Theses authorised for defence

DOCTORAL DEGREE IN ARCHITECTURE, ENERGY AND ENVIRONMENT

• CASTELLARNAU VISUS, MARIA ANGELES: Cosecha de lo invisible. Paisaje de agua en la Val de Ayerbe
  
  Author: CASTELLARNAU VISUS, MARIA ANGELES
  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 ARCHITECTURE, ENERGY AND ENVIRONMENT
  Department: Department of Architectural Technology (TA)
  Mode: Normal
  Deposit date: 26/09/2025
  Reading date: 09/01/2026
  Reading time: 12:30
  Reading place: ETSAB (Esc. Técnica Sup. Arquitect) - Pl.Baja - S.Grados Av. Diagonal, 649 - 08028 - BCN (Videoconf: https://meet.google.com/vfh-ownh-czn; Inicio: 12:00 h)
  Thesis director: CUCHÍ BURGOS, ALBERTO
  Thesis abstract: In a context of environmental crisis evidenced by the loss of biodiversity, drought, percolation in the functional structures of productive landscapes, global warming, and trends towards irreversible positions; of social crisis that reveals the strong depopulation of rural areas, the imbalance, the loss of community social structure, and the loss of linkage of people with the natural environment. And of economic crisis resulting in a loss of land use, changes in the system of ownership, the fragility of agricultural and livestock activities increasingly subjected to the costs of industrialization and inputs in the sector, and the tensions of the markets of production and distribution of food. The inland territories of the northeastern Iberia peninsula are thrown into a critical environmental and social vulnerability that jeopardizes the sustainability of habitability in these territories and their systemic functionality as resource and food producing territories.The present research aims, through the analysis of the management of material flows in the cultural landscapes of the pre-Pyrenean zone of Huesca, to find the keys that in the interrelation between architecture and agriculture reveal the strategies that make it possible for human beings organized in society to inhabit these territories.The systemic analysis of the biophysical matrix on which pre-industrial societies organized in communities manage resources to inhabit the territory provides the foundations for the management of material resources that make possible the sustainability of productive systems and, therefore, of habitability in these arid territories.Knowing and understanding the fundamental principles that govern the systemic functioning of the dynamics of micro-systemic and macro-systemic exchanges and management of material resources applied by pre-industrial societies will allow the development of strategies to achieve habitability in these territories and in territories with a similar biophysical and climatic matrix in a post-oil scenario.The present research analyzes this management in the area of the Ayerbe valley, an eminently agricultural territory typical of the pre-Pyrenees in Huesca. From this analysis of the biophysical matrix, the pre-industrial social group and its structure and dynamics of community management and the strategies of water and soil management, technological strategies that allow maintaining the viability of inhabiting these territories are refined.The methodology used consists of a cartographic study, an interview, the study of an 1856 land survey, the analysis of the internal regulations of the irrigation communities, fieldwork and the case study of the different systems of soil and irrigation management.The research results describe these modeling technologies of the natural hydrological system and soil geomorphology, which are deployed in water and soil harvesting and irrigation systems that govern as fundamental laws in the construction of the cultural landscapes of this territory. Thus, flooding, infiltration, drainage, runoff, catchment, conduction, decanting, storage, evapotranspiration, terracing, etc. technologies are described, which aim to replenish nutrients, maintain soil fertility, prevent erosion, optimize water harvesting, adapted to the local rainfall regime, crop cycles and management, and soil structure.In conclusion, the technological strategies detected are governed by fundamentals based on the laws of nature adapted to this climate and this biophysical matrix and are therefore susceptible to reconsideration for the development of strategies for the management of material resource flows not based on the use of fossil fuels in the future.
  

DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE

• 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: pending
  Reading time: pending
  Reading place: pending
  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.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• DEHGHANSOURAKI, DANIAL: Modeling Sediment Transport in Rivers and Reservoirs using an Accelerated Model
  
  Author: DEHGHANSOURAKI, DANIAL
  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: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 04/12/2025
  Reading date: 15/01/2026
  Reading time: 12:00
  Reading place: ETSECCPB Edificio C2 -212 - Sala Conferencias Campus Nord Barcelona
  Thesis director: BLADE CASTELLET, ERNEST | LARESE DE TETTO, ANTONIA
  Thesis abstract: Reservoir sedimentation is a critical, ongoing issue in managing water resources sustainably. While conventional two-dimensional models are computationally efficient, they miss key three-dimensional processes, such as thermal stratification. Three-dimensional models provide a more accurate physical representation but require extensive computational resources, making them impractical for large-scale applications. This research creates a computational framework that combines High-Performance Computing, Artificial Intelligence, and advanced 3D multiphysics simulation to bridge this gap.A two-dimensional hydro-morphodynamic model (R-Iber) was rebuilt for Graphics Processing Units, resulting in computational speed-ups of one to two orders of magnitude. The accelerated model supported training a Deep Neural Network surrogate, enabling a 100,000-run Monte Carlo analysis for robust model calibration and uncertainty quantification. In parallel, a comprehensive three-dimensional multiphysics model was developed in the Kratos framework to simulate the 3D fluid-thermal problem.The integrated approach was used for the Riba-roja reservoir system. It measured how thermal stratification affects sediment trapping efficiency. Results show that combining HPC, AI, and multiphysics modeling leads to practical and actionable methods for sustainable reservoir management.
  
• 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: pending
  Reading time: pending
  Reading place: pending
  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.
  
• GIESEN LEÓN, JEREMY JENS: Modeling and Optimization of Timing Interference for Time Critical Systems on Multicore COTS Platforms
  
  Author: GIESEN LEÓN, JEREMY JENS
  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: 27/11/2025
  Reading date: 15/01/2026
  Reading time: 11:00
  Reading place: C6-E101
  Thesis director: MEZZETTI, ENRICO | CAZORLA ALMEIDA, FRANCISCO JAVIER
  Thesis abstract: Critical Real-Time Embedded Systems (CRTES) underpin automotive, aerospace, medical devices, among others. They must guarantee deterministic, certifiable behavior under worst-case conditions. As functionality grows (sensor fusion, AI, etc), uniprocessors fall short, prompting adoption of COTS multicores. Yet shared resources induce timing interference that threatens predictability and complicates certification, especially in heterogeneous SoCs with crossbars, bridges, and hierarchical memory.This Thesis advances timing predictability on complex multicores through three linked pillars: standardized hardware observability, contention modeling, and system-level optimization. Together they form a coherent, auditable path from low-level measurements to design decisions.First, we introduce unified observability frameworks combining core-local counters with system-level tracing. They correlate hardware events with task phases, reconstruct scheduling and contention across cores and interconnects, and standardize configuration and interpretation across heterogeneous devices. Measurements are attributed to tasks (excluding OS activity), incur bounded overhead, and yield ordered access sequences preserving temporal structure. Along with latency tables for memories and bridges, these artifacts make timing phenomena measurable and calibrate conservative models.Second, we develop contention models grounded in realistic traces. Traditional Access-Count Contention Techniques (ACCT) are overly conservative for parallel crossbars. Sequence-Aware Techniques (SACT) exploit request ordering to prune infeasible overlaps and tighten bounds. We propose ASCOM, a scalable framework balancing accuracy through compositional pairing against contender sequences and segmentation of long traces. We derive explicit upper/lower bounds to quantify margins and add bridge awareness to capture inter-cluster traversals and remote-memory asymmetries. Across single- and multi-crossbar SoCs, sequence-aware analysis yields tighter, trustworthy bounds while remaining tractable on industrial-scale traces.Third, we examine how modeling informs code and data placement across heterogeneous memories. Feasibility considers capacity and compatibility; locality and non-uniform latencies are captured through calibrated SACT. Exploration reveals pronounced sensitivity to placement: with identical workloads and schedules, changing only the mapping can shift contention by over 100% of reference execution time, due to bridge traversals, device asymmetries, and port effects. Architectural factors thus directly shape worst-case interference, elevating placement to a first-order design parameter.An end-to-end workflow operationalizes these ideas. System-level traces are captured on an industrial target hardware. Traces are filtered into ordered access sequences retaining temporal structure and feeding SACT analysis. Empirical campaigns build latency tables for memories and bridges. With these calibrated inputs, the bridge-aware SACT model estimates contention and total delay for alternative placements.Results show robust contention analysis on COTS multicores is feasible when: (i) the right signals are observed with standardized, low-intrusion instrumentation; (ii) models are sequence- and bridge-aware with explicit margins; and (iii) insights drive placement where locality and capacity are addressed coherently. Because ordered sequences, latency tables, and task-scoped metrics come from the deployed hardware, conclusions are auditable and fit safety cases. Combining hardware-aware instrumentation, realistic modeling, and contention-driven mapping, the Thesis provides a practical framework for timing predictability in CRTES and narrows the gap between certification expectations: traceability, explainability, repeatability and the behavior of parallel interconnects and heterogeneous memories in contemporary multicore SoCs.
  

