by PTSC, several variants that apply different orthogonal optimizations are also proposed. Finally, we also evaluate the potential benefits of using hardware support for PTSC, mitigating the memory consumption of PTSC, as well as the execution time impact at deployment.Summarizing, this Thesis advances the state of the art in the adoption of GPUs in CES. The proposal of hardware contention tracking support and assessment of NVIDIA’s MIG, as means to improve ETD, effectively tackles the Time Predictability challenge in shared LLC. The proposal of software PTSC allows providing CES designers with the whole picture of the execution in commercially available GPUs. The use of hardware support for PTSC mitigates the overheads of software PTSC in deployment, while the different compression techniques reduce the volume of information during testing phase without losing data. Therefore, this Thesis provides means to face the Time Predictability and Code Coverage challenges of GPUs in CES.
LANGARITA BENÍTEZ, RUBÉN: Improving performance of genomics workloads through software optimizations and hardware acceleration
Author: LANGARITA BENÍTEZ, RUBÉN
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: 16/12/2025
Reading date: 06/02/2026
Reading time: 11:00
Reading place: C6-E106
Thesis director: ARMEJACH SANOSA, ADRIÀ | ALASTRUEY BENEDÉ, JESÚS
Thesis abstract: Modern multi-core architectures and accelerators have become the cornerstone for accelerating many workloads in scientific computing and engineering. Many efforts have been made to accelerate HPC applications on modern hardware architectures such as CPUs and GPUs, as well as FPGA and custom accelerators (ASICs) for specific workloads. Hence, HPC platforms are increasingly sought after to handle large-scale workloads that exploit different levels of parallelism available in the accelerators.However, there is an emergent class of workloads that cannot fully exploit the massively parallel capabilities of mainstream accelerators. Many HPC applications are often bottlenecked by the execution of sequential workflows composed of rather small compute-intensive kernels that implement complex dependency patterns. This is particularly noticeable in life science and healthcare applications, which implement long workflows of data-processing kernels. Often based on stencil and dynamic programming computations, these dependency-bound kernels tend to be moderate in size and implement complex data-dependency patterns that ultimately restrict parallelism exploitation.Precision medicine aims to improve healthcare by exploiting genomic information. In recent years, the sharp reduction in genome sequencing costs has driven a dramatic increase in the amount of data generated for processing, which has posed a significant computational and storage challenge. Sequence alignment, one of the most demanding computational problems addressed in sequencing studies, has numerous applications, including read mapping. The goal of read mapping is to align the reads extracted from the sequencing systems against a reference genome. A dynamic programming scheme is used to assign an alignment score for each of the candidates, which leads to poor data parallelization due to its dependency-bound patterns.The main objective of this work is to improve the performance of genomics workloads through software and hardware acceleration. We submit four contributions to the field. The first three are software enhancements, including an algorithm proposal, software optimizations, and kernel porting to the ARM architecture. In the last one, we expand our field of study and propose a new hardware accelerator for dependency-bound kernels, which targets dynamic programming algorithms used in genomics pipelines.

DOCTORAL DEGREE IN COMPUTING

NJOKU, UCHECHUKWU FORTUNE: Towards Effective and Interpretable Many-Objective Feature Selection in Machine Learning
Author: NJOKU, UCHECHUKWU FORTUNE
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 COMPUTING
Department: Department of Computer Science (CS)
Mode: Change of supervisor
Deposit date: 04/12/2025
Reading date: 03/02/2026
Reading time: 14:00
Reading place: Sala d'Actes Marti Recober de la FIB
Thesis director: ABELLO GAMAZO, ALBERTO | BILALLI, BESIM | BONTEMPI, GIANLUCA
Thesis abstract: Effective Machine Learning (ML) requires more than just accurate models; it also demands consideration of factors such as model complexity, fairness, and other task-specific requirements. Fulfilling these requirements begins at the data level by selecting features that con-tribute to addressing these concerns. This can benefit from a many-objective optimization approach to Feature Selection (FS).This thesis, therefore, studies Many-Objective Feature Selection (MOFS) and contributes to the development of efficient and responsible ML solutions. However, due to the large number of MOFS solutions, it comes with an interpretability challenge. Therefore, we also aim to propose a methodology for tackling this limitation of MOFS.Although FS has been long researched, previous work (on both filter and wrapper methods) has failed to address this gap by focusing only on one or at most two objectives. Also for the interpretability of FS results, no methodological approach has been proposed and rather a basic tabular representation has been used.We propose a framework that uses non-dominated sorting genetic algorithms to balance important and often conflicting objectives for FS. In particular, more than four to fifteen objectives could be considered with this method. For interpretability, our proposed methodology consists of six steps that consider three viewpoints: objectives, solutions, and variables (i.e., features).To achieve the research goal, we follow a structured approach: first, an extensive literature review that establishes the state-of-the-art and identifies open challenges. Next, empirical analyses of single-objective filter and wrapper methods, as well as multi-objective wrapper methods, are conducted to assess their strengths and limitations. Our MOFS framework is then proposed and evaluated through multiple experiments, including its application to fairness in ML. Finally, the interpretability methodology is instantiated as an interactive dashboard, which is validated through an experimental study involving 50 participants, with statistical analysis to assess its effectiveness.The findings highlight that no single FS method is universally optimal; instead, the best approach depends on dataset characteristics, task requirements, and objectives. While filter methods are computationally efficient and wrapper methods enhance model performance in single-objective settings, the proposed MOFS framework successfully balances multiple conflicting indicators related to performance, complexity, and fairness. Moreover, the interpretability methodology proved essential in helping data scientists to better understand MOFS results, enabling informed decision-making in FS.

