DOCTORAL DEGREE IN AGRI-FOOD TECHNOLOGY AND BIOTECHNOLOGY

• SOLER CAMPRECIÓS, JORDI: AVALUACIÓ DELS REQUERIMENTS REPRODUCTIUS I DEL CONTROL QUÍMIC DE L’AILANT (AILANTHUS ALTISSIMA), COM A ESPÈCIE INVASORA D’ESPAIS NATURALS
  
  Author: SOLER CAMPRECIÓS, JORDI
  Programme: DOCTORAL DEGREE IN AGRI-FOOD TECHNOLOGY AND BIOTECHNOLOGY
  Department: Department of Agri-Food Engineering and Biotechnology (DEAB)
  Mode: Normal
  Deposit date: 13/07/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: IZQUIERDO FIGAROLA, JORDI
  Thesis abstract: Invasive plants, such as Ailanthus altissima, cause damage to biodiversity due to their high capacity for expansion and establishment. A thorough understanding of the reproductive traits of this species is essential to define eradication strategies based on effective control methods.During the literature review, insufficient information was found regarding chemical methods to break seed dormancy, resulting in low germination rates. Conversely, other studies have shown that alternating temperature regimes promote germination. However, this method involves temperature accumulation that is not compatible with base temperature experiments. The base temperature for seeds or roots has never been determined, and only a few studies have addressed the base water potential of seeds, all conducted outside our region. From the base temperature, predictive germination models can be developed—a task we included in this study to create tools that assist in planning future management actions for this invasive species.The results showed a low response in dormancy release across different treatments, with the best germination achieved through cold stratification at 10 °C for 21 days. The base temperature for seeds and roots was very similar, and under water stress conditions, both seed germination and root sprouting decreased.We focused on evaluating the effectiveness of commercially available herbicides at the time of this study. Different application periods, herbicides, and techniques were tested. Herbicide application provided better control compared to untreated trees. The most effective technique was cut-stump injection, and the most efficient herbicides were triclopyr combined with 2,4-D and/or aminopyralid. The effect of flazasulfuron on Ailanthus altissima was evaluated for the first time, showing satisfactory results.We also identified, for the first time in Catalonia, the eriophyid mite Aculus taihagensis, a species already reported in other countries as a potential biological control agent.In conclusion, Ailanthus altissima can be eradicated if the correct methods are used, while predictive models will assist managers in the management of eradication efforts.
  

DOCTORAL DEGREE IN APPLIED MATHEMATICS

• FACCIOTTI, BENEDETTA: Groupoids of local systems and decorated representations on marked bordered surfaces
  
  Author: FACCIOTTI, BENEDETTA
  Programme: DOCTORAL DEGREE IN APPLIED MATHEMATICS
  Department: School of Mathematics and Statistics (FME)
  Mode: Normal
  Deposit date: 13/07/2026
  Reading date: 20/10/2026
  Reading time: 18:00
  Reading place: Sala 327 SYMCREA, planta 3 de l'EPSEB, Campus Sud Join Zoom Meetinghttps://us06web.zoom.us/j/85064553889?pwd=hlFbcaUadWq4QQLS7FYGpUhbVNbUhH.1
  Thesis director: MAZZOCCO, MARTA | NIKOLAEV, NIKITA
  Thesis abstract: This thesis studies representations of fundamental groupoids of surfaces $\Sigma$ with boundaries, with values in $G:=\operatorname{GL}_n(\mathbb C)$, up to isomorphism. When no marked points are present on the boundary, the corresponding objects admit several equivalent descriptions: as linear local systems on $\Sigma$, as representations of the fundamental groupoid $\Pi_1 (\Sigma)$, as monodromy data, and as points of the associated character variety. The introduction of marked points on the boundary, motivated by the need to encode irregular singularities of meromorphic connections, has led to several generalizations of this Betti-type description in the literature. Although these approaches are generally understood to describe essentially the same mathematical objects, the precise relation between them has not yet been been formulated explicitly. Motivated by the broader programme of establishing a precise and conceptually coherent relationship between the existing approaches to the representation-theoretic description of irregular singularities of meromorphic connections, in this thesis we develop a categorical framework for the definition of decorated Betti objects associated with marked bordered surfaces encoding higher-order poles, in a form designed to specialize to the different points of view encountered in the literature.
  
• ORTEGA SÁNCHEZ COLOMER, MIQUEL: Arithmetic patterns in unstructured sets
  
  Author: ORTEGA SÁNCHEZ COLOMER, MIQUEL
  Programme: DOCTORAL DEGREE IN APPLIED MATHEMATICS
  Department: School of Mathematics and Statistics (FME)
  Mode: Normal
  Deposit date: 17/07/2026
  Reading date: 22/09/2026
  Reading time: 17:00
  Reading place: Sala d'Actes de l'FME, Edifici U, Campus SudEnllaç de la videotrucada: https://meet.google.com/jbq-uiua-zbi
  Thesis director: SERRA ALBO, ORIOL | RUE PERNA, JUAN JOSÉ
  Thesis abstract: The main goal of this thesis is to present a number of extremal results in additive combinatorics. In lay terms, we study questions related to the appearance of a certain arithmetic pattern in a set based on its size. We focus on two patterns, products and arithmetic progressions. In the first case, we solve the density problem for product-free sets in the free group, and study several quantitative questions regarding a multiplicative analogue of Schur's theorem. In the second case, we prove a canonical van der Waerden theorem in random sets of integers, and improve existing counting results for the number of sets of integers free of arithmetic progressions of a given length. Two recurrent themes are the use of probabilistic arguments and the hypergraph container method.
  

DOCTORAL DEGREE IN ARCHITECTURAL DESIGN

• BELLAFIORE, GASPARE: Résidence Le Parc à Meudon-la-Forêt. Tectónica y decoro urbano en la obra de Fernand Pouillon.
  
  Author: BELLAFIORE, GASPARE
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL DESIGN
  Department: Department of Architectural Design (PA)
  Mode: Normal
  Deposit date: 13/07/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: PEÑIN LLOBELL, ALBERTO
  Thesis abstract: This research examines the relationship between compositional procedures and construction methods in the architecture of Fernand Pouillon, taking the complex of Résidence Le Parc in Meudon-la-Forêt (1959-1962) as a paradigmatic case study. The study begins with a diagnosis of the condition of contemporary architecture, marked by a growing fracture between the act of designing and the act of building. It notes a drift toward a production that entrusts its expressiveness to the image, the authorial gesture, or technical sophistication rather than to the internal reasons of the work. Faced with this displacement, the research recovers the concept of tectonics—not as a stylistic category or a synonym for technicality, but as the syntax through which construction becomes architectural language. It argues that Pouillon's work in Meudon-la-Forêt constitutes a privileged material verification of this hypothesis. The theoretical framework articulates two critical traditions often treated separately: Anglo-Germanic tectonic analysis (Bötticher, Semper, Sekler, Frampton) and the Latin theory of analogical decorum developed in France by Quatremère de Quincy and Julien Guadet. The research argues that a conjunction of both is necessary to read Pouillon's work, reconstructing the genealogy of French constructive rationalism—from Philibert de l'Orme to Auguste Perret—as the cultural horizon that makes his choices intelligible. In this reading, Pouillon emerges not as an exception within post-war modernity, but as a "transformative continuator": an architect who reactivates the French classical tradition and translates it to the operational conditions of reconstruction and mass social housing. The work is structured into three parts. The first reconstructs the theoretical framework of tectonics. The second traces the cultural genealogy of Pouillon's thought and analyses the operational context of post-war Paris. The third part develops a multiscalar analysis of Résidence Le Parc, covering the problems of the framed wall, stone as a tectonic and ethical core, the travée as a device of order. The study reaches four main theses:First: The hybrid construction system of Meudon—load-bearing Fontvieille stone articulated with reinforced concrete slabs—is not a technical compromise, but a new tectonic synthesis that reactivates the logic of load-bearing mass under conditions of industrial prefabrication. Second: The travée functions in Meudon as a "total operator" of the project, simultaneously coordinating construction logic, facade composition, and interior spatial organization, extending to the urban scale as the rhythm of public space. Third: Decorum in Pouillon does not respond to the strict truth of the Perretian frame, but to a "lithic verisimilitude" (vraisemblance)—an expressive adequacy between form, construction, and civic character—that reformulates Quatremère’s principle of analogical decorum for modern conditions. Fourth: The civic dimension of the work is not an ethical supplement added to formal decisions, but the direct effect of the construction grammar itself assumed as a shared language. The research is based on specialized critical bibliography (Lucan, Bonillo, Ferlenga, Sayen), primary sources from Pouillon’s archives, heritage documentation from the French Ministry of Culture, and direct measurements taken in the municipal archives of Meudon-la-Forêt. Its main contribution consists of articulating tectonic analysis and the theory of decorum within a single analytical device, proposing a systematic reading of the travée as the syntactic atom of the project, and defending the relevance of Pouillon’s lithic lesson for the contemporary debate on civic architecture and collective housing.
  

DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING

• RIVERA TORRES, PEDRO JUAN: Complex Engineering Systems: Expanding the Bioengineering Toolset with Biomimetic and Complexity Science-Based Solutions to Engineering Problems.
  
  Author: RIVERA TORRES, PEDRO JUAN
  Programme: DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING
  Department: Department of Automatic Control (ESAII)
  Mode: Article-based thesis
  Deposit date: 13/07/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: KANAAN IZQUIERDO, SAMIR
  Thesis abstract: This dissertation will seek to expand the toolset available for the solution of problems in engineering using probabilistic Boolean networks (PBN), a modeling methodology used mainly for analyzing Gene Regulatory Networks (GRN). Its purpose is validating their benefits as mechanisms of problem solving in engineering; general machine learning, reinforcement learning and fault detection and isolation in generation and transmission/distribution of electrical power and in manufacturing systems. The use of PBNs has been validated before as a mechanism of modeling of manufacturing processes and smart power. Modeling of systems using PBNs allows to construct models of multiple systems, know their respective failure modes, and incrementing their robustness using reinforcement learning to predictively react to faults and failures. We present the use of PBNs as a model constructing mechanism to determine the reliability of engineered systems and processes, and control of their evolution using machine learning. These models will enable us to study the mechanics of failure in engineered systems, making them more robust. We also present a Learning Probabilistic Boolean Network model of a manufacturing system and a Smart-grid system that can learn to preserve a healthy system state, in a way inspired by Artificial Neural Networks, but without the training that these systems require, and allowing the system to avoid faults and failures.
  