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 CONSTRUCTION ENGINEERING

• RAMIREZ PEREZ, ALEXIS JOHARIV: Comportamiento a flexión y cortante de un tablero continuo de vigas pretensadas con tendones de polímeros reforzados con fibras (FRP)
  
  Author: RAMIREZ PEREZ, ALEXIS JOHARIV
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 22/10/2025
  Reading date: 12/01/2026
  Reading time: 11:00
  Reading place: C1-002
  Thesis director: OLLER IBARS, EVA MARIA | MARI BERNAT, ANTONIO RICARDO
  Thesis abstract: The durability of reinforced concrete structures is mainly compromised by steel corrosion, which generates high maintenance costs and reduces structural safety. Fiber-reinforced polymers (FRP) represent an alternative of great interest, as they provide high specific strength and are not susceptible to corrosion. However, their application as active reinforcement in continuous prestressed members is still very limited, due to the scarce experimental research on their structural performance and the absence of specific design guidelines.The main objective of this dissertation is to analyze the flexural and shear behavior of a two-span continuous bridge at 1/3 scale, built with precast prestressed girders and a cast in situ reinforced concrete slab, using carbon carbon fiber composite cables “CFCC” tendons as active reinforcement. The research was organized into three phases: (1) characterization of carbon fiber (CFRP) bars, glass fiber (GFRP) bars, and CFCC tendons, with the latter selected for prestressing due to their suitability; (2) a flexural test on span 1, with a concentrated load applied at midspan, to study the global flexural behavior at the serviceability and ultimate limit states; and (3) a shear test on span 2, with a concentrated load applied 1.6 m from the end support, to evaluate shear strength, effectiveness of GFRP stirrups, and the influence of CFCC prestressing. The results were compared with numerical simulations using the CONS program and with the CCCM analytical model adapted to FRP tendons. The experimental tests showed that CFCC tendons reached 62–76% of their ultimate strength without anchorage slip in the flexural test, confirming their reliability as active reinforcement. Failure was governed by shear-off at the girder–slab interface. In shear, failure occurred after a characteristic diagonal cracking pattern and progressive redistribution of stresses between spans, while shear-off failure was avoided through a reinforcement added after the flexural test.The overall contribution of this dissertation lies in providing the first comprehensive experimental, analytical, and numerical evidence on a continuous bridge prestressed with CFCC tendons. The findings strengthen confidence in the use of FRP in concrete structures, and open new research avenues aimed at optimizing transverse reinforcement and moving towards the codification of this technology.
  
