Theses authorised for defence

DOCTORAL DEGREE IN APPLIED MATHEMATICS

GIL RAMS, DÍDAC: Splitting of separatrices in generalized standard maps
Author: GIL RAMS, DÍDAC
Programme: DOCTORAL DEGREE IN APPLIED MATHEMATICS
Department: School of Mathematics and Statistics (FME)
Mode: Normal
Deposit date: 15/05/2026
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: MARTIN DE LA TORRE, PAU | BALDOMA BARRACA, INMACULADA CONCEPCION
Thesis abstract: We consider generalized standard maps, that is, families of area-preserving maps on the plane F:(x,y) = (x+y+f(x;h),y+f(x;h)) with h the perturbative parameter and f fulfilling quite general assumptions. This generalization includes the Chirikov standard map, the Hénon map or the perturbed McMillan map, among others.We study transverse intersections between the invariant manifolds (stable and unstable) associated to a hyperbolic fixed point of F. These intersections give rise to homoclinic orbits related to the hyperbolic fixed point. The existence of these kind of orbits is one of the most celebrated methods to prove the existence of chaotic dynamics in a system. Indeed, the Birkhoff-Smale Homoclinic Theorem ensures that, if there exist transverse intersections between the invariant manifolds of the same invariant object, the system is locally conjugate to a Smale horseshoe with infinite symbols.The classical Melnikov theory is a first order perturbative theory that is often used to measure the intersection angle between the invariant manifolds. However, when the Melnikov function is exponentially small in the perturbative parameter, the first order analysis fails. Despite its exponentially small character, the Melnikov function still provides the correct size of the splitting in some systems. This is not our case, which is singular. To deal with it, we use a complex time matching technic involving the inner equation related to F.In the first part of our work, by considering an small enough perturbative parameter h, we obtain an asymptotic formula for the Lazutkin's invariant, a quantity analogous to the intersection angle between the invariant manifolds, related to the primary homoclinic points of a wide class of maps F. An exponentially small upper bound was obtained by Fontich. Later, we provide an asymptotic formula for a controversial example exponentially bigger than the naïve guess.The leading term of the obtained asymptotic formulas depends on a constant, often called Stokes constant, that comes from the study of the inner equation. The second part of our work contains a general algorithm, based on the study of the inner equation related to F, to compute an interval containing such constants by means of a computer assisted proof in CAPD. Finally, we apply this algorithm to prove that the Stokes constants related to maps F of the form f(x;h)=e f_0(x), with e = 4 sinh^2(h/2) and f_0 a polynomial of degree 2<=d_0<= 970 or trigonometric polynomial of any degree, are different from zero (including the Standard and Hénon maps). We also provide an example of a generalized standard map such that its Stokes constant is zero.
KHAN, SHERAZ AHMED: A posteriori error estimates for the finite element approximation of flow problems based on the variational multiscale concept
Author: KHAN, SHERAZ AHMED
Programme: DOCTORAL DEGREE IN APPLIED MATHEMATICS
Department: School of Mathematics and Statistics (FME)
Mode: Normal
Deposit date: 15/05/2026
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: CODINA ROVIRA, RAMON
Thesis abstract: Numerical methods have become popular for solving complex flow problems in recent decades. Finite element methods have attracted the attention of scientists and engineers by offering computational solutions to partial differential equations, widely used to address engineering problems. In fluid mechanics, the standard Galerkin finite element method exhibits unstable and oscillatory solutions when dealing with convection-dominated problems. To overcome these limitations, stabilized finite element methods have emerged that provide stable solutions by incorporating additional stabilization terms into the standard Galerkin formulation. Predicting and controlling the error of numerical approximations remains a computational challenge. A posteriori error estimation has made significant progress and has become an essential tool for finite element practitioners, assessing and controlling the accuracy of numerical solutions and guiding adaptive refinement strategies.The initial part of this study develops a posteriori error estimates for the convection-diffusion-reaction equation using the variational multiscale framework. We present the results of the a priori analysis and two strategies of the a posteriori error analysis for the orthogonal sub-grid scale method. Our proposal is to use a scaled norm of the sub-grid scales as an a posteriori error estimate in the stabilized norm of the problem, which provides control over the convective term. The error convergence analysis is conducted using the L2 norm and the stabilized norm. Numerical examples demonstrate the reliable performance of the proposed error estimator compared to other estimators belonging to the variational multiscale family.The second part develops a goal-oriented a posteriori error estimation framework for linear functionals in the stabilized finite element discretization of the stationary convection-diffusion-reaction equation. We propose an explicit approach using the orthogonal sub-grid scale method, based on evaluating the sub-grid scale in the quantity of interest functionals, and compare it with a duality-based method requiring the solution of an additional adjoint problem. The results indicate that both methods yield similar error estimates, whereas the VMS-based explicit approach is computationally less expensive. Numerical tests demonstrate the effectiveness of the proposed techniques in terms of the quantity of interest functionals.The third part is dedicated to developing an adaptive mesh refinement strategy guided by a posteriori error estimators for the transient Navier-Stokes equations of incompressible flows. A VMS-based a posteriori space error estimator is derived using the orthogonal sub-grid scale method, and an h-refinement strategy driven by the local error indicator is proposed and validated on benchmark flow problems.Overall, this thesis develops a posteriori error estimates for orthogonal sub-grid scale discretizations of flow problems within the variational multiscale framework. The proposed error estimation strategies are shown to be robust for applications in fluid mechanics.