DOCTORAL DEGREE IN BUSINESS ADMINISTRATION AND MANAGEMENT

• GOYZUETA MEJÍA, ZARELA MÓNICA: L'orientació de client a partir de l'experiència educativa: la perspectiva d'estudiants de pregrau a les universitats privades del Perú
  
  Author: GOYZUETA MEJÍA, ZARELA MÓNICA
  Programme: DOCTORAL DEGREE IN BUSINESS ADMINISTRATION AND MANAGEMENT
  Department: Department of Management (OE)
  Mode: Normal
  Deposit date: 08/06/2026
  Reading date: 18/09/2026
  Reading time: 12:00
  Reading place: ETSETB- UPC, Aula B3 Teleensenyament Enllaç públic: meet.google.com/ipt-evpc-xzc
  Thesis director: CONSOLACION SEGURA, CAROLINA MARIA | BARREDO IBAÑEZ, DANIEL
  Thesis abstract: Neoliberalism, as a model of global governance, has promoted competition and market efficiency as pillars of economic and social progress. Its influence has permeated various sectors, and higher education has been no exception. In this sphere, this ideology has driven the emergence of marketization, a trend that conceives of the education system under a supply and demand model, where education is understood as a good or service that can be acquired, and whose value is measured primarily by the economic return it generates for the individual and its contribution to the economy as a whole.In this context, the metaphor of the student as customer arises, a concept of business origin that positions the student as the central consumer of an experiential educational service, aimed at providing them with a satisfactory academic foundation for their professional development.This phenomenon has generated extensive debate in literature, with arguments both for and against. However, existing research has not delved deeply into educational experience as a determining variable in shaping the profile of the student as client. Furthermore, most studies have focused on Europe and the United States, leaving Latin America—and particularly Peru—as a largely unexplored context.Within this framework, the purpose of this doctoral thesis is to analyze how client orientation is shaped in undergraduate students at private universities in Peru, considering the dimensions of their educational experience, the influence of demographic variables, and the perspective of academic experts. To this end, a mixed-methods approach was adopted.First, a systematic literature review on the student as customer metaphor (2000–2022) was conducted in the Scopus and Web of Science databases, identifying 83 studies that met the eligibility criteria. Second, the SCOQ (Student Customer Orientation Questionnaire) scale by Koris and Nokelainen (2015) was adapted to the Peruvian context, and 798 surveys were collected from three private universities. The data were analyzed using exploratory factor analysis, which identified the dimensions of the educational experience that define customer orientation in Peruvian students. Subsequently, a multiple regression model was applied to assess the influence of demographic variables. Finally, the results were triangulated with 12 in-depth interviews with academic experts to corroborate and enrich the findings.The research results reveal four main findings. First, the literature is structured around two predominant approaches: a critical perspective, focused on the risks of commodification and the weakening of academic rigor, and a relational perspective, which conceives of the student as a co-producer of the educational service. Second, adapting the SCOQ instrument to the Peruvian context allowed, through exploratory factor analysis, the identification of five factors of the educational experience. In four of these factors, students exhibit a client orientation. In contrast, positive self-demand is the only factor in which this orientation is not observed, highlighting the hybrid and multidimensional nature of the Peruvian student, who combines service demands with academic responsibility. Third, the multiple regression analysis, while having limited explanatory power, showed that some demographic variables have predictive value, with years of study standing out as the most influential factor. Finally, the triangulation with experts showed that teachers adopt a conditional acceptance stance, in which they recognize certain expectations inherent in a service logic on the part of students, but subordinate their validity to the preservation of academic rigor and teacher autonomy.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• KALLINGER, MAGNUS DANIEL: Layout Optimization in Floating Offshore Wind with Focus on Subsea Components
  
  Author: KALLINGER, MAGNUS DANIEL
  Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Normal
  Deposit date: 06/07/2026
  Reading date: 02/10/2026
  Reading time: 11:00
  Reading place: UPC Campus Nord, ETSECCPB, C/ Jordi Girona 1-3, edificio C1, Sala 002, Barcelona
  Thesis director: DOMÍNGUEZ GARCÍA, JOSÉ LUIS | TRUBAT CASAL, PAU
  Thesis abstract: Floating offshore wind is regarded as a key technology for exploiting deep-water wind resources where bottom-fixed foundations become economically uncompetitive. Yet, large-scale floating wind deployments remain constrained by high cost, limited maturity, and strong multidisciplinary coupling among subsystems that jointly determine farm feasibility and performance. Subsea components are central to this coupling: station-keeping systems and dynamic/static power cables govern not only structural response and electrical performance, but also impose first-order constraints on wind-farm design (turbine placement, anchoring footprints, cable topology and routing corridors). In addition, the limited practicality of subsea instrumentation motivates monitoring strategies that can reduce O&M burden and support condition-based operation. In this context, this thesis addresses layout optimisation for floating wind with a focus on subsea components. The thesis is organised around three research lines, aligned with the subsequent contribution chapters. First, it develops an early-stage optimisation framework for station-keeping design that combines computationally efficient frequency-domain simulations with customised particle swarm optimisation to screen large design spaces (layouts, materials, and ancillary components). The framework is applied both to conventional floating wind platforms and to a single-point moored weathervaning concept. Second, it investigates virtual sensing for floating wind turbines to estimate critical mooring and structural loads from accessible measurements, motivated by the high installation and maintenance effort of subsea sensors and by the need for scalable monitoring. Third, it advances floating wind inter-array design through (i) farm-level topology optimisation that incorporates floating-specific cable length effects and techno-economic performance, and (ii) physically informed routing that explicitly accounts for floater offsets, mooring-cable interaction constraints, touchdown feasibility, and three-dimensional bathymetry. The results show, first, that early-stage station-keeping optimisation can be carried out efficiently while producing technically meaningful and cost-effective designs, and it highlights the importance of line-specific functionality, substructure type, and site-dependent choices. Second, the virtual sensing studies demonstrate that critical loads can be estimated with useful accuracy and improved robustness when physical structure is embedded into the learning process, enabling reduced reliance on subsea instrumentation. Third, in the electrical domain, the proposed topology and routing methods improve the physical consistency and feasibility of floating wind cable layouts and yield measurable reductions in cable length and investment cost, which propagate to lower levelized cost of energy. Relative improvements are modest, but the absolute savings become significant at farm scale.
  
• MONTERO VEGA, MARIANA: Joint Operations of Autonomous Delivery Robots and Mobile Micro Hubs: A Continuous-Approximation and Game-Theoretic Assessment for Urban E-Commerce Logistics
  
  Author: MONTERO VEGA, MARIANA
  Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Article-based thesis
  Deposit date: 03/07/2026
  Reading date: 08/09/2026
  Reading time: 11:00
  Reading place: UPC Campus Nord, ETSECCPB, C/ Jordi Girona 1-3, edific C2, Sala 212 (Sala Conferències), Barcelona
  Thesis director: ESTRADA ROMEU, MIGUEL ANGEL
  Thesis abstract: Last-mile logistics is one of the most resource-intensive and externality-generating segments of urban freight systems, yet market forces consistently fail to align private incentives with social objectives. This thesis investigates the conditions under which Autonomous Delivery Robots can serve as a catalyst for a more sustainable and equitable urban logistics paradigm, examining the problem through the Desirability-Feasibility-Viability framework across four interconnected studies.On the desirability side, a global survey of 1,344 e-commerce users across Europe, Asia, and North America reveals that acceptance of ADRs is real but structurally uneven. Socio-demographic factors, particularly gender, age, and urbanity shapes delivery preferences in ways that have direct implications for infrastructure design and deployment strategy. Parcel lockers emerge as the most preferred delivery modality globally, a finding that motivates their inclusion as a full market participant in the subsequent viability analysis. A multi-regional acceptance study combining structural equation models with an ordered logit model identifies perceived competence as the central mediating variable driving behavioral intention across all regions, while revealing that risk sensitivity and price barriers are significant only in markets where ADRs have not yet achieved commercial deployment. On the feasibility side, the moving micro hub (MMH) concept, a two-echelon system combining Autonomous Hub Vehicles with ADRs is introduced and evaluated through a continuous approximation model across multiple urban demand scenarios. The system reduces delivery costs by 40–55% relative to business-as-usual (BaU) while significantly lowering global warming potential, with ADR body capacity emerging as the dominant cost lever and operational speed as essentially irrelevant. User-derived design constraints from the desirability studies including robot height preferences, multi-compartment design, and off-peak delivery windows are incorporated directly as operational parameters, establishing a quantitative link between stated user preferences and system cost structure.On the viability side, a two-stage game-theoretic model demonstrates that cooperation among business-as-usual, moving micro hub, and parcel locker operators never emerges endogenously under market conditions: the ε-core is strictly positive across all Monte Carlo simulations when there is little to no taxation , establishing that public subsidy is a structural necessity rather than a transitional feature. A Stackelberg regulatory layer shows that Pigovian and diversified tax schemes achieve near-subsidy-free coalition stability at substantially lower fiscal effort than flat entry tolls, while producing fairer profit distributions and maintaining the viability of all three operators. Critically, the minimum subsidy required is shown to be substantially smaller than the monetized externality savings generated by the demand shift toward cleaner technologies, reframing public investment in coalition support as a fiscally efficient instrument for urban sustainability rather than a transfer to private operators. Taken together, the findings establish that the future of last-mile logistics will not be decided by technology alone. ADRs are operationally viable and environmentally beneficial, but their transformative potential depends on the willingness of regulators to price externalities, of system designers to align operational parameters with real user needs, and of policymakers to accept that stable cooperation among heterogeneous operators is a governance achievement, not a market outcome.
  

DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS

• GARÍ GALÍNDEZ, JON: Developing Artificial Intelligence Strategies to Accelerate Scientific Research: Application to Thin-Film Photovoltaic Technologies
  
  Author: GARÍ GALÍNDEZ, JON
  Programme: DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS
  Department: Department of Physics (FIS)
  Mode: Article-based thesis
  Deposit date: 13/07/2026
  Reading date: 14/09/2026
  Reading time: 10:00
  Reading place: Edifici A, 1a planta, aula A1.07Campus Diagonal-Besòs – UPCAv. d'Eduard Maristany, 1608930 Sant Adrià de Besòs (Barcelona)
  Thesis director: IZQUIERDO ROCA, VICTOR | GUC, MAXIM
  Thesis abstract: The development cycle of new materials-based technologies typically spans 15-25 years due to the constantly increasing complexity of experimental research processes. Accelerating this process is essential to enable large-scale implementation of sustainable technologies that support the green energy transition and secure the electrification of society. Photovoltaics (PV) play a central role in this transition, particularly novel thin-film photovoltaic (TFPV) technologies, which promise to significantly broaden the application of solar modules in everyday life. Therefore, accelerating their development and transfer is key to achieving this goal. In this context, recent advances in artificial intelligence (AI), explainable artificial intelligence (XAI), robotics, and automation have enabled a new paradigm: the data-driven materials science, capable of accelerating materials discovery and optimization. However, despite the increasing use of machine learning (ML) in materials science, the application of XAI approaches to real experimental characterization datasets remains limited, and the translation of ML model outputs into physically meaningful insights is still a major challenge.The present work addresses this challenge by exploring and developing AI-driven strategies for the analysis and interpretation of experimental characterization data, following a proposed interpretability framework aimed at both accelerating research and enhancing explainability of ML models. The work begins by implementing and optimizing different training strategies for restricted Boltzmann machines (RBMs) using benchmark datasets. This study is aligned with the first level of the interpretability framework (Level 1: Using AI) and establishes the basis for the implementation of ML algorithms in experimental characterization datasets. Subsequently, an initial approach to XAI-driven strategies for extracting valuable information from experimental characterization data of kesterite-based TFPV devices is developed (Level 2: Using XAI), demonstrating the potential of interpretable ML models for identifying correlations between the physicochemical properties of materials and the PV performance of devices.Finally, building on this progression, an integrated XAI-driven methodology is implemented to analyze multimodal datasets obtained from holistic characterization of kesterite-based solar cells. It integrates the entire research cycle, from synthesis and characterization to data analysis, interpretation, and extraction of valuable feedback for further technology optimization. Particular emphasis is placed on interpretability, where the combination of intrinsic XAI models with post-hoc XAI techniques enables the identification of the physicochemical properties that govern device performance and reproducibility, linking the relevant spectral zones with the corresponding physical properties. This strategy reaches the third level of the interpretability framework (Level 3: Using XAI+) and provides meaningful feedback to guide subsequent research cycles. This feedback is validated through modified fabrication processes, resulting in improved device performance. Furthermore, it substantially reduces research cycle times, accelerating material optimization from timescales exceeding one year to less than a week. These results contribute to the development of self-driving laboratory (SDL) approaches and the advancement of data-driven materials research, ultimately supporting the green energy transition.
  