• VALVERDE BURNEO, DAVID ENRIQUE: Desarrollo de nuevos materiales cementicios multifuncionales
  
  Author: VALVERDE BURNEO, DAVID 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 CONSTRUCTION ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 10/10/2025
  Reading date: 19/01/2026
  Reading time: 11:00
  Reading place: C1-002
  Thesis director: SEGURA PEREZ, IGNACIO | GARCIA TRONCOSO, NATIVIDAD LEONOR
  Thesis abstract: This doctoral thesis focuses on the development of multifunctional cementitious materials, combining structural strength with self-sensing capabilities through piezoresistivity, as well as integrating deformation energy dissipation through auxetic structures. The research explores the integration of conductive and structural fibers in cementitious matrices, coupled with the use of advanced manufacturing techniques such as 3D printing and the use of flexible silicones to obtain molds with complex architectures. The objective is to obtain cementitious materials that in addition to possessing structural capacity, have added function capabilities. It is expected that these materials can be used in buildings with self-monitoring, damage prevention, stress sensing pavements, structural elements with higher impact resistance and energy dissipation capabilities. The research begins with an exhaustive bibliographic review, from which the most promising materials have been selected to achieve the proposed objectives. The experimental campaign and data treatment/analysis have been defined. The work continues with the realization of the planned experiments, the analysis of the results, the optimization of the composition and properties of the new cementitious materials, the development of prototypes testing the potential applications.From the achievements obtained in this doctoral thesis we have the following: the research and publication of a cementitious composite reinforced with recycled carbon fibers to obtain a piezoresistive conductive concrete, which presents a variation of the electrical conductivity with respect to the unitary deformation quite evident when the fiber addition contents are around 1% in volume. This makes it an ideal sustainable cementitious material for strain and/or stress detection. This publication can be found in the journal Construction and Building Materials.Another research focuses on the mechanical characterization of cellular auxetic cementitious cementitious composites (which achieve their auxeticity through the presence of ellipsoidal holes in their structure) reinforced with recycled steel fibers. This research successfully characterizes the influence of fiber content on the mechanical response to compression and deformation energy dissipation, while demonstrating the feasibility of using recycled resources. Within this same publication, a family of functions was presented that successfully fit the mechanical response curves (stress-strain, energy dissipated by deformation) that were obtained experimentally. This publication can be found in the Journal of Building Engineering.A third article achieved in this thesis deals with the development of a new type of piezoresistive concrete with auxetic capacity. This material, obtained by combining cellular auxetic cementitious cementitious composites and recycled carbon fibers, is capable of detecting deformations from very low to high levels. Its potential applications in structural monitoring are promising, and the results of this research have been published in Case Studies in Construction Materials.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• BUSTO ABADIA, JAIME: Estudio y mejora del flujo armónico de cargas
  
  Author: BUSTO ABADIA, JAIME
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 18/11/2025
  Reading date: 20/01/2026
  Reading time: 13:00
  Reading place: ETSEIB, aula H4.2
  Thesis director: MESAS GARCIA, JUAN JOSE | SAINZ SAPERA, LUIS
  Thesis abstract: The presence of voltage and current harmonics in electrical installations is a long-standing challenge in the field of power quality, a challenge that remains relevant today due to the continuous increase in nonlinear loads connected to these installations, the growing sensitivity of electrical devices to disturbances, and the need to predict and prevent problems arising from all the above factors. To address this, both standards that evaluate and quantify the tolerable limits of harmonic distortion for the electrical system and the loads connected to it have been developed, as well as various tools based on the formulation and numerical solution of the system of equations posed in harmonic load flow analysis. In addition, procedures to mitigate the harmonic problem have been studied. In this context, the development of the harmonic load flow formulation has always aimed to study the problem using the smallest possible number of equations that still yield correct results, thereby reducing the numerical problems involved in its mathematical solution without sacrificing accuracy. Although this formulation has already been extensively studied, researchers continue to propose improvements to it that allow the aforementioned objectives to be better achieved.Considering all the above, the objectives established in the thesis, which have ultimately been achieved, are:1.- Development and programming of a new harmonic load flow formulation that improves the convergence properties of current formulations.2.- Harmonic sensitivity analysis of the four most common types of nonlinear loads in electrical installations (single-phase and three-phase rectifiers with capacitive filters, three-phase 6-pulse rectifiers, and discharge lamps), and incorporation of the results into the new formulation.3.- Validation of the new formulation against those existing in the literature using a 3-bus academic network and an IEEE 14-bus network expanded to 23 buses.4.- Study of the harmonic cancellation phenomenon using the new formulation and the IEEE 14-bus network expanded to 23 buses.The following methodology was employed to achieve these goals:In the first part of the thesis, the state of the art of existing harmonic load flow formulations found in the literature was analysed, along with the treatment of variables, equations, and the problems they present. Then, the four common types of nonlinear loads in electrical installations were described, along with their modelling and their voltage and current responses to harmonic excitations.Subsequently, the new formulation was presented, including the theoretical foundations it is based on, the calculation stages it is divided into, as well as the data used and the unknowns to be calculated. The harmonic sensitivity analysis of nonlinear loads was also shown, which determines the differentiated treatment each will receive in the new formulation.Next, two application examples were presented to validate the results obtained. The new formulation was applied to two networks of different complexity, analysing the results and comparing them with those obtained using other existing formulations, both with single and aggregated loads.The final part addressed the study of harmonic cancellation in several groups of aggregated nonlinear loads, calculating the harmonic cancellation rate in each case using the new formulation developed.
  