DOCTORAL DEGREE IN ARCHITECTURAL DESIGN

NARANJO SERRANO, MÓNICA GABRIELA: Espacios públicos no programados. Contextos de descompresión y densificación urbana
Author: NARANJO SERRANO, MÓNICA GABRIELA
Programme: DOCTORAL DEGREE IN ARCHITECTURAL DESIGN
Department: Department of Architectural Design (PA)
Mode: Normal
Deposit date: 17/04/2026
Reading date: 09/06/2026
Reading time: 11:30
Reading place: ETSAB (Escuela Técnica Superior de Arquitectura de Barcelona) - Planta Baja - Sala de GradosAv. Diagonal, 649-651 - 08028 - Barcelona
Thesis director: GASTON GUIRAO, CRISTINA | SICA PALERMO, NICOLÁS
Thesis abstract: Starting from the premise that the city is not built as a sum of isolated objects, but rather as a complex system of spatial, historical, and social relationships, this work investigates the role of architecture in the generation of Unprogrammed Public Spaces (UPS) as fundamental components of the contemporary urban fabric. This research focuses on those open spaces that, without having been explicitly conceived as public space within architectural programs or urban regulations, acquire a collective character through design decisions linked to site occupation, volumetric configuration, and the building’s relationship with ground level.This comparative study is based on the analysis of two urban axes: Dearborn Street in Chicago and Avenida Paulista in São Paulo. Both cases make it possible to observe how modern architecture, in different urban and cultural contexts, was capable of producing significant urban voids that expanded the public dimension of the city. While in Chicago architectural strategies were oriented toward introducing spaces of relief within a highly consolidated fabric, in São Paulo they responded to the need to structure and densify an urban landscape in formation.The study of Dearborn Street, as the main case, is supported by a historical reconstruction that shows how, despite repeated reconstruction processes following the fire of 1871, the city maintained rigid morphological parameters for decades—alignment to the building line, fragmented parceling, and full lot occupation—which were only challenged with the insertion of modern projects in the mid-twentieth century. The emergence of buildings such as Inland Steel, the Civic Center, the First National Bank, and the Federal Center enabled the formation of a sequence of plazas and open spaces that, far from being isolated gestures, configured a continuous system of unprogrammed public spaces along the street axis.In São Paulo, the analysis of six buildings reveals a different yet conceptually related approach. Strategies such as the tower-on-podium typology, the liberation of the ground plane, and the perforation of the ground floor allowed not only the creation of open spaces at ground level, but also a volumetric release in height, introducing air, light, and urban continuity into a city marked by accelerated processes of densification. The buildings studied—Quinta Avenida, Pauliceia, Nações Unidas, Conjunto Nacional, Banco Sulamericano, and MASP—demonstrate how these operations gave rise to UPS with a high capacity for permanence, appropriation, and collective representation.Based on the comparative analysis, recurring mechanisms—historical, spatial, morphological, and social—are identified as intervening in the configuration of UPS. It is demonstrated that these spaces are neither residual nor collateral effects of the architectural project, but rather the direct result of conscious decisions that allow architecture to yield space to the city or, alternatively, to allow the city to extend into the interior of the building. Likewise, it is shown that UPS generate itineraries of pauses and movement within the apparent monotony of the urban fabric, acting as articulators of the pedestrian experience.It is concluded that, although there is no single model of UPS, universal strategies can be identified whose adaptation is always local and context-specific. In contemporary scenarios characterized by a scarcity of available public land, UPS acquire a strategic role in the construction of the city. Finally, this work seeks to contribute a conceptual and methodological framework that makes it possible to identify, analyze, and design UPS as part of a collective project for the city, in which architecture consciously assumes its public and urban responsibility.

DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY

MARTIN FANJUL, VALENTIN: Arquitectura y autismo: consideraciones acústicas para el desarrollo de espacios específicos
Author: MARTIN FANJUL, VALENTIN
Programme: DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY
Department: Department of Architectural Technology (TA)
Mode: Normal
Deposit date: 25/03/2026
Reading date: 08/06/2026
Reading time: 11:00
Reading place: ETSAB (Escola Tècnica Superior d'Arquitectura de Barcelona) - Planta Baixa - Sala de GrausAv. Diagonal, 649-651 - 08028 - Barcelona
Thesis director: LACASTA PALACIO, ANA MARIA | DAUMAL DOMENECH, FRANCESC DE PAULA
Thesis abstract: This doctoral thesis combines acoustics, autism and architecture with an unequivocal practical focus, so that the conclusions and possible future avenues of research it may generate can be used in specific spaces for people on the autism spectrum.Existing knowledge is recent and scarce, it is mainly based on the experience of technicians who have created specific spaces, whether newly built or adapted. This fact is further emphasised when the disorder itself adds the concept of spectrum, which implies very broad and diverse conditions that further hinder the ability to obtain generalised solutions.Another factor that has influenced this search is the difficulty for potential users to convey their acoustic needs, especially those with more severe disorders, which is why the research has been structured in two ways.The first is a quantitative survey aimed at technical managers and carers of people with ASD, consisting of a set of 10 questions, which was sent to 715 valid email addresses in 30 countries and in three languages: English, French and Spanish.The second is qualitative in nature and is organised through the study of scientific texts, visits to specific centres, relationships with autistic people and their families, as well as professional experience with this group.It has been argued that venues should be designed primarily for those who suffer from hyperacusis, but studies have not been conclusive about how this condition evolves over the course of their lives. For this reason, it has been recommended that acoustic properties be maximised during childhood and youth, when there is no doubt about its prevalence.A significant factor found is that acoustic interventions should prioritise high-pitched sounds over low-pitched ones, as they are more annoying. For this reason, acoustic solutions were presented using existing construction systems based on the data obtained.The state of the art recommends solutions to improve sound environments, including the use of carpets, but after studying other disciplines, it has been found that they should not be used despite their acoustic properties. During visits to specific centres, those in charge reported acoustic problems relating to activities in greenhouses and swimming pools, which is why interventions based on existing construction solutions have been developed.The studies carried out have detected an anomaly between whether high-pitched or low-pitched sounds, depending on the language of the speakers, cause more discomfort. While for English and Spanish it was the high-pitched sounds, for French it was both, but the limitations of the sample obtained do not allow these findings to be irrefutable, although they do generate a line of research to consider the language of people with ASD as a factor in acoustic design.The complexity of acoustic design for autistic people has been demonstrated, as evidenced by the modifications made in the specific centres consulted. Collaboration in its design is necessary between all those involved, including family members, technicians and the staff responsible for their care. Acoustic quality is not exclusive to autistic people; research that improves their sound environments will also improve those of neurotypical people.KeywordsAcoustics, autism, architecture, ASD, acoustic quality, sound environments, design and construction solutions.
MORROS CARDONA, JORDI: Segons ús i costum de bon mestre d’obres. Estudi de les tècniques constructives documentades en les esglésies catalanes durant els segles XVII i XVIII.
Author: MORROS CARDONA, JORDI
Programme: DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY
Department: Department of Architectural Technology (TA)
Mode: Normal
Deposit date: 14/05/2026
Reading date: 12/06/2026
Reading time: 11:00
Reading place: ETSAB (Escola Tècnica Superior d'Arquitectura de Barcelona) - Planta Baixa - Sala de GrausAv. Diagonal, 649-651 - 08028 - Barcelona
Thesis director: ONECHA PEREZ, ANA BELEN
Thesis abstract: During the 17th and 18th centuries, an intense period of construction activity took place in Catalonia. In the case of churches, this was a historical period that produced a large number of architectural interventions. Several studies on buildings constructed during the Catalan Baroque period are currently available, but most have focused primarily on historiographical, compositional, and stylistic aspects. Much research has focused on specific regional areas, and some of it on specific buildings. Consequently, to date, no comprehensive description has been made of the construction techniques commonly used in church buildings throughout the 17th and 18th centuries across the Catalan territory. Through a critical analysis of existing scientific and academic contributions, gaps in knowledge regarding the construction techniques used were identified, leading to a specific study that has enabled a more precise and comprehensive description of these techniques. The research method included compiling an inventory of churches with documented interventions, extracting and thematically classifying the information, and providing a final description of the construction knowledge. As a result of applying this method to the case studies, it has been possible to refine, complete, and expand our understanding of the design and execution of church construction projects by their builders. The existence of a sequential construction process for carrying out the works has been confirmed, based on the mastery of the construction trades by the master builders involved, with a specific repertoire of elements and materials. In this regard, for example, the identification of the construction processes for creating large openings in existing walls, increasing the thickness of existing walls, laying roof tiles, the controlled demolition of stone vault masonry for the reuse of materials, the use of protective surface anti-corrosion primers, or the use of bitumen as a sealing material for masonry joints. It has also been possible to analyze the knowledge documented regarding the conservation, deterioration, and repair of churches. A series of common and recurring pathological processes have been identified, consisting of: moisture and leaks in roofs and walls, cracks and fissures in vaults and walls, and the accumulation of dirt on interior surfaces. The causes of these problems were related to a lack of adequate maintenance, the inherent porosity of the materials and prolonged exposure to atmospheric agents, deficiencies in the foundation and the ground, or a lack of sufficient natural ventilation. Meanwhile, it has been found that the descriptions of the repair processes for these problems are quite vague. In any case, the persistent occurrence of structural damage and deterioration led to the drafting of specific conservation and maintenance instructions for churches. The development of the research also required complementary work to identify the construction terminology specific to this period, revealing the richness of technological content within the analyzed architectural language. In many cases, these are expressions that are now unknown due to the disappearance of the construction processes described, as well as terms that have gradually been replaced by others in line with the natural evolution of languages. Therefore, the results obtained are highly valuable for properly understanding and assessing the construction techniques used in architectural interventions of this period in Catalonia, and as a knowledge base for professionals who must undertake such work now and in the future.
XIE, ZEYUE: Development of nonwoven-reinforced ECCCs and multifunctional smart textiles for energy harvesting and thermal management in buildings
Author: XIE, ZEYUE
Programme: DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY
Department: Department of Architectural Technology (TA)
Mode: Normal
Deposit date: 06/05/2026
Reading date: 10/06/2026
Reading time: 11:00
Reading place: Sala Actos INTEXTER - C. Colom, 15 - Edif. TR7 - TerrassaEnlace a videoconferencia: https://meet.google.com/zdd-iyeq-euiConexión a 10:30 (hora Bcn)
Thesis director: ARDANUY RASO, MONICA | VENTURA CASELLAS, HEURA
Thesis abstract: The escalating demand for energy efficiency in modern infrastructure has catalyzed the development of smart building materials capable of active and passive thermal management. While smart textiles and Electrically Conductive Cementitious Composites (ECCCs) offer promising solutions, their practical application is currently hindered by the dispersion limitations of traditional fillers, the mechanical-electrical trade-off, and the lack of multifunctional integration. This thesis addresses these challenges by developing a multifunctional smart fabric and novel nonwoven-reinforced ECCCs, which could culminate in a synergistic, all-weather thermal management system for intelligent building interiors. First, this work addresses the discrepancy in fabric conductivity characterization by establishing a structure-based evaluation framework. Instead of using the same testing method for all materials, contact and non-contact techniques are chosen according to whether the fabric exhibits intrinsic or extrinsic conductivity and its conductivity range, leading to more reliable measurements for different fabric types. Secondly, a multifunctional smart Cotton/Polydopamine/Copper Sulfide/TPU (CO/PDA/CuS/TPU) fabric was fabricated for smart applications. This advanced material integrates anisotropic conductivity, active Joule heating, passive photothermal conversion, and thermoelectric energy harvesting into a single unit. The fabric exhibited rapid active heating (up to 72 °C) and efficient photothermal conversion under solar irradiation. Furthermore, a thermoelectric generator integrated into the fabric demonstrated the capability to harvest energy (350 nW at ΔT = 50 K) and function as a self-powered temperature sensor. Thirdly, a novel ECCC reinforced with stainless steel/polyester (SS/PES) nonwoven fabric was engineered to overcome the agglomeration and loss in mechanical performance issues associated with particulate fillers. The study revealed that the bonding strength of the cement matrix significantly contributes to the generation of the conductive network. An optimal fiber content of 20% was identified near the percolation threshold, which achieved superior electrothermal efficiency compared to higher conductivity formulations (reaching a ΔT of 46.2 °C within 30 minutes at 21 V). The resulting composite demonstrated excellent mechanical properties, durability, and reliable de-icing capabilities. Finally, the functionality of these materials was validated through finite element simulation and experimental testing under varying temperature and humidity conditions. Based on these findings, a closed-loop synergistic ecosystem was proposed, combining the ECCC (as floor heating) and the smart fabric (as curtains). This system dynamically adapts to environmental conditions: utilizing passive photothermal heating and thermoelectric monitoring during the day, and switching to active Joule heating at night, where the curtains recover heat loss from the ECCC elements. This research provides a holistic solution for next generation smart buildings, demonstrating significant potential for energy conservation and intelligent environmental control.