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: pending
Reading time: pending
Reading place: pending
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

SERRA FANALS, MARC: Fracture toughness, finite fatigue life behavior and fatigue crack growth resistance of cemented carbides
Author: SERRA FANALS, 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: Article-based thesis
Deposit date: 19/12/2025
Reading date: 28/01/2026
Reading time: 11:00
Reading place: ESCOLA D'ENGINYERIA DE BARCELONA ESTAv. Eduard Maristany, 16 Sala PolivalentPlantA 0 (A.0.3) https://eebe.upc.edu/es
Thesis director: LLANES PITARCH, LUIS MIGUEL | JIMENEZ PIQUÉ, EMILIO
Thesis abstract: Cemented carbides are widely used in tooling and wear-intensive applications due to their high hardness, strength and toughness. However, their performance depends on tungsten and cobalt, two critical raw materials (CRMs) subject to supply risk, cost increases and environmental concerns. Partially substituting WC with cubic carbides (γ-phase: NbC, TiC, etc.) offers a promising path toward more sustainable hardmetals, but their adoption is limited by scarce knowledge of their mechanical reliability. In service, premature fracture—under monotonic or cyclic loads—is the dominant failure mode, making it essential to understand toughness, finite fatigue life, and fatigue crack growth (FCG) resistance in these complex microstructures.This PhD establishes a comprehensive microstructure–property framework for two γ-phase cemented carbides compared with two WC-Co references. It includes detailed microstructural characterization (grain size, phase distribution, binder mean free path and carbide contiguity), combining conventional WC-Co methods with newly developed image-analysis procedures tailored to three-phase systems. These adapted tools revealed key γ-phase features—such as low contiguity and binderless carbide clusters—that act as critical microstructural heterogeneities controlling fracture and fatigue behavior.Fracture toughness was assessed using complementary methodologies: traditional indentation, pre-cracked SENB specimens, and ultrashort pulsed laser ablation (UPLA) micro-notching for SEμNB samples, together with Hertzian indentation. SENB values served as the reference, showing that indentation consistently overestimates toughness in harder grades due to poorly formed Palmqvist cracks. The UPLA SEμNB technique matched SENB accuracy while significantly reducing preparation complexity. Hertzian indentation was only reliable for γ-phase grades, where a uniform flaw population ensured reproducible cracking loads.A key innovation of this thesis is the adoption of a finite fatigue life framework (≤200,000 cycles), more representative of real hardmetal service where failure occurs by subcritical crack growth of pre-existing flaws. Normalized S–N curves revealed lower fatigue sensitivity in fine-grained γ-phase grades, driven by a higher proportion of transgranular γ-carbide fracture that reduces binder-controlled cyclic degradation. Medium-grained grades showed similar fatigue sensitivity due to comparable microstructural scales.FCG experiments demonstrated that γ-phase additions reduce resistance to cyclic crack propagation in fine-grained grades, lowering thresholds and increasing growth rates due to brittle γ-carbide cleavage and limited ligament bridging. Medium-grained grades exhibited more metallic-like FCG behavior and higher fatigue sensitivity, reflecting stronger binder-ligament suppression. Finite-life fatigue data, analyzed via Weibull statistics and correlated with monotonic strength, enabled successful estimation of natural-flaw FCG behavior. Fine-grained grades showed excellent agreement with long-crack measurements, while medium-grained grades required R-curve corrections to account for stronger crack-growth resistance stemming from larger binder mean free paths and coarser grains. These results validate the methodology and provide a unified microstructure–fatigue–strength framework.Finally, FESEM, FIB and fractography clarified the micromechanisms governing crack propagation under monotonic and cyclic loading. Stable fatigue growth produced step-like facets within the binder, whereas unstable fracture showed dimple rupture. γ-phase grains were confirmed as preferential transgranular fracture sites—especially in fine-grained grades—explaining their lower toughness, reduced fatigue thresholds and accelerated FCG. Similar micromechanisms were observed around intrinsic defects, validating that monotonic strength and finite fatigue life are governed by the same flaw population.

DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING

MACIÀ CID, LLORENÇ: Performance Enhancement of a Vacuum Generation Pneumatic Device by Fluid Dynamics Characterization
Author: MACIÀ CID, LLORENÇ
Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
Programme: DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING
Department: Department of Mechanical Engineering (EM)
Mode: Normal
Deposit date: 19/12/2025
Reading date: 26/01/2026
Reading time: 11:00
Reading place: Sala de Conferències de TR5, planta 1, ESEIAAT
Thesis director: CASTILLA LOPEZ, ROBERTO | GAMEZ MONTERO, PEDRO JAVIER
Thesis abstract: In this thesis, behavior analyses and performance improvements, are presented for a supersonic vacuum ejector, key component in industrial automatization tasks. To characterize the performance of an EVKAC180 model ejector, a combination of numerical simulations using the Computational Fluid Dynamics (CFD) OPENFOAM toolbox and experimental measurements on a dedicated test rig was used. Two operation regimes: a supercritical mode, where the secondary flow chokes, and a subcritical mode, where it remains subsonic. And breakpoints were identified. Simulations reproduced this dual behavior with good agreement with experimental data, though some deviations were found at high and low flow rates. In addition to the density-based implicit solver (HiSA), an ex plicit solver (rhoCentralFoam) was also used, confirming consistent results across the flow rates. The polytropic evolution, another key ejector metric, was found to be initially adiabatic, progressively transitioning to isothermal. A one-dimensional model was developed to complement CFD simulations and estimate ejector performance from geometry and operating conditions. The model computes the entrainment ratio and secondary pressures under both critical and subcritical regimes. Its results were validated against experimental and CFD data, showing accurate predictions and low deviations (below 4 %) in critical regimes. It provides a faster, low-cost alternative for early design stages. The ejector performance was improved by analyzing the influence of design parameters through single- and multi-factor analyses. The mixing chamber length proved to be the most impactful factor, leading to a 10 % individual improvement. The fractional factorial multi-factor analysis confirmed this trend and produced the final improved geometry design, referred to as the EDGE ejector, achieving a slightly higher overall performance gain of 10.4 %. The interaction effects among parameters were found to be limited yet important overall. Finally, an empirical model tool for predicting the Total Evacuation Time (TET) was proposed, combining the characteristic and polytropic curves. Several experimental test rigs were used to refine the polynomial fits of the characteristic curves, exhibiting deviations in TET prediction as low as 1.4 %. The validated tool was then applied to the EDGE ejector, achieving a 4 % reduction in TET (a gain of 8 s) compared to the original model, fulfilling the objective of this research. Moreover, the tools developed in this thesis reduce the need for extensive experimental data and enable reliable forecasting for new ejector designs.