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

• RODRÍGUEZ ROMERO, CARLOS EDUARDO: Analysis of coupled hydro-mechanical processes in double-structure geomaterials for nuclear waste storage
  
  Author: RODRÍGUEZ ROMERO, CARLOS EDUARDO
  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: 04/12/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: VAUNAT, JEAN | GENS SOLE, ANTONIO
  Thesis abstract: The safe long-term isolation of high-level radioactive waste requires engineered barriers capable of maintaining low permeability and mechanical stability under complex thermo-hydro-mechanical (THM) conditions. Among candidate materials, compacted bentonite exhibits a distinctive double-structure behaviour, governed by the coexistence of micro- and macro-porous domains. This thesis focuses on the analysis of coupled hydro-mechanical processes in double-structure geomaterials, with particular attention to bentonite mixtures of blocks and pellets, as used in buffer systems for deep geological repositories. The research first reviews the geomechanical basis of double-structure soils and identifies the experimental evidence supporting their dual-porosity nature. A constitutive THM framework is then developed, extending the existing double-structure formulation to incorporate: (i) the parameter ακ to control microstructural deformation; (ii) a fabric-dependent structuration law to represent the memory and degradation of compression; and (iii) frictional resistance at block–pellet and block–wall interfaces.The model was implemented and calibrated using laboratory and mock-up experiments from the BEACON project, including the MGR22, MGR23, and MGR27 experiments, the EPFL path-dependent tests and the POSIVA test. Numerical simulations successfully reproduced the evolution of swelling pressure, void ratio, dry density, water content and water intake observed experimentally. The results confirmed that friction plays a decisive role in the redistribution of stresses between pellets and blocks, while microstructural evolution governs the long-term homogenisation process. The enhanced formulation captured partial density homogenisation and the persistence of microstructural porosity, in agreement with laboratory observations.Overall, the thesis provides an improved understanding of the coupled hydro-mechanical behaviour of double-structure bentonites and proposes a robust constitutive framework capable of reproducing their key features under repository-relevant conditions. The work highlights the necessity of considering both microstructural evolution and frictional effects in predictive models for bentonite barriers, thus contributing to the reliability of long-term safety assessments of deep geological repositories.
  