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

PAMIES SAURET, CARLES: Sillerías góticas españolas. Reconstrucción digital mediante fotogrametría de las sillerías góticas españolas: Análisis de la ubicación y funciones del Coro en las Catedrales de los siglos XV-XVI
Author: PAMIES SAURET, CARLES
Programme: DOCTORAL DEGREE IN ARCHITECTURAL, CIVIL AND URBAN HERITAGE AND REFURBISHMENT OF EXISTING BUILDINGS
Department: Departamento de Representación Arquitectónica (RA)
Mode: Normal
Deposit date: 11/05/2026
Reading date: 16/06/2026
Reading time: 11:00
Reading place: ETSAB (Escola Tècnica Superior d'Arquitectura de Barcelona) - Planta Baixa - Sala de GrausAv. Diagonal, 649-651 - 08028 - Barcelona
Thesis director: NAVARRO DELGADO, ISIDRO | SÁNCHEZ RIERA, ALBERTO
Thesis abstract: This doctoral thesis examines the layout, evolution, and functions of choirs in Spanish Gothic cathedrals from the 15th and 16th centuries, distinguished by their location in the central nave. Through an interdisciplinary approach combining historical, architectural, and iconographic analysis with advanced photogrammetric techniques, several choir ensembles are digitally documented. The resulting three-dimensional models provide new interpretations of the Spanish choir model, highlighting its liturgical, symbolic, and socio-political significance, while establishing replicable digital methodologies for heritage documentation, preservation, and dissemination.

DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE

CAZZARO, FRANCESCO: Advancing Text-to-Query Semantic Parsing Systems
Author: CAZZARO, FRANCESCO
Programme: DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE
Department: Department of Computer Science (CS)
Mode: Normal
Deposit date: 07/05/2026
Reading date: 08/06/2026
Reading time: 11:00
Reading place: sala de juntes de la FIB, edifici B6 - Campus Nord UPC (Barcelona)
Thesis director: QUATTONI, ARIADNA JULIETA
Thesis abstract: Executable Semantic Parsing is the task of mapping a natural language sentence into a formal meaning representation that can be executed over a knowledge base to retrieve information. This task presents several challenges. Natural language variability makes the translation process inherently difficult and, at the same time, meaning representations are highly compositional structures built from elementary units. As a result, semantic parsers must exhibit strong compositional generalization, a capability that remains challenging for current models. Moreover, annotated data for semantic parsing is scarce, and its collection is labor intensive and costly, making it difficult to train models.In this thesis, our aim is to improve and advance semantic parsing systems. We introduce a pipeline that decouples the semantic parsing process into two steps, a translation stage and a reordering stage, which enhances the compositional abilities of the parser. We also propose a data generation method that recombines existing annotated pairs in novel ways. This approach improves the generalization capabilities of semantic parsers while alleviating the data scarcity problem.Furthermore, to address the challenge of limited annotated data, we design a novel approach to automatically generate data pairs from a given knowledge graph without the need of human intervention. This generated data can then be used to train a semantic parsing system specifically designed for that particular knowledge graph. This thesis is among the first to explore semantic parsing for property graphs, where we not only introduce the data generation method but also provide an annotated benchmark for evaluating parsing performance.
HERNÀNDEZ CARNERERO, ÀLVAR: Generalizable Time Series Classification Models for Complex Real-World Applications
Author: HERNÀNDEZ CARNERERO, ÀLVAR
Programme: DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE
Department: Department of Computer Science (CS)
Mode: Normal
Deposit date: 23/04/2026
Reading date: 08/06/2026
Reading time: 12:00
Reading place: Sala d'actes de la FIB - Edifici B6 planta 0, Campus Nord
Thesis director: SANCHEZ MARRE, MIQUEL | VAZQUEZ SALCEDA, JAVIER
Thesis abstract: This thesis develops a comprehensive framework for Time Series Classification (TSC) focused on real-world applications characterized by limited data availability, heterogeneous datasets, and complex temporal structure, which concludes with a generalizable and adaptive modelling approach. This research conducts a comprehensive survey of state-of-the-art methods, identifying their strengths and limitations, with a focus on specific domains such as antimicrobial prediction, astronomy, and physiological monitoring. Building on these insights, preprocessing pipelines are developed for the considered time series, including new temporally informed feature generation grounded in domain knowledge, robust feature importance estimation, and wrapper-based feature selection. Methodologically, windowing strategies are engineered to mitigate data scarcity and temporal distribution shifts, a hybrid modular architecture is proposed to integrate mechanisms suited to the specific needs of the data, and an adaptation of additive attention is formulated. The methodology employs ensembles to enhance predictive stability and evaluates model interpretability by analyzing how the trained models prioritize features and by visualizing attention patterns across the sequence to reveal temporal relevance patterns.A central contribution of the thesis is CLAIM (Content-modulated Low-rank Adaptive Isotropic Mixer), a novel architecture for TSC that synthesizes insights from our research and from recent advances in sequence modelling. CLAIM combines content-modulated dynamic mixing, adaptive inductive biases, and a low-rank isotropic block design, resulting in an efficient and interpretable model. Experiments across heterogeneous datasets (including intensive care unit patient trajectories, exoplanet transit signals, and electrocardiogram waveforms) show that CLAIM frequently achieves the best performance in small-data regimes compared to temporal transformer and Multilayer Perceptron Mixer (MLP-Mixer) baselines. CLAIM also offers practical advantages in interpretability, due to its dynamic weights and explicit inductive-bias components. In addition, it demonstrates strong computational efficiency, particularly at inference time. The model modulates structural priors such as locality, causality, and location invariance in a data-driven manner, aligning with effective contemporary design principles for temporal modelling. Furthermore, it adapts its focus across domains, as reflected in the dynamic weighting of temporal components, which corresponds with established domain knowledge.The thesis contributes a unified perspective on real-world TSC, pairing domain-guided pipelines with a generalizable modelling approach. The resulting CLAIM architecture offers an interpretable, efficient, and adaptive solution that advances the state of the art in small-data TSC.
VILALTA ARIAS, ARMAND: Semantic Embeddings in Deep Convolutional Neural Networks
Author: VILALTA ARIAS, ARMAND
Programme: DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE
Department: Department of Computer Science (CS)
Mode: Normal
Deposit date: 26/03/2026
Reading date: 15/06/2026
Reading time: 11:00
Reading place: Sala d'actes de la FIB - Edifici B6, Campus Nord Barcelona
Thesis director: GARCÍA GASULLA, DARIO | CORTÉS GARCÍA, CLAUDIO ULISES
Thesis abstract: One of the fundamental questions in Artificial Intelligence (AI) is how to represent knowledge effectively. The main challenge lies in devising a representation that can be exploited for intelligent computations. Since 2012, when Deep Neural Networks (DNNs) established themselves as the state of the art in Computer Vision, their use has rapidly expanded to a wide range of AI domains, including text and speech recognition, image generation, gaming, and robotics. This widespread success stems from their nature as representation learning techniques. However, DNNs require large volumes of data and considerable computational resources to learn such representations, which significantly limits the range of problems to which these models can be directly applied.In this thesis, we explore the possibility of reusing the knowledge learned by a DNN for a specific problem to solve a different one, which is commonly known as transfer learning. We focus on the representations learned by a DNN, codified in the activations of its neurons in response to an input, namely embeddings. All this work stems from a first analysis to understand where valuable information is encoded in Convolutional Neural Networks (CNNs) within the context of transfer learning. When used for characterizing every class of eleven datasets, we statistically measure the discriminative power of every feature found within a deep CNN. We seek to provide new insights into the behaviour of CNN features, particularly the ones from convolutional layers, which they had not used in previous literature. Our results confirm that low and middle level features may behave differently from high-level features, but only under certain conditions. We find that all CNN features can be used for knowledge representation purposes both by their presence or by their absence, doubling the information a single CNN feature may provide. We also study how much noise these features may include and propose a thresholding approach to discard most of it.This enables the definition of a methodology to improve the generalization capabilities of CNN representations, which we refer to as the Full-Network Embedding (FNE), which successfully integrates convolutional and fully connected features. To do so, the embedding normalizes features in the context of the problem and discretizes their values to reduce noise and regularize the embedding space. Significantly, this also reduces the computational cost of processing the resultant representations. The proposed method outperforms single layer embeddings on several image classification tasks while also being more robust to the choice of the pre-trained model used for obtaining the initial features. The performance gap in classification accuracy between thoroughly tuned solutions and the full-network embedding is also reduced, making the proposed approach a competitive solution for a large set of applications. We consider FNE more semantic as it understands CNN activations as semantic concepts. Similarly to many human languages, it considers if a feature of the input is significant in a given context and if it is because of its presence or absence.A first stem is the use of the FNE as the basis for a network representation of concepts where complex network techniques are applied. We propose the construction of a graph embedding space, introducing a methodology to transform the knowledge coded within a deep convolutional network into a topological space.The second stem, uses the same techniques in the context of multimodal embeddings representing text and images. The FNE provides a multi-scale representation of images, which results in richer characterizations while focusing on the relevant information through its semantic discretization. Results for image annotation and image retrieval tasks show a constant improvement when applied to different existing methodologies.