DOCTORAL DEGREE IN OPTICAL ENGINEERING

CUELLAR SANTIAGO, FATIMA: Optical and visual quality of presbyopia-correcting intraocular lenses
Author: CUELLAR SANTIAGO, FATIMA
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: Article-based thesis
Deposit date: 22/12/2025
Reading date: 20/02/2026
Reading time: 11:30
Reading place: Auditori Joan Salvadó del Ce (CUV) Facultat d'Òptica i Optometria de TerrassaAvgda. 22 de Juliol, 660. 08222 Terrassameet.google.com/wbu-qxqi-hkj
Thesis director: MILLAN GARCIA VARELA, MARIA SAGRARIO
Thesis abstract: The development of new presbyopia-correcting intraocular lens (IOL) designs, with their manufacturing and launching on the market makes optical characterization highly recommendable, allowing for a more objective and quantitative understanding of their properties before implantation, thus avoiding the influence of subjective and individual factors. International regulations require the evaluation of IOL optical and visual quality in both laboratory and clinical settings.This investigation focuses on the interaction of new presbyopia-correcting IOLs designs with ocular optical aberrations (in normal and astigmatic corneas), the effect of IOL decentration and tilt on image quality, and the potential risk of unwanted optical phenomena. In all these cases, studying the optical behavior of a set of diffractive trifocals, extended-depth-of focus (EDOF), and enhanced monofocal (EM) IOLs under controlled in vitro conditions serves as a valuable complement to clinical studies. The optical quality of IOLs is evaluated through preclinical metrics based on the modulation transfer function (MTF), the estimation of postoperative visual acuity, range of vision and halo. Characterization was conducted using an optical bench equipped with a model eye consisting of a saline-filled wet cell in which the commercial presbyopia-correcting IOLs under study are immersed one by one. Adaptive optics was used to introduce controlled amounts of corneal aberration. This configuration allows for an objective, patient-independent assessment and enables control over factors such as pupil size, corneal aberrations, and lens alignment, aspects difficult to control in clinical practice. The experimental setups approximately reproduced the conditions under which the lens is implanted in the eye, in accordance with current international standards (ISO 11979-2-2024 and ANSI Z80.35-2018). An upgrade of the optical setup to allow for depth of field scanning in the object space has been initiated with the characterization of tunable focus lenses (FTL).To complement and validate the characterization of intraocular lenses (IOLs) in the optical bench, this work also includes studying visual quality using the SimVis Gekko visual simulator, which allows dynamic reproduction of vision with different intraocular lens designs before the cataract surgery. We also provide clinical results, obtained through collaborative research, that demonstrate excellent agreement with the laboratory findings. These data include visual assessments (with and without astigmatism) of pseudophakic patients implanted with the same presbyopia-correcting IOLs tested in the optical laboratory.
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: pending
Reading time: pending
Reading place: pending
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