DOCTORAL DEGREE IN ELECTRONIC ENGINEERING

• GARCÍA LIMÓN, JOSÉ ALBERTO: Diseño e implementación de un sistema de medida no invasiva de parámetros cardiovasculares en calzado
  
  Author: GARCÍA LIMÓN, JOSÉ ALBERTO
  Programme: DOCTORAL DEGREE IN ELECTRONIC ENGINEERING
  Department: Department of Electronic Engineering (EEL)
  Mode: Change of supervisor
  Deposit date: 29/06/2026
  Reading date: 03/09/2026
  Reading time: 11:00
  Reading place: Auditorio del departamento de Ingeniería Eléctrica del CINVESTAV, México
  Thesis director: CASANELLA ALONSO, RAMON | ALVARADO SERRANO, CARLOS
  Thesis abstract: Cardiovascular diseases remain the leading cause of mortality worldwide, driving the development of technologies for continuous monitoring. Among the most relevant biomarkers are heart rate (HR), heart rate variability (HRV), and pulse transit time (PTT), which is closely related to arterial stiffness and blood pressure. However, accurate estimation of PTT in wearable devices remains a challenge, mainly due to the difficulty of obtaining proximal references unaffected by the cardiac pre-ejection period (PEP).This thesis proposes a novel approach for cardiovascular monitoring based on plantar acquisition of physiological signals through sensors integrated into a shoe insole. A measurement system based on a piezoelectric sensor in the heel region was developed to capture the ballistocardiogram (BCG), a mechanical signal associated with blood ejection. Widely accepted physiological models relate its morphology to pressure gradients in the aorta, enabling the extraction of both proximal and distal information along the aortic segment. The proposed system was validated against the standard weighing scale BCG and employed to estimate several cardiovascular parameters.In addition, a continuous wavelet transform (CWT)-based algorithm was validated for robust J-wave detection in BCG signals. Evaluated using multiple datasets with different sensors, body positions, and mechanical interfaces, it yielded the following sensitivity (Se) and positive predictive value (P+): chair (99.87% and 98.48%), bed (99.64% and 97.60%), and weighing scale (99% and 88%) over a total of 9,266 heartbeats, demonstrating robust performance for HR estimation. This behavior was also observed using the proposed plantar BCG system, achieving P+ and Se values of (97.07% and 84.85%) and (98.20% and 93.42%) during standing and seated conditions, respectively, with coverage factors above 95%. Furthermore, robust estimation of temporal HRV parameters was achieved in the seated position, and a significant correlation (r = 0.8, p < 0.001) was observed between the plantar BCG I–J interval and carotid–femoral pulse transit time, suggesting its potential as an indirect marker of arterial stiffness.As a complementary approach, this work explored impedance plethysmography (IPG) for distal pulse arrival time (PAT) detection at the foot. Results showed that, although photoplethysmography generally provides higher signal quality, its performance is more sensitive to sensor contact pressure and peripheral vasoconstriction. In contrast, the IPG enabled robust pulse detection under realistic operating conditions, including the presence of textile layers, making it particularly suitable for footwear-based systems.Finally, combining BCG and IPG signals enabled the estimation of whole-body pulse transit time (wb-PTT), showing a significant correlation (r = 0.72, p = 0.001) with the reference system based on carotid tonometry and photoplethysmography. This approach overcomes the limitations of conventional wearable devices based on short arterial paths and enables continuous, non-invasive cardiovascular monitoring compatible with daily activities. Overall, the results demonstrate the feasibility of a new generation of smart insoles. Integrating BCG and IPG into a single platform enables a comprehensive characterization of cardiovascular status and opens new opportunities for applications in digital health, preventive medicine, and remote clinical monitoring.
  

DOCTORAL DEGREE IN MARINE SCIENCES

• ERBS, FLORENCE AMANDINE: AI-enhanced Passive Acoustic Monitoring of Tropical Freshwater Environments
  
  Author: ERBS, FLORENCE AMANDINE
  Programme: DOCTORAL DEGREE IN MARINE SCIENCES
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 28/05/2026
  Reading date: 18/09/2026
  Reading time: 14:00
  Reading place: Place: ETSECCPBUPC, Campus NordBuilding C1. Classroom: 002C/Jordi Girona, 1-308034 Barcelona
  Thesis director: ANDRE SANCHEZ, MICHEL
  Thesis abstract: Tropical freshwater ecosystems, particularly in the Amazon basin, are among the world’s most vulnerable environments, facing escalating pressures from human activities such as overexploitation, pollution, and habitat degradation. Effective conservation efforts are constrained by the scarcity of long-term monitoring data, as traditional visual survey methods are often unsuitable for the high turbidity of Amazonian waters and the complex floodplain habitat mosaics where seasonally inundated lakes, channels, and forests make species detection challenging. This dissertation addresses these challenges by developing an innovative and scalable monitoring framework using Artificial Intelligence (AI)-enhanced Passive Acoustic Monitoring (PAM) focused on three ecological indicator species: the pink river dolphin (Inia geoffrensis), the tucuxi (Sotalia fluviatilis), and the Amazonian manatee (Trichechus inunguis).The research is presented as a compendium of two scientific publications that integrates longterm autonomous acoustic monitoring with Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), to automate species detection in complex and noisy freshwater soundscapes. The first study focuses on Amazonian river dolphins, exploiting their near-continuous production of echolocation clicks for presence detection. The developed CNN classifier achieved a high average precision of 0.95 and successfully discriminated between dolphin clicks and impulsive interferences like rain and boat engine noise. This automation enabled the tracking of synchronized seasonal movements into floodplain bay and river channel habitats following the annual flood pulse. Furthermore, the study provided rare insights into the seasonal use of flooded forests revealing regular dolphin presence during high-water periods. Additionally, it quantified the spatio-temporal overlap between dolphins and boat traffic, establishing a baseline for assessing anthropogenic noise exposure in core habitats.The second study applied a similar AI-enhanced approach for detecting the Amazonian manatee, a cryptic species characterized by inconspicuous surfacing behavior and a previously poorly described vocal repertoire in the wild. By training a CNN model on wild vocalizations, the research provided the first detailed characterization of the wild Amazonian manatee’s vocal repertoire, identifying four distinct call types, and leading to new insights into the vocal behavior of the species in the floodplains. The analysis of vocal parameters, including repetition rates and frequency characteristics, revealed that Mamirau´a Lake, where the species was presumed absent, serves as a critical nursery habitat.This dissertation demonstrates that the integration of PAM and machine learning offers a noninvasive, cost-effective, and performant tool for monitoring biodiversity in remote tropical freshwater environments. The transition from manual acoustic analysis to automated processing allows for efficient conversion of high-volume acoustic datasets into ecological insights, facilitating the identification of critical habitats, supporting the understanding of floodplain ecological processes, and advancing the assessment of anthropogenic impacts and ecosystem health. These findings provide a robust foundation for a standardized Amazonian monitoring framework to support evidence-based conservation for these endangered species and their ecosystems.
  
• MURILLO GOMEZ, NELSON ENRIQUE: COASTAL HAZARDS, RISKS AND ADAPTATION IN THE BARRA DE SALAMANCA (COLOMBIA)
  
  Author: MURILLO GOMEZ, NELSON ENRIQUE
  Programme: DOCTORAL DEGREE IN MARINE SCIENCES
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 16/07/2026
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: JIMENEZ QUINTANA, JOSE ANTONIO
  Thesis abstract: Coastal sandbars are generally elongated landforms that provide protection to environmental, socioeconomic, and infrastructural ecosystems from extreme events, but are highly sensitive to morphodynamic changes driven by natural and anthropogenic processes. This is further complicated by the uncertainty Surrounding the expected sea-level rise in the coming years. These dynamics generate pressures and motivate land managers to understand the genesis of their morphological evolution, the physical agents that modulate it, the risks associated with the diversity of their exposed ecosystems within a tolerance limit, and to propose sustainable adaptation measures for the future.This research reconstructs the morphological evolution of the Salamanca coastal sandbar (Colombia), located within a national and international conservation park, over the last 40 years, the physical agents present at decadal and episodic scales, and the assessment of threats associated with erosion and flooding. Understanding the past and considering sea level rise projections to 2050, a projected area susceptible to damage was identified. Within this area, the exposure and vulnerability of the exposed elements were assessed, and this, when integrated with the threats, allowed for the estimation of environmental, physical, and socioeconomic risks. Recognizing that risk cannot be eliminated because it is intrinsic to coastal development, we have proposed a model of tolerable risk levels and a list of adaptation measures grouped into strategies according to their implications for the coastal zone. The results showed that the sandbar is decreasing its sediment transport rates, indicating a search for morphological equilibrium. However, erosion rates of around -20 m/a at the most critical points are deteriorating environmental services. This, combined with storm impacts and the increasing construction of hard infrastructure, has worsened and increased the exposure of the main land-based infrastructure connecting the region's most important towns with the interior of the country. This is putting commercial and tourism activities at risk. The communities located in these areas are in highly vulnerable socioeconomic conditions, generating pressure on the coastline that requires urgent intervention. The tolerable risk for environmental, physical infrastructure, and socioeconomic factors was established according to the degree of impact on the exposed element, its loss of natural value, and the resulting repercussions on the quality of life of the inhabitants. This criterion facilitates a balance of sustainable development between the inhabitants and their environment. The risk reduction strategies demonstrated that acting alone does not achieve tolerable risks, and only a comprehensive strategy allows us to approach the proposed objectives. Prompt action is needed to reduce uncertainty and increase objectivity about the expected future. We conclude that the methodology developed allowed us to understand what has happened, why, under what conditions the threats have evolved, the morphological evolution, the risk typologies, what could happen, and how to reduce the probability of the expected changes. We believe this methodological process can be replicated and adapted to any coastal area with the specific characteristics required. keywords: morphology, risks, adaptation measures.
  

DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING

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

DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING

• BANDARRINHA MONTEIRO, CARLOS ALEXANDRE: Pseudo-Boiling Wall-Bounded Turbulence in Supercritical Flows: Direct Numerical Simulation & Flow Physics
  
  Author: BANDARRINHA MONTEIRO, CARLOS ALEXANDRE
  Programme: DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING
  Department: Department of Mechanical Engineering (EM)
  Mode: Article-based thesis
  Deposit date: 14/07/2026
  Reading date: 04/09/2026
  Reading time: 11:30
  Reading place: Sala Polivalent, Edifici A, Campus Diagonal-Besòs
  Thesis director: JOFRE CRUANYES, LLUÍS
  Thesis abstract: This thesis presents the development and application of a high-fidelity computational framework for the direct numerical simulation (DNS) of high-pressure transcritical turbulent flows. These flows, characterized by strong thermophysical property variations in the vicinity of the pseudo-boiling region, exhibit complex interactions between turbulence, thermodynamics, and transport processes that cannot be accurately captured using classical modeling approaches. The primary objective of this work is to advance both the numerical simulation tool and the physical understanding required to reliably simulate and analyze such regimes. To this end, the multiphysics flow solver, RHEA (Reproducible Hybrid-architecture flow solver Engineered for Academia), is redesigned into a GPU-resident version, RHEA-X. The solver combines low-dissipation spatial discretizations with strong-stability-preserving Runge–Kutta time integration and advanced thermodynamic and transport models, including real-fluid equations of state. Its modular, object-oriented design enables the treatment of compressible, high-pressure transcritical, particle-laden, and immersed-boundary flows within a unified framework. The implementation leverages MPI and OpenACC to achieve persistent GPU data residency and direct inter-device communication, enabling efficient execution on modern heterogeneous high-performance computing systems. Performance analyses demonstrate near-ideal strong and weak scaling and substantial reductions in time-to-solution relative to CPU-based implementations up to a large GPU count. Using this framework, the thesis first investigates the grid resolution requirements for DNS of high-pressure transcritical wall-bounded turbulence. It is shown that classical resolution criteria, developed for incompressible flows, are insufficient in the presence of strong thermophysical gradients. In particular, the pseudo-boiling region induces localized amplification of turbulence intensity and energy dissipation, requiring refined resolution to accurately capture up to second-order statistics. New resolution guidelines are proposed based on hydrodynamic and thermodynamic scaling arguments. The physical behavior of transcritical flows is then examined in microconfined square-duct configurations spanning subcritical to supercritical regimes. The results reveal that, under transcritical conditions, flows can transition from laminar to turbulence-like states without changes in geometry or bulk velocity scales, driven by strong density gradients associated with the pseudo-boiling region. This leads to significant amplification of velocity fluctuations, intensified secondary motions, and substantial enhancement of heat transfer. Finally, the role of buoyancy is analyzed in transcritical turbulent square-duct flows. It is demonstrated that buoyancy influences the flow primarily through the modulation of secondary motions, which act as the dominant mechanism for redistributing momentum and restructuring turbulence. The case-dependent interaction between buoyancy, thermophysical gradients, and secondary flows leads to strong spatial heterogeneity, non-equilibrium turbulence behavior, and, consequently pronounced variations in wall shear stress and transport processes.
  