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

PÉREZ QUINTANA, MARC: Multimodal Data Fusion for Multiple Object Tracking: A Reference Perception System for ADAS and AV Functions Validation
Author: PÉREZ QUINTANA, MARC
Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
Department: Institute of Robotics and Industrial Informatics (IRI)
Mode: Normal
Deposit date: 21/04/2026
Reading date: 18/06/2026
Reading time: 11:00
Reading place: Aula Capella, Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB), Campus Sud, Av. Diagonal, 647 08028 Barcelona
Thesis director: AGUDO MARTÍNEZ, ANTONIO
Thesis abstract: In 2021, 1.19 million people died from traffic accidents, which are the leading cause of death among people aged 5 to 29 years. Most of these accidents are caused by the driver; therefore, automated vehicles present a unique opportunity to reduce fatalities and improve road safety. But the large-scale deployment and adoption of safe automated vehicles require a robust validation procedure, including open-road tests, which are significantly more challenging than tests on proving grounds or in simulation, because there is no ground-truth data on the objects around the vehicle under test. This thesis studies how to build a reference perception system to enable the validation of automated vehicles and advanced driver assistance systems on the open road. We discuss object detection and present a clustering method to detect class-agnostic objects on point clouds. These detections can be projected to the image plane to be combined with image-based detections to improve robustness and add class information. We also present a method to exploit class prototypes, defined as the mean and covariance of the features of that class, to improve the performance of a learning-based object detector on point clouds. Object detections from different modalities can be combined in the presented multiple object tracking method, which works without assuming sensor synchronization and can be adapted to include object information from any source, such as vehicle-to-vehicle communications, and includes the handling of common errors that are understudied in the literature: Misclassifications and partial bounding box detections. These object detectors and multiple object trackers can be evaluated with a novel proposed methodology to evaluate perception systems focusing on safety, which we use to evaluate the effect on object detection performance of different weather conditions and the robustness layers included in recent testing protocols. We also present a pipeline to extract scenarios in standardized formats from recorded images and point clouds, that can be directly used by a simulator. Finally, we discuss how scenario extraction, combined with other tools, can help in the validation of automated vehicles on the open road.