ARRÉS CHILLÓN, JAVIER: Application to Sensing, Imaging, and Cooling of Ultra-Thin Metal Films and Derived Nanostructured Glass Surfaces
Author: ARRÉS CHILLÓN, JAVIER
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: 04/12/2025
Reading date: 22/01/2026
Reading time: 15:00
Reading place: ICFO Auditorium
Thesis director: PRUNERI, VALERIO
Thesis abstract: The continuous evolution of optoelectronic systems responds to the demand for higher efficiency, speed, and sensitivity. A key strategy is to modify material dimensions at the nanoscale, which alters their optical, electrical, and thermal properties and enables new functionalities.A prominent example is ultra-thin metal films (UTMFs), with thicknesses below 10 nm, which exhibit properties different from thicker metal layers. This thesis explores the use of gold (Au) UTMFs deposited on copper oxide (CuO) seed layers, fabricated with industrial techniques such as physical vapor deposition (PVD). These ultra-thin films enable continuous and ultrasmooth surfaces, as well as tunable properties through optical or electrical processes.The potential of these UTMFs in electrochemical sensors based on self-assembled monolayers (SAMs) is demonstrated. The results show that thinner films respond more rapidly to SAM formation, and that biotin functionalization enables the detection of streptavidin through measurable resistance changes.The optical interaction between UTMFs and fluorophores is also investigated, focusing on fluorescence quenching caused by non-radiative energy transfer. Experiments reveal the dependence on film thickness and fluorophore–metal separation, confirming that these films can enhance the signal-to-noise ratio in fluorescence imaging of stained bacteria.Finally, glass surfaces are nanostructured with nanopillars (NPs) generated via thermally dewetted UTMF masks and subsequent etching. These surfaces exhibit unique optical properties: anti-reflective coatings in the visible range and enhanced infrared emissivity. Moreover, they are combined with thin polymer coatings to preserve visible transparency while improving the efficiency of passive radiative cooling (PRC). Results confirm that nanostructured glass surfaces dissipate more heat than flat ones, opening opportunities in solar panels, displays, and windows.This thesis therefore demonstrates the potential of Au UTMFs and nanostructured glass surfaces for the development of chemical sensors, advanced optical microscopy techniques, and radiative cooling applications.
CHIEN, YING-HAO: Revealing Ultrafast Dynamics in Hexagonal Boron Nitride with Attosecond X-ray Absorption Fine-structure Spectroscopy
Author: CHIEN, YING-HAO
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: 16/10/2025
Reading date: 27/01/2026
Reading time: 10:00
Reading place: ICFO Auditorium
Thesis director: BIEGERT, JENS
Thesis abstract: Since the invention of the integrated circuit (IC) in the 1950s, modern civilization has been built upon its foundation. As ICs continue to scale down and operate at higher speeds, managing heat dissipation and energy transfer process is critical to overcoming performance limitations and enabling the development of next-generation ICs. In classical models, electrons and phonons are treated as independent systems to simplify calculations. This approximation successfully describes electronic band structures, charge transport, and optical responses in many materials under equilibrium conditions. However, it neglects the critical role of electron-phonon coupling, a fundamental many-body interaction that governs non-equilibrium energy exchange between electronic and lattice degrees of freedom. Recent advances in attosecond X-ray absorption fine structure (atto-XAFS) spectroscopy offer an unprecedented opportunity to observe electron-phonon coupling dynamics with both attosecond temporal and element-specific resolution. Hexagonal boron nitride (hBN), a widely studied prototypical material with diverse applications, still presents unresolved questions regarding its ultrafast dynamics. In this work, we investigate the coupled electron and phonon dynamics in bulk hBN using atto-XAFS. By employing different excitation conditions and exploiting different temporal resolutions, we disentangle the respective contributions of electrons and phonons to the transient response, demonstrating the unique capability of atto-XAFS to probe many-body dynamics in real-time. To enable further studies of novel materials, we upgraded our titanium-doped sapphire (Ti:sapphire) chirped pulse amplification (CPA) laser system, integrated a new commercial TOPAS optical parametric amplifier, designed a novel microfluidics gas target combined with a piezo pulse valve system aimed at reducing helium consumption for high harmonic generation (HHG), implemented a cryogenic sample mount for temperature-dependent measurements, and replaced the diffraction grating in the soft X-ray spectrograph with high diffraction efficiency and high resolving power reflection zone plates. We demonstrate the enhanced performance of the upgraded system for future advanced atto-XAFS experiments.
TYULNEV, IGOR: Investigation and Control of Phase Transitions by Ultrafast Strong-field Techniques
Author: TYULNEV, IGOR
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: 10/12/2025
Reading date: 05/02/2026
Reading time: 10:00
Reading place: ICFO Auditorium
Thesis director: BIEGERT, JENS
Thesis abstract: This work presents the experiments and results on the application of mid-infrared laser sources towards condensed matter systems for the study and control of manybody interactions within material phases and at phase boundaries. Utilizing the decades in know-how and development of intense, few-cycle waveforms at high repetition rates, the here demonstrated applications leverage the mid-infrared wavelengths to study and control strong-field phenomena at ultrafast time-scales and across phase transitions. To this end non-linear techniques are employed to extend the source capabilities towards a variety of driving and probing wavelengths, meanwhile tailoring spin-angular momentum multi-color beams as driving fields with unique patterns. With strong-field driven dynamics happening at sub-cycle time scales, techniques such as high harmonic generation (HHG) are applied to a variety of materials which undergo electronic and structural transitions. For bulk transition metal dichalcogenides, as the investigated MoS2, the induced spatial and temporal symmetry breaking from a tailored trefoil-shaped strong-field allowed the detection of valley polarization, i.e. a carrier population imbalance between neighboring bandgap extrema. The specific control of the energy bands at these sites, first, allows the realization of a valley switch to be used for optical computing, and second, realizes a hybrid system of light and matter with band topology akin to the Haldane model, which paves the way towards field-induced and controlled topological phase transitions in two-dimensional materials. Furthermore, the field-induced currents and the emerging harmonics are used to probe the potential landscape of the lattice and therefore, simultaneously detect signatures of the crystal and band structure encoded in a static spectrum. Interference within the spectra further reveal the underlying electron-hole dynamics and timings. In high-temperature superconducting ceramics like YBCO, the temperature induced changes in electronic properties are also sensitively detected via HHG, even for more elusive material phases. Meanwhile higher order transitions like the correlated charge density wave (CDW) phase shows a mixture of electronic and structural changes in the HHG crystallography as investigated in TiSe2. The macroscopic and nonlinear approach yields major changes in the harmonic spectra even from small changes in e.g. atom displacement and identifies phase anisotropies which eluded conventional or microscopic techniques.

DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS

HASSANKALHORI, MAHDI: From Ion Channels to Industrial Enzymes: Modeling and Modulating Protein Functional Properties
Author: HASSANKALHORI, MAHDI
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: 19/11/2025
Reading date: 02/02/2026
Reading time: 11:00
Reading place: ESCOLA D'ENGINYERIA BARCELONA ESTC/Eduard Maristany, 16 (08019 Barcelona)Sala Polivalent Edifici Ahttps://eebe.upc.edu/ca/lescola/co
Thesis director: TORRAS COSTA, JUAN | LUCAS, MARIA FÁTIMA ASSUNÇAO
Thesis abstract: Recent advances in computational molecular modeling have significantly enhanced our understanding of protein structure and function, enabling the design and optimization of biomolecules for diverse applications, for instance in biosensing and industrial biocatalysis. This thesis aimed to leverage integration of innovative computational methodologies to investigate and modulate the functional properties of four distinct protein targets from two protein families: ion channels, specifically human acid-sensing ion channels (hASIC1a and hASIC3), and enzymes, including an artificial enzyme based on the Lactococcal Multidrug Resistance Regulator (LmrR) protein scaffold and thermophilic Streptomyces sclerotialus Tyrosine Hydroxylase (SsTyrH). Depending on the case and objectives, we employed an integration of computational protein structure prediction, molecular dynamics simulations, protein residue network analysis, an specialized ion binding site prediction tool and a machine learning-based model for functional site prediction to identify key positions involved in protein function, regulation and other relevant properties. Our findings include the discovery of novel functional regulatory sites in hASIC1a and the design of mutations that confer sustained currents in hASIC1a, the prediction of the potential calcium binding sites in hASIC3 for guiding the experimental identification and functional characterization of such regulatory positions. Furthermore, integrative computational approaches successfully led to the prediction of functional distal hotspots and improved variants in the LmrR-based enzymatic system and SsTyrH, all validated by experimental characterization. This research demonstrates the efficacy of integrating computational methodologies to engineer proteins with tailored functional properties, providing valuable insights for the development of optimized ion channels for biotechnological applications and industrial biocatalysts, as well as advancing our understanding of protein structure-function relationships.
MINGOT BEJAR, JULIA: Applications of Poly(N-isopropylacrylamide)-based Hydrogels in Chemical Engineering
Author: MINGOT BEJAR, JULIA
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: 21/11/2025
Reading date: 23/01/2026
Reading time: 11:00
Reading place: Campus universitari Diagonal-Besòs Av. d'Eduard Maristany, 6-12, 08930 Sant Adrià de Besòs, Barcelona Edifici I planta 0, espai I.0.1 (Polivalent)
Thesis director: ARMELIN DIGGROC, ELAINE APARECIDA | LANZALACO, SONIA
Committee:
     PRESIDENT: MECERREYES MOLERO, DAVID
     SECRETARI: MAS MORUNO, CARLOS
     VOCAL: CAPEZZA, ANTONIO
Thesis abstract: This doctoral thesis explores the multifunctionality of poly(N-isopropylacrylamide) (PNIPAAm)-based hydrogels as a platform for biomedical and environmental applications. By exploiting the thermoresponsive properties of PNIPAAm and its copolymers, the research demonstrates how this material can be engineered to perform in distinct technological domains.In the biomedical field, inert polypropylene surgical meshes, commonly used for hernia repair, were functionalised with gold nanoparticles and a Raman reporter, converting their surface into a SERS-active platform. Covalent grafting of PNIPAAm-based copolymers onto the plasmonic substrate imparted thermoresponsive behaviour, resulting in an implantable device capable of simultaneous SERS detection and thermal response. In vitro assays with fibroblast cells confirmed the biocompatibility and stability of the device, highlighting its potential for minimally invasive diagnostics and post-surgical monitoring.A complementary theranostic approach was applied to the modification of 3D polyurethane sponges, used in endoluminal vacuum-assisted therapies, with PNIPAAm hydrogel and metallic nanoparticles. Functionalisation with gold and silver nanoparticles, stabilised by biopolymer shells, endowed the modified sponges with antibacterial properties. Photothermal activation under Raman laser irradiation resulted in significant antimicrobial activity against Escherichia coli and Staphylococcus aureus, offering new prospects for infection detection and treatment in implantable devices.In the environmental section, the thermoresponsive behaviour of PNIPAAm hydrogels was exploited for solar-driven water desalination and sustainable energy generation. A PNIPAAm-alginate-PEDOT:PSS system exhibited enhanced water evaporation rates potentiated by the consecutive surface contraction of the hydrogel (“pudding effect”). Further developments involved PNIPAAm-gelatine hydrogels incorporating carbon black as photothermal absorber, achieving stable desalination performances under real conditions (outdoor sunlight), with demonstrated durability and reusability.Finally, PNIPAAm-based matrices were employed to fabricate hydrogel thermal electricity generators. This combination of PNIPAAm with doped conductive polymers enabled photothermal-to-electric energy conversion driven by ionic transport within the hydrogel network upon exposure to solar light.Overall, this thesis establishes PNIPAAm hydrogels as a highly adaptable material platform. Their thermoresponsive behaviour, combined with plasmonic or photothermal functionalities, offers potential solutions to challenges in healthcare and resources sustainability.
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 SIGNAL THEORY AND COMMUNICATIONS