DOCTORAL DEGREE IN NATURAL RESOURCES AND THE ENVIRONMENT

• MULERO JIMÉNEZ, LORENA: Bosc i Sostenibilitat: proposta educativa a l’entorn dels serveis ecosistèmics del bosc i els ODS amb pedagogia de ciència oberta a secundària
  
  Author: MULERO JIMÉNEZ, LORENA
  Programme: DOCTORAL DEGREE IN NATURAL RESOURCES AND THE ENVIRONMENT
  Department: Department of Mining, Industrial and ICT Engineering (EMIT)
  Mode: Normal
  Deposit date: 18/06/2026
  Reading date: 03/09/2026
  Reading time: 12:00
  Reading place: Sala de Juntes de l'EPSEM
  Thesis director:
  Thesis abstract: We live in a society that normalizes crises. These crises affect the very pillars of civilization, and education is the engine that moves the world. Furthermore, what would become of society and the education of new generations without caring for the environment and nature?This thesis develops a series of actions related to forests and their contribution to sustainability through their connection with the Sustainable Development Goals (SDGs). This is a process of raising awareness among secondary school students regarding their essential role in the journey toward a sustainable and respectful society. Likewise, it analyzes the impact of implementing the "Forest and Sustainability Project," applying the innovative teaching methodology known as Open Science Schooling. The study focuses on how this approach fosters students' awareness of their role as key agents in changing society and steering it toward sustainability.A case study is conducted using teaching materials created and developed within this thesis. The activities are implemented in secondary schools across Catalonia. Additionally, activities are carried out within the framework of the Exploratori dels Recursos de la Natura that aims to promote science and technology among youth and conducts activities addressed to both secondary school teachers and students.
  

DOCTORAL DEGREE IN NETWORK ENGINEERING

• KANJ BONGARD, SEBASTIEN: Contribution to the Systematic Study of Threat Actor Tools and Techniques in Real-World Cyber Incidents
  
  Author: KANJ BONGARD, SEBASTIEN
  Programme: DOCTORAL DEGREE IN NETWORK ENGINEERING
  Department: Department of Network Engineering (ENTEL)
  Mode: Normal
  Deposit date: 22/06/2026
  Reading date: 18/09/2026
  Reading time: 10:30
  Reading place: Aula C3-304a (Seminari de Telemàtica), Campus Nord
  Thesis director: PEGUEROLES VALLES, JOSEP RAFEL
  Thesis abstract: Cyber incident response and digital forensics (DFIR) research increas- ingly faces a tension between academic rigor and the operational re- alities of real-world investigations. While academic studies often rely on controlled datasets and synthetic scenarios, practitioners must oper- ate under time pressure, incomplete evidence, and strict confidentiality constraints. This doctoral research addresses that gap through an In- dustrial PhD program conducted in collaboration with Incide Digital Data S.L., which enabled access to real-world incident data and practi- tioner workflows while maintaining a rigorous scientific methodology. The thesis investigates how threat-actor tools, techniques, and behaviours can be systematically analyzed and transformed into reusable, vali- dated, and operationally meaningful artifacts. Three complementary research directions are explored. First, an integrated forensic methodol- ogy is proposed for the analysis of abused legitimate tools and mobile activity, combining tool-centric investigations with structured iOS ac- tivity characterization to support accurate reconstruction, automation, and legally robust analysis in real incident-response contexts. Second, the research develops a Business Email Compromise (BEC)-specific map- ping of Tactics, Techniques, and Procedures using the MITRE ATT&CK framework, addressing limitations of narrative-driven BEC reporting. The proposed matrix is validated against real-world cases and demon- strates improved behavioural comparison, clustering, and defensive alignment. Third, the thesis designs and empirically evaluates a YARA- based detection library targeting malware anti-analysis techniques, with a focus on anti-virtual machine and anti-sandbox behaviour, highlight- ing both the strengths and limits of static detection in operational con- texts. Across these contributions, the thesis demonstrates that behavioural and tool-based indicators provide durable defensive value and that hy- brid analytical pipelines are necessary to address modern evasive threats. 6 By grounding methodological innovation in industrial practice, this work advances DFIR towards more systematic, reproducible, and operationally relevant research, supporting faster investigations and more consistent defensive decision-making.
  

DOCTORAL DEGREE IN NUCLEAR AND IONISING RADIATION ENGINEERING

• TOBAJAS ASENSIO, LUIS MIGUEL: ANÁLISIS DE LA INFORMACIÓN INSTITUCIONAL Y EL TRATAMIENTO DE LA PRENSA DE LOS INCIDENTES NUCLEARES ESPAÑOLES (1989-2009)
  
  Author: TOBAJAS ASENSIO, LUIS MIGUEL
  Programme: DOCTORAL DEGREE IN NUCLEAR AND IONISING RADIATION ENGINEERING
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 17/06/2026
  Reading date: 18/09/2026
  Reading time: 11:30
  Reading place: Aula I 28.8 de l'Escola Tècnica Superior d'Enginyeria Industrial de Barcelona, ETSEIB
  Thesis director: REVENTOS PUIGJANER, FRANCESC-JOSEP | PONT SORRIBES, CARLES
  Thesis abstract: The general objective of this research is to analyze the safety of the nuclear power plants in Spain during the period between 1989 and 2009, through a comprehensive analysis of institutional information and press coverage of nuclear incidents.The methodology employed includes a mixed qualitative and quantitative model. Scientific production on nuclear incidents has been analysed through technical information databases, academic databases (Wos and Scopus), and newspaper archives.The newspapers ABC, La Vanguardia, and El País were selected based on the criterion of being among the most widely followed newspapers in Spain during the period studied, considering the press as the best means of monitoring incidents at the end of the 1980s.In 1990, following the Chernobyl accident, the INES Scale was introduced, created by the International Atomic Energy Agency (IAEA) and the Nuclear Energy Agency, with the aim of facilitating international communication to the public and the media. This study analyses incidents classified as level two or higher according to IAEA criteria. The results of this work consider the use of the INES Scale in institutional information and in the media.The conclusions allow for a deeper understanding of the treatment of information provided to the public and the media coverage of nuclear incidents. The analysis of lessons learned from the four incidents studied and their follow-up makes it possible to conclude that there have been advances in nuclear safety and in institutional and public information, with the consolidation of the INES Scale in nuclear communication in Spain. However, it is determined that the completion of corrective actions does not reach public opinion despite its relevance.The research provides proposals for improvement with the aim of promoting better communication in the future, including the participation of experts. Communication is one of the most relevant issues in nuclear crises and must be clear, timely, accurate, transparent, and proactive.
  

DOCTORAL DEGREE IN PHOTONICS

• PINILLA SANCHEZ, ADRIAN: Advanced Catalytic Interface Analysis Through In Situ Studies and Automated Experimental Platforms
  
  Author: PINILLA SANCHEZ, ADRIAN
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 08/07/2026
  Reading date: 07/09/2026
  Reading time: 15:00
  Reading place: ICFO Auditorium i https://teams.microsoft.com/meet/393968795433086?p=iOTHwY4gw6m1ZfoLbp
  Thesis director: GARCÍA DE ARQUER, FRANCISCO PELAYO
  Thesis abstract: Electrochemical technologies offer a route to decarbonize key industries, such as energy, chemical and fertilizer manufacturing, by converting abundant chemicals like carbon dioxide (CO₂) and nitrate into fuels and feedstocks using renewable electricity. Realizing this potential requires electrocatalytic systems that achieve technoeconomic viability, which is linked to performance metrics such as activity, selectivity, and stability. Their deployment is constrained by two coupled challenges: incomplete mechanistic understanding of dynamic electrochemical interfaces and slow manual workflows that cannot efficiently explore the high-dimensional design spaces of catalysts, electrolytes, and operating parameters. In electrochemical reactions, performance across its many dimensions emerges from the evolving interplay of catalyst structure and local reaction environment at polarized interfaces. Advancing electrocatalytic performance therefore requires tools that can both reveal and enable control over the evolving catalyst-electrolyte interface during operation. This thesis addresses these challenges by combining operando surface-enhanced Raman spectroscopy (SERS), automated data-analysis frameworks, and self-driving laboratory approaches to accelerate electrocatalyst development under technologically relevant conditions for CO₂ and nitrate electroreduction reactions.Operando SERS probes acidic CO₂ electroreduction on copper-based gas diffusion electrodes up to 0.2 A cm⁻², showing how interfacial species like sulfate, hydroxide, carbon monoxide (CO), and carbon-containing intermediates evolve with potential and pH. Our findings suggest that strongly adsorbed sulfate blocks active sites and delays CO₂E onset at low overpotentials, while co-adsorbed hydroxide and carbon on reconstructed copper surfaces stabilize *CO coverages that favor C-C coupling and multicarbon product formation. These results identify electrolyte anions and local alkalization as key levers for tuning the onset potential, intermediate stabilization, and selectivity in acidic CO₂ electroreduction, opening new strategies for rational system-level design of catalysts and electrolytes.To handle the complexity of operando experiments, the thesis introduces SERSFlow, a modular framework for structured operando SERS data and reusable analysis pipelines. Implemented as a local-first Python service with a web interface, it combines preprocessing, feature extraction, and multivariate analysis in deterministic workflows that reproduce expert trends while reducing analysis time from hours to minutes. Benchmarking shows that baseline subtraction alone can shift fitted peak areas by 40–100% for weak or overlapping bands, and spatiotemporal mapping reveals micron-scale heterogeneity in adsorbate populations and double-layer structure.Finally, the Autoammonia platform—a distributed self-driving laboratory for nitrate-to-ammonia reduction—is developed with two active nodes in different institutions. It integrates in situ catalyst electrodeposition, flow-cell nitrate electroreduction, and automated ammonia quantification within a closed-loop workflow managed by orchestration, planning, and safety software. Autonomous campaigns with copper-based catalysts show that self-driving experimentation is feasible in realistic flow-cell architectures and complex electrolytes using accessible hardware and open-source software.Collectively, the thesis shows that mechanistic operando characterization, reproducible data workflows, and autonomous experimentation are mutually reinforcing components of a coherent strategy for advancing electrocatalysis. The concepts and tools developed here provide a foundation for more systematic, data-rich, and scalable approaches to the design and optimization of electrocatalysts and electrochemical interfaces for sustainable, electrified chemical production.
  