• SAYAD NOGHRETAB, BABAK: HYDRO-MECHANICAL MODELING OF GAS FLOW THROUGH CLAY-BASED ENGINEERED ISOLATION BARRIERS
  
  Author: SAYAD NOGHRETAB, BABAK
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 16/10/2025
  Reading date: 15/01/2026
  Reading time: 10:00
  Reading place: ETSECCPB.UPC, Campus NordBuilding C1. Classroom: 002C/Jordi Girona, 1-308034 Barcelona
  Thesis director: PUIG DAMIANS, IVAN | OLIVELLA PASTALLE, SEBASTIAN
  Thesis abstract: Safe management of high-level radioactive waste (HLRW) requires durable isolation from the biosphere over geologic time. Deep geological repositories (DGRs) rely on engineered and natural barriers, with bentonite as a key buffer and backfill material because it seals fractures, sorbs radionuclides, and develops swelling pressure during hydration. During operation and early post closure, resaturation and corrosion generate gas, so predicting system behavior requires coupled hydro gas mechanical models that represent double porosity, heterogeneity, and preferential pathways. This Thesis addresses that need by integrating explicit pathway mechanics in compacted buffers, double porosity constitutive laws for pellet/powder mixtures, and image-based statistics linked to finite element simulations in CODE_BRIGHT.First, a three-dimensional coupled hydro gas mechanical model of the large-scale gas injection test (LASGIT) is formulated with heterogeneous initial permeability, embedded fractures with dilatancy, and explicit gap closure states at the canister–buffer interface and is exercised through targeted sensitivity analyses. Second, the BENTOGAZ laboratory mixture of equal parts pellets and MX-80 powder is modeled with the Barcelona Expansive Model to couple microstructure and macrostructure; systematic parameter studies are complemented by a handmade heterogeneity setup that assigns distinct properties to randomly distributed pellet and powder domains. Third, an image to model workflow for SEALEX links micro-CT analysis to simulation: binarized slices yield macroporosity maps, directional variograms quantify anisotropy and correlation lengths, and the fitted statistics generate anisotropic porosity fields that enable automatic heterogeneity on the finite element mesh.Together, these methodologies constitute a set of methods that couple explicit fractures with dilatancy, dual structure behavior, and image informed spatial heterogeneity for repository relevant assessment of gas entry, resaturation, and sealing performance.
  

DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING

• LU, YONGGANG: Research on Transient Flow Characteristics and Dynamic Behaviour of hydraulic Pumps in Support of Energy transition
  
  Author: LU, YONGGANG
  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: Article-based thesis
  Deposit date: 26/11/2025
  Reading date: 16/01/2026
  Reading time: 11:00
  Reading place: Aula Laboratori Hidràulica, Pavelló D, planta -1, ETSEIB
  Thesis director: PRESAS BATLLÓ, ALEXANDRE
  Thesis abstract: Amid the global shift to low-carbon energy, multi-energy complementary power systems are key to achieving carbon neutrality. Nuclear energy, pumped storage hydropower, and industrial waste energy recovery enhance energy system flexibility but increase demands on energy transfer and fluid transport. Hydraulic pumps, vital for energy conversion, face challenges: RCPs in Generation IV lead-cooled reactors suffer from corrosion and vibration; pumped storage units face stability issues; and industrial waste pressure recovery is inefficient under variable conditions. This study focuses on three core devices—RCPs, pump-turbines, and PATs—using analysis, simulation, and experiments to investigate their dynamics and propose optimizations.First, the transient fluid-structure interaction of lead-bismuth eutectic RCPs during startup was studied. A mathematical model for flow rate and rotational speed under various startup modes was developed. Bidirectional fluid-structure interaction analysis showed maximum stress at the impeller blade root and maximum deformation at the blade-hub/shroud junction. Higher startup torque increased acceleration and torsional shock, with peak stress linked to instantaneous rotational speed. These findings inform safer RCP startup design.Second, the dynamic characteristics of reversible pump-turbines under load rejection were studied using 3D transient simulations and entropy production theory to analyze energy loss. The study found the unit crosses the S-shaped region during load rejection, with complex flow under reverse pump conditions. When speed exceeded 110%, significant fluctuations in axial hydraulic thrust and torque were observed, and blade pressure loads became asymmetric. These findings improve understanding of pump-turbine transient behavior.Finally, a two-stage PAT system for high-pressure energy recovery in petrochemicals was studied, focusing on vortex evolution and pressure pulsations. Pulsations in the diffuser stemmed from rotor-stator interaction near the tongue, with strong inter-stage interference at the inlet impeller. Low-frequency pulsations from vortex shedding were detected at high flow rates, threatening system stability. Combined experiments and simulations clarified pulsation propagation, aiding inter-stage matching and efficiency improvements.The innovative results of this study have been published in leading fluid mechanics and energy journals. They advance the theoretical understanding of hydraulic pump dynamics and provide practical solutions for nuclear safety, grid flexibility, and industrial energy conservation. The main body of the dissertation details each research component, with three supporting JCR Q1 articles appended.
  