GIL DÍAZ, CRISTINA: Characterization of cirrus clouds and dust aerosols with remote sensing: application of radiative transfer models for the study of their radiative effects
Author: GIL DÍAZ, CRISTINA
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: Article-based thesis
Deposit date: 09/12/2025
Reading date: 22/01/2026
Reading time: 10:30
Reading place: Sala de Juntas, Edificio D4, Campus Nord, Barcelona
Thesis director: SICARD, MICHAEL
Thesis abstract: Clouds and aerosols are key modulators of the Earth’s radiative balance, yet their interactions remain among the largest sources of uncertainty in climate projections. This Ph.D. thesis investigates aerosol–cloud–radiation processes at mid-latitudes, with emphasis on cirrus clouds and mineral dust, by combining long-term ground-based lidar measurements, radiative transfer modelling, and regional climate simulations.First, a multi-year dataset of MPLNET lidar measurements in Barcelona was analyzed to characterize the geometrical and optical properties of cirrus clouds and to quantify their direct radiative effect. Cirrus occurrence was high, with marked seasonal variability. Distinct radiative behaviours were identified: at nighttime, cirrus clouds warm both top-of-the–atmosphere and bottom-of-the–atmosphere, while during at daytime they consistently warm top-of-the-atmosphere and predominantly cool bottom-of-the-atmosphere.Second, the semi-direct radiative effects of Saharan dust during a coupled dust and heatwave event were assessed with a regional climate model over the Iberian Peninsula. Results highlighted the importance of spectral nudging for an accurate simulation and showed that dust absorption modifies thermodynamic profiles, cloudiness, and the surface energy balance, thereby partially mitigating heatwave impacts. These responses were spatially heterogeneous, reflecting the strong dependence of dust–radiation interactions on dust distribution and meteorological conditions.Third, the role of the dust giant mode and the dust conversion factors for calculating cloud condensation nuclei and ice-nucleating particle concentrations were examined. Incorporating a synthetic giant mode significantly improved the agreement with reference datasets for the dust direct radiative effect, despite inherent uncertainties and idealized assumptions. In addition, dust conversion factors were derived from AERONET and MPLNET lidar measurements, demonstrating the potential of lidar to provide vertically resolved proxies for aerosol indirect effects.
PÉREZ GUIJARRO, JORDI: On Quantum Supervised Learning and Learning Techniques for Quantum Error Mitigation
Author: PÉREZ GUIJARRO, JORDI
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: 22/12/2025
Reading date: 13/02/2026
Reading time: 11:00
Reading place: Aula D5-007, Edifici D5, Campus Nord UPC, Barcelona
Thesis director: RODRIGUEZ FONOLLOSA, JAVIER | PAGES ZAMORA, ALBA MARIA
Thesis abstract: The development of quantum computers promises to drastically reduce the time required to solve certain computational problems. Among their most promising applications is the field of machine learning. However, significant uncertainty remains in this area. In particular, it is still unclear under which learning scenarios quantum algorithms will outperform their classical counterparts. This thesis aims to deepen our understanding of when quantum speed-ups can be expected in machine learning tasks. Specifically, we examine the connection between learning speed-ups and the more extensively studied phenomenon of quantum computational speed-up. We conclude that, in cases where the training set can be classically generated, the two are equivalent concepts, and we provide examples of such functions based on the prime factorization problem.Importantly, quantum machine learning is not only concerned with improving classical learning algorithms using quantum computation but also with learning from quantum data. In this context, we investigate a learning scenario in which the inputs to the target functions are quantum states, thereby generalizing the classical supervised learning framework. To this end, we first focus on the problem of quantum hypothesis testing, which can serve as a subroutine for both the problems of evaluating a function and learning a function. Specifically, we derive several sequential methods for solving the problem of quantum hypothesis testing, along with a lower bound on the resources required. This lower bound immediately implies corresponding lower bounds for the problems of learning and evaluating functions. Additionally, we develop a learning method based on the classical shadows technique.Finally, after exploring how quantum processes can aid learning tasks, we examine how classical learning techniques can, in turn, enhance quantum computing. In particular, we study how classical machine learning methods can be used to mitigate the effects of noise in quantum devices, with a focus on quantum error mitigation. Specifically, novel feature maps are proposed for the technique known as Clifford data regression. First, a theoretical justification for these feature maps is provided, followed by an analysis and a subsequent evaluation of their performance through numerical experiments. It is concluded that, for some of the proposed feature maps, a performance improvement is indeed achieved.