• PRELAT OLIVARES, LEILA ROCIO: Free-electron interaction with nanophotonic excitations
  
  Author: PRELAT OLIVARES, LEILA ROCIO
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 07/07/2026
  Reading date: 10/09/2026
  Reading time: 10:00
  Reading place: ICFO Auditorium i https://teams.microsoft.com/meet/322181711925000?p=OtJ34OjGTLMTdTXLs6
  Thesis director: GARCÍA DE ABAJO, JAVIER
  Thesis abstract: Free electrons provide a powerful platform to control optical excitations at the nanoscale because they carry electromagnetic fields that are tightly localized and contain large evanescent wave-vector components inaccessible to propagating light. Although this property makes electron beams uniquely suited to address confined optical modes, their full potential for technological applications is still being actively developed. This Thesis aims to contribute to this effort by exploring novel phenomena that arise when electron beams are incorporated into different optical systems.As an introduction to the main concepts underlying this Thesis, Chapter 1 summarizes the theoretical frameworks used to describe electromagnetic excitations, with emphasis on linear and nonlinear optical phenomena, surface waves such as polaritons and waveguide modes, and electron beams.Chapter 2 explores electron-driven excitation of surface polaritons through resonant scatterers placed near polariton-supporting materials. The passing electron polarizes a small resonant particle, which then launches surface modes with a spectrum determined by the particle’s response. Our semi-analytical model reveals an optimum scatterer-surface separation that maximizes polariton emission. This approach is extended to periodic arrays of scatterers, leading to a polaritonic analog of the Smith-Purcell effect, in which surface polaritons are emitted directionally into diffraction orders controlled by the array period, electron velocity, and polariton dispersion relation. Hexagonal boron nitride nanodisks coupled to graphene plasmons are identified as a realistic mid-infrared implementation for small resonant scatterers, with efficiency comparable to resonant lossless particles.In Chapter 3, we introduce wave-mixing cathodoluminescence as a nonlinear spectromicroscopy technique for detecting low-frequency excitations through visible-range optical readout. In this mechanism, the evanescent field of a swift electron mixes with an external optical pump through the second-order nonlinear response of a specimen, generating sum- and difference-frequency photons. The method up-converts far-infrared spectral fingerprints into the visible range, avoiding the need for low-frequency light sources or detectors. Calculations for retinal-coated silver nanorods show that molecular vibrational signatures can be accessed with nanometer-scale spatial resolution under external illumination and visible-range detection.Chapter 4 explores electrostatic control of electron trajectories as a means of tuning coupling to guided modes in silicon waveguides. By deflecting electrons into grazing trajectories using a static electron-repulsive field, the minimum electron-waveguide separation becomes a controllable parameter that governs both coupling strength and modal selectivity. In particular, we consider three doped silicon waveguides placed on a sapphire substrate, with the two side elements acting as lateral gating structures. Including image-force effects and collision thresholds, the analysis predicts voltage-tunable photon yields reaching several photons per electron in realistic integrated photonic geometries.In Chapter 5 cylindrical waveguides are studied as mediators between free electrons and nanoscale absorbers. A gate-controlled grazing electron launches a guided wave packet that subsequently drives a nearby resonant particle. This waveguide-mediated channel concentrates the broadband electron field spectrally and spatially, producing strong absorption enhancements relative to direct bare-electron excitation.In summary, this Thesis establishes free-electron-nanophotonic interactions as a versatile platform for nanoscale excitation, spectroscopy, and control of optical, polaritonic, and guided modes, with potential applications in integrated photonics, molecular sensing, and quantum nanophotonics.
  
• RUÍZ GONZÁLEZ, JOSÉ JAVIER: Development of computational tools and pipelines for enhanced interpretation of Raman spectroscopy in biomedical applications
  
  Author: RUÍZ GONZÁLEZ, JOSÉ JAVIER
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 07/07/2026
  Reading date: 14/10/2026
  Reading time: 10:00
  Reading place: ICFO Auditorium
  Thesis director: LOZA ALVAREZ, PABLO
  Thesis abstract: Raman spectroscopy has gained increasing attention over the last few decades due to its ability to non-destructively extract chemical information from samples. However, despite advances in instrumentation, it has not yet become standard practice in the biomedical field. One of the main reasons is the difficulty in interpreting and extracting the chemical information encoded in Raman signal, so as to validate the technique using complementary, well established techniques.Considering this, the aim of this Thesis is to develop tools and analytical pipelines that enhance the biochemical interpretation of Raman spectra, and to demonstrate its usefulness in two relevant biomedical research lines: breast cancer resistance to neoadjuvant treatments and the diagnosis of choroidal melanoma.Firstly, we developed and validated RamanBiolib, an open-source Raman spectral library accompanied by search algorithms, aimed at providing rapid and objective identification of biomolecules. Secondly, we used RamanBiolib after spectral unmixing to identify and quantify cytochrome c molecule in breast cancer cells resistant to neoadjuvant treatments. This revealed a shift towards its reduced state to avoid apoptosis and acquire drug resistance. Then we also characterized lipid droplets in triple-negative breast cancer cells, highlighting the relevance of variable importance analysis in classification models. This approach allows for the biochemical interpretation of their classification performance and assessing possible background contributions to their accuracy. By doing so, significant changes in lipid unsaturation were detected. Furthermore, we developed RamanTF, a transformer-based algorithm that automatically quantifies key biomolecules from raw spectra.Finally, to study melanin-rich samples, we defined a pre-processing and analysis workflow to correct instrumental interferences that were observed in previous studies, but not corrected yet. With this established workflow, key melanin properties were identified, such as melanin structural disorder or defects abundance, which can be used as biomarkers to diagnose choroidal melanomas. Overall, the tools, discussions, and results presented in this Thesis advance Raman spectroscopy towards clinical application and provide a basis for its widespread adoption as a routine technique in biomedical and diagnostic research.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• CARRINO, CASIMIRO PIO: Multilingual and Cross-Lingual Machine Reading Comprehension in Few-Resource Settings: Synthetic Data, Cross-Lingual Transfer, and Domain-Specific Evaluation
  
  Author: CARRINO, CASIMIRO PIO
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 06/07/2026
  Reading date: 04/09/2026
  Reading time: 12:00
  Reading place: Aula MERIT D5010, Campus Nord, Barcelona
  Thesis director: RODRIGUEZ FONOLLOSA, JOSE ADRIAN
  Thesis abstract: Machine Reading Comprehension (MRC) is a fundamental benchmark for evaluating natural language understanding systems, requiring models to generate answers grounded in context. Despite advances with transformer-based architectures and large language models (LLMs), challenges persist in multilingual and cross-lingual scenarios, especially under few-resource and domain-specific constraints. This thesis addresses these challenges through three principal contributions, spanning the progression from encoder-based extractive to generative MRC, and covering data regimes from large-scale in-language supervision to zero-shot cross-lingual transfer in domain-specific settings.The first contribution introduces the Translate-Align-Retrieve (TAR) methodology, which preserves answer span alignment during translation of extractive QA datasets. By integrating neural machine translation, unsupervised word alignment, and alignment-based answer retrieval, TAR enables systematic construction of high-quality multilingual training data for low-resource languages. This approach produced SQuAD-es v1.1, the first large-scale Spanish extractive QA dataset (87,599 question-answer pairs). Models trained on this resource achieve or surpass established baselines on Spanish QA benchmarks, demonstrating that alignment-based translation is effective for mitigating data scarcity.The second contribution develops a self-knowledge distillation framework with cross-lingual sampling to enhance transfer in few-resource settings with limited parallel data. This work addresses Cross-Lingual Transfer (XLT) and Generalised Cross-Lingual Transfer (G-XLT), where question and context are in different languages. The method integrates cross-lingual sampling as data augmentation with self-knowledge distillation as regularisation, introducing a mean Average Precision at k (mAP@k) coefficient to modulate distillation loss by teacher model quality. Evaluations on MLQA, XQuAD, and TyDiQA-GoldP demonstrate consistent improvements over standard fine-tuning, providing a robust alternative to machine translation-based augmentation when only limited parallel resources exist.The third contribution presents a semi-automatic methodology for constructing privacy-preserving multilingual QA benchmarks in sensitive, data-scarce domains, exemplified by the Human Resources (HR) domain with JobResQA. This combines data de-identification, LLM-based synthesis, and human-in-the-loop translation with MQM error annotations and post-editing. JobResQA comprises 105 synthetic résumé–job description pairs and 581 QA items across five languages and four question types. Baseline evaluation using the G-Eval LLM-as-judge metric across nine open-weight models reveals persistent cross-lingual challenges, with only the largest models attaining high accuracy across all languages. The methodology also enables bias and fairness investigations in high-stakes HR applications.Collectively, these contributions show that data scarcity, cross-lingual transfer, and domain specificity persist as central challenges across architectural paradigms, particularly in few-resource settings. All resources, including datasets, models, and code, are released as open-source. The TAR methodology has seen widespread adoption with over 100 citations, producing datasets for diverse languages and scripts. While performance has improved with LLMs, the core challenges addressed in this thesis remain central to advancing multilingual and cross-lingual MRC.
  
• TSIAMAS, IOANNIS: Robust and Data-Efficient End-to-End Speech Translation: Segmentation, Cross-Modal Alignment, and Prosody-Aware Evaluation
  
  Author: TSIAMAS, IOANNIS
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 15/05/2026
  Reading date: 18/09/2026
  Reading time: 15:00
  Reading place: Aula MERIT D5010, Campus Nord UPC, Barcelona
  Thesis director: RODRIGUEZ FONOLLOSA, JOSE ADRIAN | RUIZ COSTA-JUSSA, MARTA
  Thesis abstract: End-to-end (E2E) Speech Translation (ST) offers a streamlined alternative to traditional cascaded systems, promising lower latency and reduced error propagation. However, its adoption in real-world scenarios is currently hindered by three critical bottlenecks: input processing challenges (mismatch between static data and continuous audio), training data scarcity, and evaluation limitations regarding paralinguistic information.This dissertation addresses these limitations through a cohesive set of methodological and architectural innovations. First, we tackle the segmentation and input processing challenge. We introduce Supervised Hybrid Audio Segmentation (SHAS), a method that effectively bridges the gap between manual training segmentation and automatic inference segmentation, allowing E2E models to process continuous audio streams with minimal performance loss. Building on this, we propose SEGAUGMENT, a data augmentation strategy that utilizes training data re-segmentation to maximize the utility of existing datasets, significantly improving performance in low-resource settings.Second, we tackle data scarcity by developing methods for zero-shot speech translation through cross-modal alignment. We introduce ZEROSWOT, which leverages Optimal Transport to align speech encoders with massively multilingual machine translation models at the subword level, enabling translation without paired ST data. We further refine this approach with CHARSONAR, demonstrating that character-level modeling significantly improves cross-lingual and cross-modal transfer, achieving state-of-the-art results, despite being a zero-shot method.Finally, we investigate the semantic richness of E2E translations. We present a focused evaluation on prosody, revealing that while current E2E architectures possess the internal capacity to represent paralinguistic features like intonation and stress, they often fail to manifest these in the final translation.Collectively, these contributions advance the state of the art by creating E2E ST systems that are more robust to unsegmented inputs and more data-efficient, while also providing insights into the limitations of current E2E systems in preserving the nuances of spoken communication.
  

DOCTORAL DEGREE IN STRUCTURAL ANALYSIS

• GONÇALVES JUNIOR, LUIS ANTONIO: Modeling the influence of manufacturing processes on the fatigue behavior of metallic materials through a continuum damage-based constitutive framework
  
  Author: GONÇALVES JUNIOR, LUIS ANTONIO
  Programme: DOCTORAL DEGREE IN STRUCTURAL ANALYSIS
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 29/06/2026
  Reading date: 07/09/2026
  Reading time: 14:00
  Reading place: Sala Zienkiewich (CIMNE) Building C1, UPC - Campus North Gran Capitan S/N 08034 Barcelona
  Thesis director: BARBU, LUCIA GRATIELA | OLLER MARTINEZ, SERGIO HORACIO
  Thesis abstract: Since the mid-19th century, the study of fatigue in metals has become a major field of interest for materials scientists and structural engineers because fatigue represents one of the principal failure mechanisms in metallic engineering structures. Initially based on empirical approaches such as the stress amplitude–life (S–N) curves derived from Wöhler’s pioneering studies, fatigue prediction capabilities have evolved significantly, leading to sophisticated numerical models capable of predicting not only fatigue life but also the progressive degradation of material properties associated with the fatigue phenomenon, including crack initiation and propagation up to the complete failure of the component.Despite these advances, the systematic incorporation of manufacturing process effects —such as machining, forming, trimming, and punching— into fatigue formulations remains limited. Most existing approaches still rely on simple modifications of S–N curves through reduction factors, restricting their applicability mainly to coupon-level specimens and preventing the accurate prediction of crack initiation and propagation patterns.In this context, the present thesis proposes a constitutive framework to incorporate manufacturing-induced effects into the fatigue response of metals in the high-cycle regime. The model is formulated in a general manner, allowing different manufacturing processes to be considered through suitable specializations based on relevant process-related data, such as residual stresses, surface roughness, porosity, and defect volume fraction.To develop this framework, several fatigue modeling approaches are reviewed, with particular emphasis on fracture mechanics, continuum damage mechanics, and phase-field formulations, commonly implemented using numerical methods such as the finite element method and the extended finite element method. Among them, a continuum damage mechanics-based high-cycle fatigue model is selected as the baseline framework due to its high computational efficiency and its ability to model complex stress–strain states throughout the material degradation process, from the intact condition to complete failure.The constitutive framework is first enhanced through the introduction of a novel hardening–softening stress–strain curve for damage. In addition, a methodology to convert average-based S–N data obtained from standardized fatigue tests into local material-point information is proposed to ensure a consistent calibration of the fatigue parameters with the local nature of the formulation. The enhanced model is validated against experimental data from stiffness-based rapid fatigue tests and durability tests performed on real automotive components, demonstrating strong predictive capabilities at both coupon and component levels while maintaining high computational efficiency.Finally, the framework is extended to explicitly account for manufacturing-induced effects. A residual stress relaxation model and a formulation to account for notch effects associated with manufacturing operations are introduced. The resulting model is specialized for shear-cutting operations, such as trimming and punching, using residual stresses obtained from process simulations and measured surface roughness as process-related inputs. The formulation is validated against uniaxial fatigue tests performed on trimmed and punched complex-phase steel specimens, demonstrating its ability to accurately predict fatigue life and crack initiation locations.
  