DOCTORAL DEGREE IN BUSINESS ADMINISTRATION AND MANAGEMENT

DÍAZ MEDIAVILLA, MARIA ESTELA: Estudio comparativo de la percepción del riesgo laboral entre diferentes colectivos dentro del sector de la construcción
Author: DÍAZ MEDIAVILLA, MARIA ESTELA
Programme: DOCTORAL DEGREE IN BUSINESS ADMINISTRATION AND MANAGEMENT
Department: Department of Management (OE)
Mode: Normal
Deposit date: 05/05/2026
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: ABAD PUENTE, JESUS
Thesis abstract: Objective — The main objective of this study is to empirically evaluate differences in risk perception between construction workers and health and safety managers. Additionally, it aims to determine the effect of work experience and accident experience (both direct and witnessed) on the rational and emotional dimensions of this perception.Methodology — A cross-sectional quantitative design was adopted using a psychometrically validated questionnaire. The final sample consisted of 349 professionals from the construction sector in Catalonia. Data were analyzed using principal component analysis and confirmatory factor analysis to validate the construct structure, followed by multiple linear regression models with interaction terms to test the study hypotheses.Results — The findings empirically demonstrate that, within the analyzed sample, risk perception has a three-dimensional structure composed of rational risk perception, emotional perception of moderate-severity risks, and emotional perception of high-severity risks. A significant safety perception gap was identified: health and safety managers exhibit higher levels of emotional perception regarding high-severity risks compared to workers. In addition, both work experience and accident experience exert different effects on risk perception depending on the dimension analyzed and the professional group considered.Conclusions — Risk perception in the construction sector presents a more complex structure than the traditional two-dimensional conception. The empirical evidence indicates that rational risk perception remains a single dimension, whereas emotional perception is divided into two distinct subdimensions depending on the severity of the potential harm: one related to moderate-severity risks and another associated with high-severity risks. Furthermore, perceptual differences between workers and health and safety managers emerge exclusively in the emotional response to high-severity risks. Finally, experiential factors influence risk perception differently depending on professional role, highlighting the complexity of the cognitive and affective processes involved in risk evaluation in hazardous work environments such as the construction industry.Implications — The findings suggest moving away from “one-size-fits-all” safety approaches. Safety management systems should incorporate training methodologies with a strong emotional impact, such as virtual reality simulations, to reduce workers’ tolerance to risk. For health and safety managers, it is advisable to implement recalibration mechanisms, such as cross-audits and project rotation, to mitigate the overconfidence bias associated with accumulated experience.Limitations — The study has a cross-sectional design, which prevents establishing strict causal relationships in the evolution of risk perception. Furthermore, the data are based on self-reported responses, which may differ from actual on-site perception. Finally, the research context is limited to the construction sector within a specific geographical area, suggesting the need to replicate the model in other high-risk industries.Future Research — Future studies should adopt longitudinal designs to examine how risk perception evolves following exposure to critical events. It would also be valuable to incorporate neurophysiological measurements to capture workers’ immediate emotional responses to risk. Additionally, future research could examine perceptual mimicry within work teams in order to better understand how organizational culture shapes individual risk tolerance.
GAMARRA GAMARRA, MARÍA DEL PILAR: Comportamiento Ético: Identidad Moral, Atención Moral y su papel en la Construcción del Liderazgo Ético
Author: GAMARRA GAMARRA, MARÍA DEL PILAR
Programme: DOCTORAL DEGREE IN BUSINESS ADMINISTRATION AND MANAGEMENT
Department: Department of Management (OE)
Mode: Normal
Deposit date: 30/04/2026
Reading date: 25/06/2026
Reading time: 15:30
Reading place: Seminari 1 DOE - Planta 7 de l'ETSEIB-UPCDefensa, acte públic: meet.google.com/afg-drtc-azc
Thesis director: OLIVELLA NADAL, JORGE | GIROTTO, MICHELE
Thesis abstract: When a leader acts without ethics, the entire organization is shaken; when leadership is exercised with integrity, it inspires sustainable cultures and strengthens social trust. This doctoral thesis addresses the challenge of understanding how leaders perceive and enact their own ethical behavior, focusing on two fundamental internal drivers: moral identity and moral attentiveness. These factors, often invisible in everyday organizational discourse, distinguish formal leadership from authentic leadership capable of generating legitimacy, resilience, and commitment in complex contexts.The research is grounded in a clear diagnosis: financial scandals, corporate misconduct, and growing social demands for transparency have placed ethics at the center of the business agenda. However, most previous studies have examined ethical leadership from the perspective of subordinates or within Anglo-Saxon contexts, leaving aside the leader’s own viewpoint and the analysis of specific cultural realities such as the Spanish context. This is the gap that the thesis seeks to address.The study is developed in two phases. The first presents a bibliometric analysis and a systematic review of more than thirty years of scientific literature, identifying three theoretical pillars of ethical leadership: values-based theories, cognitive moral development theory, and social learning theory. This review highlights the fragmentation of existing approaches and the scarcity of empirical studies focused on leaders’ self-perceptions, as well as the need to incorporate variables such as gender, age, and hierarchical level.The second phase builds an empirical model applied to the Spanish context. To this end, the classic ethical leadership scale is psychometrically validated and adapted to leaders’ self-perceptions through exploratory and confirmatory factor analyses, reliability tests, and structural equation modeling. The process includes expert review, pilot testing, and the administration of questionnaires to a sample of managers from different sectors. The result is a robust, context-adapted scale that identifies three dimensions of self-perceived ethical leadership: integrative decision-making, the reinforcement of ethical behaviors, and the leader’s personal example as a role model.The findings show that moral identity and moral attentiveness significantly influence these dimensions, albeit in different ways. The internalization of moral identity predicts the integration of ethical principles into decision-making, while the symbolization of moral identity and reflective moral attentiveness explain the tendency to reinforce ethical behaviors. In addition, variables such as gender, age, managerial experience, and hierarchical position act as moderators, indicating that ethical leadership emerges through the interaction of personal and professional characteristics.Overall, this thesis demonstrates that ethical leadership is not an abstract code or a superficial discourse, but a practice rooted in the leader’s internal coherence, reflected in decision-making, and projected onto organizational culture, contributing to the development of more just and sustainable organizations.

DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING

FERNANDEZ, LORETTE SYLVIE JACQUELINE: Design and Characterization of More Sustainable Molecular Solar Thermal Energy Storage Systems
Author: FERNANDEZ, LORETTE SYLVIE JACQUELINE
Programme: DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING
Department: Department of Chemical Engineering (EQ)
Mode: Normal
Deposit date: 20/05/2026
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: MOTH-POULSEN, KASPER
Thesis abstract: Energy demand and consumption associated with global population growth are driving an energy transition from fossil fuels to more sustainable alternatives, with storage at the core of this revolution. Among the various approaches, molecular solar thermal energy storage (MOST) is gaining increasing attention. The emission-free MOST systems capture solar energy, store it chemically, and release it on demand in the form of heat. This thesis examined three strategies to further promote the sustainability of MOST systems. The first relies on enhancing the performance of a small liquid solar energy-harvesting device by introducing various reflective elements beneath the collector. An increase of 0.1% in solar energy storage efficiency is achieved compared with a non-reflective background. The second strategy focuses on employing surfactants to disperse organic MOST photoswitches in water. Sunlight (simulated) harnessing and macroscopic heat release (under ambient conditions) of 4.7 °C are demonstrated in such formulations. The third examines the optical properties of MOST coatings based on cellulose nanocrystals for the development of solid-state devices. Overall, these strategies pave the way for future sustainable research directions for MOST systems.