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.

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: pending
Reading time: pending
Reading place: pending
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.
SLIMANI, MEHDI: Computational strategies for time-accurate simulation of part-scale LPBF
Author: SLIMANI, MEHDI
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: Article-based thesis
Deposit date: 15/12/2025
Reading date: 23/01/2026
Reading time: 11:00
Reading place: Sala Zienkiewich (CIMNE) Building C1, UPC - Campus North Gran Capitan S/N 08034 Barcelona
Thesis director: CHIUMENTI, MICHELE | CERVERA RUIZ, LUIS MIGUEL
Thesis abstract: The qualification of MAM (Metal Additive Manufacturing) processes remains a majorchallenge due to the complex thermo-mechanical phenomena involved.The process is driven by a small moving heat sourcethat generateshighly localized, transient thermal gradientsand induces thermal strains.As these strains are constrained bythe surrounding material,residual stresses and warpage develop,causing part distortion or even failure.Accurate modeling is essential for understanding the underlying physics, aswell as for reliable process qualification and parameter optimization.However,such simulations are computationally expensive due to the small size of theheat source, which introduces disparate spatial scales,and its continuous motion, which gives rise to equally disparate temporalscales.The need to simultaneously resolve these scalesrenders high-fidelity part-scale simulations prohibitively expensive.This thesis contributes to the field of MAM modeling on both the appliedand methodological fronts. On the applied side, methods for warpage and stressmitigation are investigated in both DED (Directed Energy Deposition) and LPBF (Laser Powder Bed Fusion) processes, includinga novel substrate design strategy for DED that significantlyreduces residual stresses, and a modeling framework to capturerecoater–induced build failure in LPBF.On the methodological front, the thesis focuses on developing efficientstrategies for high-fidelity part-scale simulations of LPBF processes,with particular emphasis on overcoming the disparity of temporal scales.WhileAMR (Adaptive Mesh Refinement) has become a popular approach to address the challenge of disparatespatial scales, uniform time stepping remains the standard approach in the field.For centimeter-scale parts, this can require hundreds of millions of time-steps,making such simulations computationally unfeasible.Commonly used strategies to alleviate this issue involveextreme simplifications of the thermal model,such as lumping multiple tracks or layersinto a single time-step.Effectively, this eliminates the small scales associated with the moving heat sourcebut compromises the model's predictive accuracy,requiring additional calibration.Two methods are proposed to address the temporal-scale disparity withouteliminating the underlying small scales: the advected subdomain and aRobin–Robin substepping scheme, both designed to preserve modelfidelity while drastically reducing computational cost.The advected subdomain method attaches a moving mesh to the laser. Bysolving the thermal problem in the reference frame of the heat source, thetransient dynamics near the melt pool become quasi-steady, allowing the use ofsignificantly larger time-steps.Substepping divides the domain into regions that evolve with differenttime-steps:finer steps are applied locally around the moving heat source, while larger stepsare used away from it.The developed Robin-Robin coupling scheme proves robust andensures mesh-independent convergence between the regions.These methods and their components are systematically evaluated throughnumerical analysis, benchmarked against standard approaches, and validatedagainst experimental data. Furthermore, they are combined to compound theirrespective benefits.Together, these contributions advance numerical MAM modeling,thereby improving the computational efficiency of high-fidelity simulationsand enabling reliable process qualification and optimization.

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 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: pending
Reading time: pending
Reading place: pending
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.

Last update: 21/01/2026 05:46:15.