• GUO, ZHIMING: Study on HTPB propellant passivation, mixing, casting and curing processes by experiment and simulation
  
  Author: GUO, ZHIMING
  Programme: DOCTORAL DEGREE IN STRUCTURAL ANALYSIS
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 11/05/2026
  Reading date: 04/09/2026
  Reading time: 12:00
  Reading place: UPC Campus Nord, ETSECCPB, C/ Jordi Girona 1-3, edificio C1, Sala 002, Barcelona
  Thesis director: ROSSI BERNECOLI, RICCARDO | FU, XIAOLONG
  Thesis abstract: This study investigates the key physical issues involved in the four propellant production steps (passivation, kneading, casting, and curing) through a combination of experimental and numerical simulations.In this experimental study using HTPB propellant ingredients as raw materials, we first investigate the passivation and dehydration (similar to reduced pressure micro-boiling) of this raw material (N-butylnitroxyethylnitramine (BuNENA)). Next, we add other materials (including liquids and granules) to the passivated raw material and mix them in a vertical kneader. The resulting propellant slurry is then cast into a specific mold. Finally, we investigated the solidification of the propellant samples formed in the mold.In this numerical simulation study, First, the passivation process (bubble generation and movement) of the BuNENA material was studied through numerical simulation. Next, the mixing process of the propellant in a vertical kneader was investigated. The uniformity and flow characteristics of the HTPB propellant material were studied under stirring conditions.Finally, the slurry casting process was simulated, and finally, the curing of the cast propellant model was simulated.This paper contains the following research contents:(1) A passivation experimental device was established and experiments were carried out using a principle similar to reduced pressure micro-boiling; in the fluid dynamics simulation model, the Lagrangian framework was applied to track the formation and movement of bubbles, and the bubbles themselves were modeled as rigid spheres subjected to buoyancy and viscous forces. The Euler framework based on variational multiscale (VMS) was used to simulate the fluid around the bubbles. The bubble movement was analyzed. By combining experimental and simulation methods, the passivation process of BuNENA was analyzed in detail, which is of substantial significance in the field of passivation of composite solid propellants.(2) A computational fluid dynamics (CFD) method was used to establish a digital simulation model of the mixing process of the vertical kneader. Changes in various flow field related characteristics of the vertical kneader were analyzed. The mixing performance of the propellant slurry in the kneader was studied by establishing a mixing uniformity index analysis method. The accuracy of the simulation results was verified by real kneading experiments, SEM-EDS and density experiments. (3) The vacuum casting process was optimized by combining experiments and numerical simulations. First, the shear thinning behavior was revealed through rheological tests, and the Herschel-Bulkley model parameters confirmed non-Newtonian fluid characteristics. The variational multi-scale finite element method was used to simulate and analyze the vacuum casting process of HTPB propellant slurry. Second, the flow rate and impact force of droplets under different vacuum pressures were studied by combining real-time image recognition with machine vision and Kalman filtering. (4) Finally, the curing reaction kinetic model of HTPB propellant was studied by the non-isothermal DSC method. The distribution and evolution of the internal temperature and temperature degree of the propellant during the molding process were analyzed using a thermochemical model. The temperature gradient and curing time variation of the propellant curing process were explored by the thermocouple-integrated method.
  

DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY

• CASAPINO ESPINOZA, CARLOS ALBERTO: Estudio de eficiencia térmica de bloques de tierra (adobe), y propuesta de desarrollo de prototipo para clima frío. Caso de estudio altoandino Perú.
  
  Author: CASAPINO ESPINOZA, CARLOS ALBERTO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY
  Department: Department of Architectural Technology (TA)
  Mode: Article-based thesis
  Deposit date: 28/07/2026
  Deposit END date: 08/09/2026
  Thesis director: GOMEZ SOBERON, JOSE MANUEL VICENTE | GOMEZ SOBERON, MARIA CONSOLACION
  Thesis abstract: Buildings that use earth as a component of their construction systems represent between 30 and 50% worldwide, with most of these structures being residential and located in rural areas or developing countries. Earth is an economical and sustainable solution with excellent hygrothermal regulation. However, it presents limitations such as lower mechanical resistance and reduced durability in humid conditions. To mitigate these limitations, chemical stabilization (using lime or cement) or compression is commonly employed, which increases production costs, embodied energy, and CO2 emissions.At the same time, the generation of different types of waste, such as construction and demolition waste, mineral waste, and other materials like used tires, represents a serious environmental problem. Incorporating this waste as second-generation raw materials in unfired earth blocks emerges as a circular economy alternative to improve their properties without additives or stabilization methods. Therefore, the objective is to evaluate the technical feasibility and compatibility of incorporating different types of recycled aggregates, such as crushed ceramics (CCB), powdered soapstone (PSR), and end-of-life tires (CTW), by analyzing their effects on the various properties of earth blocks manufactured using traditional methods, without stabilizers or firing.The experimental methodology was structured in three stages: The first stage involved characterizing the soil and the different aggregates. The second stage focused on the mix design and manufacturing process, defining the replacement and curing percentages. The third stage consisted of the experimental campaign, evaluating, under standardized tests, density, porosity, hygroscopic expansion, compressive and flexural strength, elastic modulus, thermogravimetric analysis, thermal tests, and durability tests; these tests are addressed in the articles that comprise this thesis.The results obtained from the recycled aggregates studied demonstrate the possibility of their use through incorporation into soil matrices under regulatory standards, representing alternatives for reducing energy demand, reducing production costs, improving the insulating capacity for CCB and CTW cases, and in the case of PSR it was presented as an alternative mineral stabilizer with the potential to increase mechanical resistance and optimize thermal behavior for energy absorption, thus presenting themselves as construction alternatives for cold climates, also representing alternatives for the management of these wastes.
  

DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING

• CLARAMUNT MOLET, MIREIA: Development of a novel clinical gait assessment tool for monitoring and stratifying neuromuscular diseases
  
  Author: CLARAMUNT MOLET, MIREIA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING
  Department: Department of Mechanical Engineering (EM)
  Mode: Normal
  Deposit date: 24/07/2026
  Deposit END date: 04/09/2026
  Thesis director: FONT LLAGUNES, JOSEP MARIA | IDELSOHN ZIELONKA, SEBASTIAN
  Thesis abstract: Neuromuscular diseases are chronic and degenerative conditions of the skeletal musculature that progressively impair gait, one of the primary determinants of functional independence. Their monitoring, both in clinical practice and clinical trials, relies on clinical scales and functional tests that are subject to observational bias, ceiling effects, and insufficient sensitivity to detect subtle changes. At a time when novel disease-modifying therapies are emerging, the availability of an objective, portable tool integrable into routine clinical practice for biomechanical mobility assessment represents an unmet clinical need.To address this need, the present thesis develops the biomechanical algorithms to derive spatiotemporal parameters, sagittal joint kinematics, muscle activation, plantar pressure distribution, and heart rate from raw wearable sensor data. Data capture relies on the Ephion Mobility system, which integrates and synchronises inertial sensors, surface electromyography, plantar pressure insoles, and a cardiac sensor within a single mobile application. Using this system, data were collected from 176 volunteers, 90 patients and 86 controls, across two countries and standard hospital settings.The first study, conducted in collaboration with Hospital Sant Joan de Déu, serves as the proof of concept. It validates a multidimensional gait score for Duchenne muscular dystrophy, derived from multisensor data through unsupervised learning, which demonstrates good agreement with current clinical metrics and promising capacity for disease monitoring.With the validity of the approach established, the second study, carried out at the Copenhagen Neuromuscular Center, explores its applicability in two conditions with markedly different distributions of muscle weakness: Becker muscular dystrophy and myotonic dystrophy type 1. Biomechanical gait assessment is shown to discriminate disease-specific patterns and severity gradients that functional tests do not capture. Finally, the third study, conducted in collaboration with the Spanish Pompe Patient Association, addresses the most demanding question: whether the tool can detect longitudinal progression in a slowly evolving disease. The Pompe-MDPI achieves statistical significance over one year of follow-up in a context where current metrics fail to detect change over the same interval.Taken together, the results provide preliminary evidence that portable multidimensional biomechanical assessment is clinically feasible, sensitive to functional severity, and capable of detecting longitudinal disease progression where conventional measures fall short. The derived scores represent promising candidates as digital biomarkers for natural history studies and clinical trials of disease-modifying therapies.
  

DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING

• MARÍN RIVAS, ENRIQUE DAVID: Mechanochemical Preparation of Pd-Cu/CeO₂ Catalysts for Carbon Monoxide Oxidation
  
  Author: MARÍN RIVAS, ENRIQUE DAVID
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 31/07/2026
  Deposit END date: 14/09/2026
  Thesis director: LLORCA PIQUE, JORDI | VENDRELL VILLAFRUELA, XAVIER
  Thesis abstract: Cerium oxide (CeO2)-based catalysts are widely studied for oxidation reactions due to their redox properties, oxygen storage capacity, and ability to stabilise metal-support interfacial sites. Among these systems, Pd/CeO2 and Cu/CeO2 catalysts are of particular interest for low-temperature CO oxidation. However, their catalytic behaviour depends on the synthesis method, metal dispersion, and defect structure. In this thesis, mechanochemical synthesis by planetary ball milling was investigated as a sustainable route for preparing CeO2-based catalysts, together with different treatments aimed at modifying their structural and catalytic properties.The first part of this work focused on Pd/CeO2 catalysts prepared by planetary ball milling under controlled atmospheres. The results demonstrated that mechanochemical synthesis promotes the formation of active Pd-Ce interfacial structures. Catalysts prepared at 250 rpm under air for 10 min exhibited the highest CO oxidation activity, outperforming those prepared by conventional impregnation. This behaviour was attributed to the formation of PdOx-Ce interfacial species and strong metal-support interactions. Electron microscopy revealed highly dispersed Pd nanoparticles and clusters on the ceria surface.The second part investigated Cu/CeO2 catalysts prepared by mechanochemical methods using different precursors, calcination temperatures, milling conditions, and reduction treatments. The results showed that mechanochemical synthesis can produce catalysts with superior performance compared with conventional methods. Catalysts prepared from copper nitrate and calcined at 300 °C showed the best activity. H2/N2 reduction further enhanced catalytic performance. Electron microscopy confirmed the absence of large CuOx aggregates and the presence of highly dispersed copper species. In addition, operando synchrotron experiments revealed dynamic Cu+/Cu2+ redox cycling under reaction conditions, contributing to catalyst stability and progressive activation.The third part addressed bimetallic Pd-Cu/CeO2 catalysts prepared by planetary ball milling. Different Cu/Pd ratios, metal loadings, and deposition sequences were evaluated. Under non-reduced conditions, Pd incorporation did not significantly improve activity compared with monometallic Cu/CeO2 catalysts. However, after H2 reduction, the bimetallic catalysts exhibited enhanced activity, highlighting the importance of pre-reduction in the formation of favourable Pd-Cu-Ce interfacial structures.Electron beam irradiation was also investigated as a post-synthesis treatment for Pd/CeO2 catalysts. Irradiation improved catalytic activity and reduced the apparent activation energy for CO oxidation. Raman and XPS analyses revealed an increase in structural defects, peroxide species, and additional PdOx-Ce interfacial sites.Finally, flash sintering was applied to ceria-based materials. Although the treatment induced significant microstructural and electrical modifications, the resulting materials exhibited lower catalytic activity than untreated CeO2, mainly due to the thermal effects associated with Joule heating.Overall, this thesis demonstrates that mechanochemical synthesis is an effective strategy for preparing highly active CeO2-based catalysts. The catalytic behaviour of Pd/CeO2, Cu/CeO2, and Pd-Cu/CeO2 systems is governed by metal-ceria interfacial structures, metal dispersion, and the redox properties of the support.
  