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.
  

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 EST C/Eduard Maristany, 16 (08019 Barcelona) 934137400 Sala Polivalent Edifici A https://eebe.upc.edu/ca/lescola/com
  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.
  

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.
  
• IRAWAN, AMIR MUSTOFA: Explainable Artificial Intelligence Applied to Geoscience and Remote Sensing: Development and Application to Wild Fire Forecasting Related to Climate Change
  
  Author: IRAWAN, AMIR MUSTOFA
  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: 17/11/2025
  Reading date: 20/01/2026
  Reading time: 11:30
  Reading place: Aula de Teleensenyament, Edifici B3, Campus Nord UPC, Barcelona
  Thesis director: VALL-LLOSSERA FERRAN, MERCEDES MAGDALENA | LOPEZ MARTINEZ, CARLOS
  Thesis abstract: this thesis presents a progressive exploration of wildfire prediction by integrating process-based understanding with machine learning and causal inference frameworks. Chapter 3 focuses on variable importance and sensitivity by applying perturbation-based interventions, altering key drivers such as vapour pressure deficit (VPD), soil moisture (SM), and jet stream metrics by up to ±25% to simulate intensified environmental conditions and assess their impact on burned area. In contrast, Chapter 4 employs formal causal inference through do-calculus, enabling targeted counterfactual analysis within a structural causal model (SCM). Unlike the continuous perturbation-based interventions in Chapter 3, the intervention scenarios here are implemented by bootstrapping input variables and setting them to the 25th, 50th, 75th, and 100th percentiles. This allows the model to simulate the impact of each variable across a range of conditions, from typical to extreme (worst-case), and to quantify both direct and indirect effects on burned area, particularly for key drivers such as ∆Z500 and v300. Chapter 5 extends the causal reasoning to a global scale by using PCMCI-derived graphs as structural priors within a deep learning framework. It introduces regime-specific directed acyclic graphs (DAGs) generated through spatial clustering using the DBSCAN algorithm, enabling the identification of region-specific land–atmosphere interactions. These causal graphs are then embedded into Graph Attention Networks (GATs), allowing the model to learn weighted connections informed by causal structure, thereby enhancing both predictive performance and physical interpretability. Finally, Chapter 6 synthesizes these advances by embedding causal graphs within a GAT to simulate complex, multiscale interventions. It incorporates explicit counterfactual scenarios simulating intensified El Niño (via doubled negative SOI) and jet stream ridging (via increased positive ∆Z500, v300, and jet core), revealing spatially distinct fire responses. The use of different intervention strategies across chapters reflects the evolving methodological focus, from assessing input sensitivity (Chapter 3), to inferring causal mechanisms (Chapter 4), validating causal structures across regions (Chapter 5), and finally quantifying scenario-based outcomes (Chapter 6). Building on this foundation, Chapter 6 introduces a causal GAT capable of predicting global burned area by integrating physically grounded causal graphs derived from PCMCI. This approach enables the model to follow meaningful land–atmosphere interactions, improving interpretability and aligning predictions with known physical processes. The results show that the causal GAT outperforms models using fully connected graphs. Excessive or non-informative edges in fully connected structures can lead to over-smoothing, a common issue in Graph Neural Networks, where repeated message passing across redundant links blurs key distinctions among node representations. This can obscure critical predictive features and degrade overall model accuracy. By pruning spurious or weakly informative connections, the causal GAT preserves sharper, more meaningful node embeddings and avoids the performance loss typically associated with over-parameterized graph structures. Collectively, these advances underscore that correlation-based models fail to capture the complex, non-linear interactions among ignition sources, vegetation dynamics, and climate feedbacks. They advocate for a shift toward process-based and machine learning models that can better represent the multifaceted mechanisms governing wildfire regimes in a warming world.
  
• YI, TIEYAN: UAV SAR Interferometry: ARBRES-X Data
  
  Author: YI, TIEYAN
  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: 04/11/2025
  Reading date: 20/01/2026
  Reading time: 11:00
  Reading place: Aula MERIT D5-010, Campus Nord UPC, Barcelona
  Thesis director: MALLORQUI FRANQUET, JORDI JOAN
  Thesis abstract: Small UAVs are attractive SAR platforms, but their unstable trajectories and imperfect GPS/IMU logs introduce significant motion errors that degrade image quality. The ARBRES-X system employs wide-beam, high-squint acquisitions that favor short-aperture observations, while simultaneously reducing sensitivity to motion errors. This thesis first reviews the fundamentals of SAR imaging and cross-track interferometry, then analyzes the ARBRES-X system characteristics in detail, with particular attention to how short apertures and wide beams affect processing. The accuracy requirements for platform state in SAR imaging and cross-track interferometry are quantified, revealing that off-the-shelf INS solutions are insufficient. To address this gap, a motion-error estimation algorithm is proposed and validated using simulated data. Building on these results, an end-to-end processing framework for SAR imaging and cross-track interferometry is developed and applied to ARBRES-X data. The framework produces highly coherent interferograms, and differential interferograms clearly detect PARC phase changes induced by controlled deformation, in close agreement with theoretical predictions. In addition, a speed optimization method suitable for short-aperture imaging is also demonstrated.
  

DOCTORAL DEGREE IN SUSTAINABILITY

• ADAMO, ANGELA: Contribution to the decarbonisation of energy intensive industries in the path of the European Union objectives. Application to the case study of SEAT
  
  Author: ADAMO, ANGELA
  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: Article-based thesis
  Deposit date: 18/11/2025
  Reading date: 12/01/2026
  Reading time: 16:00
  Reading place: Sala polivalent, EEBE, Edifici A, Campus Diagonal-Besós
  Thesis director: MARTIN CAÑADAS, MARIA ELENA | DE LA HOZ CASAS, JORGE
  Thesis abstract: The urgent need to address climate change is intensifying global efforts to decarbonize all sectors, especially the industrial sector, which remains one of the most challenging due to its high-temperature demands and complex operations. Among the most promising solutions is electrification through High Temperature Heat Pumps (HTHPs), potentially combined with electric boilers.This thesis assesses the decarbonization potential of HTHPs in industrial cogeneration systems, using a real case study: the Combined Heat and Power (CHP) plant at SEAT’s automotive factory in Martorell, Spain. Currently powered by natural gas, the plant provides superheated water (SHW) and is a major source of the site’s CO₂ emissions, while facing increasing environmental and regulatory pressure.Unlike prior studies that use simplified or idealized models, this work develops a high-fidelity hybrid thermodynamic model of the CHP system, based on one year of operational data and realistic constraints of electrification technologies. Two modeling approaches were explored—a purely thermodynamic model and a hybrid model integrating empirical data to compensate for sensor inaccuracies. The hybrid model, with lower error margins, was chosen for further analysis.The model includes all major components: gas and steam turbines, post-combustion heat recovery boiler (HRB), absorption chillers, air coolers, and auxiliary boilers, enabling accurate simulation of the plant under real conditions. The technical and economic viability of replacing gas-based heat production with HTHPs and electric boilers was assessed, considering performance limitations (e.g., efficiency loss at high temperatures), availability of low-temperature heat sources, and electricity market dynamics.A key contribution is the evaluation of how current regulatory and market conditions—especially incentives favoring gas-based CHP—impact the competitiveness of electrified solutions. The thesis concludes by analyzing optimal HTHP sizing under various scenarios, considering CO₂ pricing, thermal demand, and plant dynamics.Findings suggest that, although technically feasible, electrification is significantly influenced by regulatory and economic frameworks. The study highlights the importance of detailed modeling, realistic assumptions, and strategic alignment. It also reveals a broader issue: many industrial players lack the data infrastructure and planning needed to implement deep decarbonization. This work provides a replicable methodology and valuable insights for engineers, operators, and policymakers committed to reducing industrial carbon emissions.