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

• PAREDES AHUMADA, JUAN ANTONIO: Improving Data-Driven Estimations of Physical Fields in IoT Sensor Networks
  
  Author: PAREDES AHUMADA, JUAN 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 COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 29/07/2026
  Deposit END date: 09/09/2026
  Thesis director: GARCÍA VIDAL, JORGE | BARCELÓ ORDINAS, JOSE MARIA
  Thesis abstract: This thesis explores data-driven strategies for monitoring physical fields using (IoT} sensor networks. In doing so, we focus on improving the estimation of physical quantities at two complementary levels. First, at the local level, measurements collected at individual nodes are used to estimate a new physical quantity not previously monitored at that location, through Machine Learning (ML)-based virtual sensors. Second, at the network-wide level, spatially distributed measurements are leveraged to determine the optimal arrangement of sensors for reconstructing the whole physical field over a large area. This is achieved by formulating and solving the sensor placement problem using low-dimensional representations of the measured signal.Thus, the first part of this thesis focuses on developing virtual sensors based on proxy models that estimate non-regulated and rarely monitored pollutants, like black carbon (BC) mass concentration, from measurements of other physical variables. The relevant environmental variables are identified and the impact of different meteorological conditions, such as seasonality, on model's performance are studied as well. The evaluation of the proxy model shows how this data-driven technique may help to reduce the infrastructure cost to improve the exposure assessment in urban Mediterranean environments. Furthermore, the black carbon proxy model is coupled with low-cost sensor (LCS) nodes, addressing data quality challenges that may impact on obtaining a reliable estimate in real-world sensing scenarios, such as data noise, missing values, and varying sampling intervals. A robust machine learning proxy (RMLP) to estimate BC mass concentrations is developed. The robust proxy model incorporates key pre-processing tasks and constitutes an improvement over basic proxy models that ignore these phenomena. The second part of this thesis addresses the optimal sensor placement for signal recovery. Using spatially distributed measurements, the values of a scalar physical field are estimated at multiple locations. To do so, the measured signal is represented in terms of a low-rank structure which is exploited to significantly reduce the number of locations necessary to infer the values of the field of interest. In particular, the sensor placement problem is formulated for multiclass monitoring networks, consisting of different classes of devices with varying accuracy. The results show how the proposed algorithm is suitable for monitoring networks that present a great disparity between device noises or scenarios with a limited number of devices. Additionally, the sizing and placement problem is re-framed to achieve a more rigorous control over the reconstruction error. In consequence, the Sizing and Placement with Coordinate Reconstruction ErrorConstraint (SP-CREC) algorithm is proposed, which bounds the per-coordinate error variance of the reconstructed signal. This allows assigning specific thresholds to certain regions of interest within the network, where the error variance can be more or less restricted, according to monitoring needs. The results show that SC-CREC successfully complies with heterogeneous thresholds while deploying a low number of devices. As a whole, the proposed methods improve the monitoring capability of IoT sensor networks by enabling accurate reconstruction of physical quantities from limited sensor data under different deployment constraints.
  
• SIRACUSA, MARCO: Hardware-Software Co-Design for Accelerating Sparse Tensor Algebra
  
  Author: SIRACUSA, MARCO
  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: 23/07/2026
  Deposit END date: 03/09/2026
  Thesis director: MORETÓ PLANAS, MIQUEL | ARMEJACH SANOSA, ADRIÀ
  Thesis abstract: Many modern scientific and machine learning workloads exhibit inherently sparse and irregular structure. However, traditional supercomputers and datacenters are optimized for dense, regular computation. As a result, sparse workloads use only a fraction of available system resources, leaving significant performance untapped. Although prior solutions have been proposed, they typically target narrow classes of sparse tensor algebra operations, do not fully leverage modern vector compute cores, or leave much of the programmability burden to the user, limiting widespread adoption. To address this gap, this thesis presents a hardware–software co-design for the efficient execution of general sparse tensor algebra operations. We begin by analyzing the architectural implications of sparsity across a broad range of scientific and machine learning applications. Our analysis reveals that traditional compute cores are fundamentally ill-suited to the irregular tensor traversal and coordinate merging required to operate on sparse tensor formats. Building on these insights, we design a Decoupled Access–Execute (DAE) architecture that offloads these operations to a specialized unit, the Tensor Marshaling Unit (TMU), while leaving computation on the core. We demonstrate that the resulting DAE architecture outperforms traditional CPUs and GPUs by up to an order of magnitude. To deliver these gains without exposing the complexity of DAE programming to end users, we also present Ember, a compiler that lowers sparse machine learning operations to DAE code for architectures such as TMU–CPU systems. Ember is implemented in MLIR, enabling natural integration with PyTorch and TensorFlow. By automating this mapping, Ember unlocks the full performance potential of the TMU without imposing an additional programmability burden.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• DIAZ MOTTA, ARMANDO: Large Scale Wind-Powered Offshore Ammonia Production
  
  Author: DIAZ MOTTA, ARMANDO
  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: 30/07/2026
  Deposit END date: 10/09/2026
  Thesis director: DÍAZ GONZÁLEZ, FRANCISCO | VILLA ARRIETA, MANUEL RICARDO
  Thesis abstract: Hydrogen and renewable ammonia can support the decarbonization of sectors where direct electrification is not feasible, with green ammonia serving as a hydrogen carrier between renewable production areas and distant demand centers.Among the large-scale pathways proposed in recent years, green ammonia production based on renewable electricity and water electrolysis has attracted increasing attention. However, limited attention has been given to the long-term feasibility of off-grid offshore ammonia production based on SOEC electrolysis and powered entirely by offshore wind. This thesis specifically addresses this knowledge gap by investigating whether large-scale, off-grid offshore green ammonia production based on solid oxide electrolysis (SOEC), a Haber-Bosch synthesis loop (HB), and offshore wind power can become a feasible pathway by 2050.This research aims to assess the technical and long-term economic feasibility of offshore wind-based ammonia production. To this end, the thesis combines a state-of-the-art assessment with a thermodynamic steady-state model of a 3 000 tpd SOEC-Haber-Bosch ammonia plant and an integrated pseudo-dynamic framework that couples the plant, offshore wind generation, battery storage, and hydrogen buffer storage. This framework includes an economic model and a capacity optimization algorithm to minimize the levelized cost of ammonia (LCOA). The pseudo-dynamic model simulates flexible plant operation over an extended load range under site-specific wind conditions. Three offshore locations with high-quality wind resources, namely La Guajira (Colombia), the North Sea (Denmark), and the Gulf of Roses (Spain), are assessed in this thesis. The results show that, at steady state and full load, the plant requires 1 030 MW and reaches an overall efficiency of 63% on an LHV-NH3 basis, while the SOEC electrolyzer achieves 87% on an LHV-H2 basis. The Haber-Bosch loop supplies 57% of the thermal power required for feedwater evaporation in the electrolysis process. Under partial-load operation, the SOEC unit reaches minimum loads of 61% and 72% for steam conversion scenarios of 70% and 85%, respectively, with stack temperature variations within ±30 °C. Under offshore operating conditions, the overall efficiency reaches 60%, and the plant capacity factor reaches 80% at the best-performing site, about 10% below that of a conventional grid-connected ammonia plant.Regarding economic feasibility, the results indicate that La Guajira and the North Sea could achieve the lowest levelized cost of ammonia by 2050, at 472 and 436 USD t-1, respectively, whereas the Gulf of Roses remains less competitive at around 720 USD t-1.A comparison across the selected sites further shows that inflexible Haber-Bosch operation, i.e., operation at 100% load, results in only marginal production cost differences relative to flexible operation over the 10-100% load range, but increases Haber-Bosch hot-standby events, revealing a trade-off between operational stability and storage requirements.The thesis provides a techno-economic assessment framework for offshore green ammonia production, while also supporting the capacity planning of offshore renewable resources. Furthermore, the results indicate that SOEC-based offshore ammonia could become cost-competitive by 2050, provided that costs decline for floating wind and solid oxide electrolysis, and that exogenous factors such as supportive market conditions and favorable policy frameworks emerge.
  
• MASSANA RAURICH, JOAQUIM: Data-driven methodologies to reduce energy consumption and increase flexibility in electric scenarios
  
  Author: MASSANA RAURICH, JOAQUIM
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Article-based thesis
  Deposit date: 30/07/2026
  Deposit END date: 10/09/2026
  Thesis director: SUMPER, ANDREAS | COLOMER LLINAS, JUAN
  Thesis abstract: The present thesis, entitled “Data-driven methodologies to reduce energy consumption andincrease flexibility in electric scenarios”, explores the role of AI-driven tools in advancing the operational efficiency and adaptability of distributed energy systems. It addresses the growing complexity of managing electrical infrastructures in scenarios characterized by the high integration of renewable energy sources and the increasing electrification of demand, particularly through flexible assets such as electric vehicle chargers, storage systems, and programmable industrial loads. The central aim is to develop and validate intelligent, data-oriented approaches that allow energy systems to become not only more efficient but also more responsive to market signals and grid constraints. The first article included in the thesis focuses on the implementation of an optimal scheduler within a multi-vector energy management system (MVEMS) deployed in a real-world port microgrid. This study addresses the orchestration of flexible assets: such as containercranes, EV charging stations, and battery energy storage systems, whose operations areplanned daily to minimize energy costs while maximizing the use of locally produced renewable energy. The methodology integrates forecast models, control constraints, and heuristic optimization algorithms to compute a viable hourly dispatch plan. By simulating this control strategy over a realistic dataset and infrastructure, the study demonstrates how intelligent scheduling can significantly improve local energy self-sufficiency and reduce dependency on the external grid. Special emphasis is placed on practical feasibility, using real-time data and computation-aware algorithmic configurations. The second article complements this contribution by tackling the issue of grid flexibility through demand-side participation in electricity markets. Specifically, it investigates the potential of electric vehicle charging point operators (CPOs) to act as flexibility service providers (FSPs) within local congestion management frameworks. The proposed methodology centres on forecasting the aggregated and session-level flexibility available across a network of charging stations, enabling CPOs to make market bids without compromising the quality of service offered to end users. This approach combines machine learning models with calendar, weather, and socioeconomic data, and includes user behaviour profiling to avoid reliance on private or sensitive information. Through this strategy, the study opens a pathway for urban-scale EV charging infrastructure to contribute proactively to grid stability and congestion mitigation.Together, the two studies illustrate complementary facets of how data-based artificial intelligence methodologies can be applied in practice to reduce energy consumption and enhance system flexibility. The first contributes to operational planning within a microgrid context, while the second enables strategic participation in energy markets. Despite their different focus, both approaches leverage real-world data, model system constraints, and employ machine learning or optimization to address uncertainty and enhance performance. This dual perspective reflects the multifaceted challenges of the energy transition, where operational excellence and market integration must co-evolve. Ultimately, the thesis demonstrates that artificial intelligence, when grounded in domain knowledge and implemented with practical constraints in mind, can provide robust solutions to the pressing need for more adaptive and efficient energy systems.
  

DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING

• PASCUA SOLÉ, LAIA: Elucidating Structure-Activity Relationships in Bimetallic Pd-Based Catalysts for Methane Oxidation Reactions via Multi-Technique Characterisation
  
  Author: PASCUA SOLÉ, LAIA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 28/07/2026
  Deposit END date: 08/09/2026
  Thesis director: LLORCA PIQUE, JORDI | JIMÉNEZ DIVINS, NÚRIA
  Thesis abstract: This thesis studies two methane oxidation reactions using Pd-based catalysts: total methane oxidation (MTO) for natural gas vehicles as a transition fuel, and partial methane oxidation (POM) for efficient syngas production. MTO faces issues with water poisoning and stability, while POM suffers from coke formation and long-term instability. To address these problems, the catalysts were characterized under operando and in situ reaction conditions, evaluating the effect of a second metal (Co, Ni), the support (CeO₂ vs. Al₂O₃), and the preparation method (ball milling, BM, vs. incipient wetness impregnation, IWI). In MTO (Ch. 4), catalysts on Al₂O₃, prepared by BM, and with monometallic Pd gave the best results. Co and CeO₂ stabilize the PdO phase, but an optimal PdO:Pd⁰ ratio is required. Under water vapor exposure, the bimetallic BM samples showed a stabilizing effect. In POM (Ch. 5), the PdNi-BM and PdCo-BM systems showed synergy and outperformed their IWI counterparts. PdNi-BM exhibited better overall activity and stability. BM samples kept the metals in close proximity, while IWI samples underwent metal separation and sintering. Unique Janus particles were identified in PdCo-BM. Operando characterization (Ch. 6) revealed that bimetallic BM samples had a different arrangement, explaining the observed synergy. The PdCo system displayed unexpected self-sustained oscillations in both reaction products and oxidation states under constant reaction conditions once syngas production began, correlated with the reduction of both metals. Finally (Ch. 7), the interactions were modeled using AP-HAXPES. Methane exposure created carbonaceous intermediate species and led to metal reduction. Co-containing systems reduced faster and formed fewer intermediates than Ni-containing ones, and the CeO₂ support played an active role in preventing carbonaceous adsorption.
  

DOCTORAL DEGREE IN NETWORK ENGINEERING

• FARAHPOOR, MOHAMMADALI: Secure and Auditable Data Management for IoT-Driven Smart Transportation
  
  Author: FARAHPOOR, MOHAMMADALI
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN NETWORK ENGINEERING
  Department: Department of Network Engineering (ENTEL)
  Mode: Normal
  Deposit date: 28/07/2026
  Deposit END date: 08/09/2026
  Thesis director: ESPARZA MARTIN, OSCAR
  Thesis abstract: The increasing adoption of the Internet of Things (IoT) in industrial transportation has enabled continuous monitoring, predictive maintenance, and data-driven decision-making in environments such as mining, construction, and other heavy-duty operations. However, the same systems also generate large volumes of critical data whose value extends beyond real-time use. Once these data are shared among multiple stakeholders, challenges related to trust, integrity, confidentiality, recoverability, and auditability become central. This thesis addresses that problem through two connected research directions.First, it presents TrackTruck, an IoT-driven fleet-management infrastructure for industrial vehicles. TrackTruck demonstrates how embedded sensing, flexible communication, cloud-based analytics, and operational decision support can be integrated into a practical smart-transportation platform for heterogeneous fleets in demanding field conditions. The results show that such an architecture can improve operational visibility, maintenance support, dispatching efficiency, and overall productivity.Second, this thesis presents FileTrust, a blockchain-based auditable backup framework designed for low-trust multi-stakeholder IoT environments. FileTrust combines an Information Dispersal Algorithm (IDA), the InterPlanetary File System (IPFS), blockchain smart contracts, verifiable secret sharing, distributed key generation, and threshold encryption to protect access-enabling metadata and support verifiable, policy-driven recovery of critical data. Its design preserves off-chain storage efficiency while adding on-chain auditability and threshold-governed access control.Taken together, these contributions show that trustworthy industrial IoT requires more than efficient telemetry and analytics. It also requires secure long-term data governance. This thesis therefore proposes a broader perspective in which IoT-driven smart transportation is studied as a complete data lifecycle, spanning generation, transmission, operational use, preservation, controlled access, and recovery. The results provide both an applied industrial IoT case study and a secure decentralized backup framework, establishing a foundation for future trustworthy smart-transportation architectures.
  

DOCTORAL DEGREE IN SUPPLY CHAIN AND OPERATIONS MANAGEMENT

• VIDES PRADO, ANDRÉS DAVID: Estrategia sostenible para proyectos de suministro eléctrico en comunidades rurales. Caso de estudio La Guajira.
  
  Author: VIDES PRADO, ANDRÉS DAVID
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SUPPLY CHAIN AND OPERATIONS MANAGEMENT
  Department: Department of Management (OE)
  Mode: Change of supervisor
  Deposit date: 30/07/2026
  Deposit END date: 10/09/2026
  Thesis director: DOMÉNECH LÉGA, BRUNO
  Thesis abstract: This doctoral thesis develops a comprehensive strategy for planning rural electrification programs in isolated communities, using the department of La Guajira, Colombia, as a case study. Within the framework of the energy transition process, many generation and transmission projects aim to strengthen the National Interconnected System (SIN); however, they do not always consider access to energy for Indigenous communities, particularly in non-interconnected zones (ZNI). This thesis recognises electricity as a driver of human development and proposes approaching its planning as a sustainable process that integrates technical, economic, environmental, social, and institutional dimensions. The methodological framework incorporates multi-criteria decision-making tools, technical simulation, and community participation mechanisms to ensure that decision-making reflects local priorities, Indigenous worldviews, and community capacities, while also considering the expectations of stakeholders. The results constitute methodological and empirical contributions that fully address sustainable rural electrification planning. First, a review of the specialised literature identified four knowledge gaps that limit rural electrification programs. Second, a sociocultural diagnosis of the Wayuu indigenous population in La Guajira was developed through fieldwork. Third, a multi-criteria evaluation model was constructed, integrating fifteen criteria across five dimensions with weights assigned by communities, experts, and local government leaders, to select the most appropriate electrification alternative. Fourth, a four-stage redesign methodology was proposed to evaluate existing projects and develop expansion strategies that improve supply and leverage current infrastructure. Fifth, a methodology for the multidimensional impact assessment of electrification is proposed, which, through a five-stage process, gathers the benefits perceived by communities while identifying evidence-based improvement actions. Finally, a pilot rural electrification program, eligible for funding, was formulated, integrating the products of this research project into a real-world intervention for the region. Taken together, the contributions of this research seek to contribute to the planning of more robust and appropriate electrification programs, offering replicable strategies adaptable to other regions of the world.Keywords: Rural electrification, Sustainability, Energy transition, Multi-criteria decision-making, Community participation.
  

DOCTORAL DEGREE IN THERMAL ENGINEERING

• PLANA RIU, JOSEP: Marching faster in time: advanced time-integration for incompressible flows
  
  Author: PLANA RIU, JOSEP
  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 THERMAL ENGINEERING
  Department: Department of Heat Engines (MMT)
  Mode: Normal
  Deposit date: 22/07/2026
  Deposit END date: 02/09/2026
  Thesis director: PEREZ SEGARRA, CARLOS DAVID
  Thesis abstract: The computational cost of scale-resolving simulations of incompressible flows, such as Direct Numerical Simulation (DNS) and Large-Eddy Simulation (LES), is largely dictated by the temporal integration of the incompressible Navier-Stokes equations. Traditional timestepping strategies often rely on conservative stability criteria, such as the standard Courant-Friedrichs-Lewy (CFL) condition, which typically underestimates the maximum stable timestep by neglecting the complex interplay between convective and diffusive scales. This thesis addresses the challenge of "marching faster in time" by developing a framework that integrates stability-aware adaptive timesteppting with hardware-optimized sparse linear algebra techniques. The first part of this thesis focuses on the development and extension of self-adaptive time integration methods based on the spectral analysis of the governing operators. By implementing algorithms such as AlgEigCD on staggered grids, it is shown that the maximum stable timestep can be accurately determined by tracking the evolution of the operators’ eigenvalues, rather than relying on the conservative CFL condition. This approach allows for significantly larger timesteps without compromising stability or accuracy, leading to substantial reductions in computational time for incompressible flow simulations, without sacrificing the fidelity of the results. Furthermore, this thesis extends these concepts to the realm of reduced-order modeling (ROM). Using Poincaré’s separation theorem for singular values, a theoretical foundation is established to prove that the stability limits of the reduced convective operators are bounded by those of the full-order system. The resulting RedEigCD algorithm enables ROMs to sustain larger timesteps, effectively leveraging their lower dimensionality to further reduce total wall-clock time. Finally, the research addresses the hardware-level bottleneck inherent in modern CFD solvers, which are frequently limited by memory bandwidth during sparse algebraic operations. By exploiting the repeated matrix structure found in parallel-in-time ensemble averaging simulations, sparse matrix-vector products are replaced by sparse matrix-matrix products. This transformation increases the arithmetic intensity of the computations, enabling higher performance on modern hardware architectures. The effectiveness of these combined mathematical and computational strategies is validated through a series of academic and industrial test cases, demonstrating that significant speedups can be achieved without compromising the accuracy or stability of the simulations. This work provides a practical pathway for accelerating CFD simulations in real-world applications, while also contributing to the theoretical understanding of stability in numerical methods for incompressible flows.
  

DOCTORAL DEGREE IN URBAN AND ARCHITECTURAL MANAGEMENT AND VALUATION

• ZHANG, XU: Urban expansion and its environmental consequences: Green space, thermal environment, and climate responses from a remote sensing perspective
  
  Author: ZHANG, XU
  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: 30/07/2026
  Deposit END date: 10/09/2026
  Thesis director: ROCA CLADERA, JOSE NICASIO | ARELLANO RAMOS, BLANCA ESMARAGDA
  Thesis abstract: Against the backdrop of global urbanization and intensifying climate risks, urban expansion has become a key process reshaping spatial organization and environmental systems. Urban growth not only alters land-use structures and urban boundaries, but also affects thermal environments, ecological quality, and biodiversity through the reconfiguration of urban spatial structure. Existing studies often focus on single-scale analyses or isolated processes and lack systematic integration across scales, regions, and environmental mechanisms.This dissertation develops an integrated framework linking urban expansion, spatial structure, and environmental responses. Using multi-source remote sensing data, including nighttime light imagery, spectral indices, land surface temperature, vegetation indices, and biodiversity observations, the study establishes methods for urban expansion detection and urban boundary delineation. Landscape ecological metrics are applied to quantify urban morphology, connectivity, and fragmentation, while thermal and ecological responses are analyzed through heatwave indicators, surface energy partitioning, and ecological quality assessments.The study areas include rapidly urbanizing regions in China and mature metropolitan areas in Europe, enabling comparative analysis under different climatic and developmental conditions. The results show that the environmental impacts of urban expansion are determined not only by the proportion of built-up land, but mainly by spatial organization and landscape configuration. Spatial fragmentation alters energy distribution, weakens ecological connectivity, and reshapes cooling diffusion pathways, leading to differentiated thermal and ecological responses.During rapid urbanization stages, increasing impervious surfaces and declining green space continuity amplify thermal risks and reduce ecological resilience. In more mature metropolitan regions, environmental responses become more localized and heterogeneous, although they remain strongly conditioned by spatial structure. Even when total green space changes little, fragmentation can progressively degrade ecological network stability and biodiversity over time.Cross-regional comparisons reveal that expansion intensity, climatic conditions, and urbanization stages significantly influence the pace and spatial expression of environmental responses, while the fundamental structure-mediated mechanisms remain consistent across contexts.This dissertation proposes that the environmental consequences of urban expansion are essentially systemic effects driven by spatial structural reorganization, with spatial structure acting as the key mediating variable linking expansion and environmental responses. By integrating urban expansion detection, landscape structure analysis, thermal environment assessment, and ecological evaluation into a unified framework, this study advances urban expansion research from area-based analysis toward structural mechanism interpretation.The dissertation establishes a transferable multi-scale analytical framework integrating multi-source remote sensing data across national, metropolitan, municipal, and street scales. The findings highlight the importance of blue-green networks in maintaining thermal regulation and ecological stability, emphasizing that sustainable urban development depends not only on limiting expansion scale, but also on optimizing spatial structure and strengthening ecological functions.