DOCTORAL DEGREE IN CIVIL ENGINEERING

APARICIO URIBE, CARLOS HUMBERTO: EXPERIMENTAL AND NUMERICAL ANALYSIS OF FLOOD-RELATED HAZARD ASSOCIATED WITH THE EVACUATION OF UNDERGROUND STAIRS
Author: APARICIO URIBE, CARLOS HUMBERTO
Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
Department: Barcelona School of Civil Engineering (ETSECCPB)
Mode: Article-based thesis
Deposit date: 05/05/2026
Reading date: 12/06/2026
Reading time: 12:00
Reading place: UPC Campus Nord, ETSECCPB, C/ Jordi Girona 1-3, edificio C1, Sala 002, Barcelona
Thesis director: RUSSO, BENIAMINO | TELLEZ ALVAREZ, JACKSON DAVID
Thesis abstract: The rapid pace of urbanisation has led to the widespread development of underground infrastructure worldwide. Currently, these infrastructures have become increasingly vulnerable to climate-induced extreme weather events such as flooding, particularly in metro stations. Given the unique characteristics of urban underground clusters, stairs serve a dual and critical role during emergencies: they are often the primary evacuation route while simultaneously serving as the main entry path for the incoming floodwaters. This doctoral research explores the interaction between hydrodynamic forces and human evacuation on flooded stairs within underground environments. The study aims to achieve a better understanding of these interactions to identify stability thresholds, establish safety criteria, and develop effective evacuation strategies. A comprehensive approach to the problem was adopted by integrating both experimental and numerical methods.A thorough state-of-the-art review was conducted to identify the current knowledge landscape, highlighting key findings, limitations and potential further exploratory lines. The experimental component of this thesis was based on a full-scale replica constructed at the hydraulic laboratory of the School of Civil Engineering at the Universitat Politècnica de Catalunya – BarcelonaTech (UPC). This represented the flood-prone access stairs of the Paral·lel metro station, which is part of Barcelona’s Metro Network. The stairs’ hydraulic characterisation was followed by a series of experimental tests involving individual subjects walking the flooded stairs under varying discharge conditions and footwear types. Additional tests were assessed under the facility’s maximum discharge, with subjects simultaneously walking the flooded stairs in groups of two and three. A first individual subject's campaign aimed to identify thresholds for pedestrian instability, while a second one intended to optimise evacuation based on the different studied grouping configurations.To complement the experimental observations, several three-dimensional Computational Fluid Dynamics (3D-CFD) simulations were performed using the commercial software FLOW-3D. These simulations analysed the water-dragging force considering single subjects and pedestrian arrangements, providing a detailed identification of hydraulic parameters and water forces throughout the stairs’ domain. This research offers novel insights into flood risk management in urban areas, taking into account their site-specific constraints, particularly access to underground spaces via stairs. Special attention is given to subjects evacuating simultaneously, as well as optimal strategies for managing group evacuations. The outcomes offer valuable, actionable data for engineers, urban planners, and emergency responders. In this way, it will ultimately contribute to improving evacuation safety and hydraulic understanding of flooded underground stairs through the integration of experimental and numerical analysis, thereby fostering urban resilience and evacuation planning in flood-prone underground infrastructures.
GARCIA RIVERA, JUAN PABLO: ESTUDIO EXPERIMENTAL DE LA CONFLUENCIA DE LOS RÍOS TOLTÉN Y ALLIPÉN (CHILE): RESULTADOS HIDRODINÁMICOS
Author: GARCIA RIVERA, JUAN PABLO
Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
Department: Barcelona School of Civil Engineering (ETSECCPB)
Mode: Normal
Deposit date: 20/05/2026
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: MARTÍN VIDE, JUAN PEDRO | FERRER BOIX, CARLES
Thesis abstract: This thesis was motivated by the need to understand the hydrodynamic behavior of the confluence of the Toltén and Allipén rivers (Chile), where a bedload measurement campaign was conducted over 90 days in 2013 using a Helley-Smith sampler. During this campaign, gravel and sand transport was recorded with a non-uniform transverse spatial distribution in the measurement section (transect), referred to in this thesis as section 9. However, the lack of simultaneous hydrodynamic measurements prevented the establishment of cause-and-effect relationships between flow and sediment transport distribution.During the field campaign, individual and total flow rates were also recorded, with values between 180 and 900 m³/s. This information served as the basis for developing experimental scenarios in the physical model.The overall objective of this thesis was to understand the hydrodynamic behavior (three-dimensional velocity field) of this confluence in order to identify patterns that can be generalized to confluences with similar characteristics. The physical model was constructed in the Hydraulics Laboratory of the University of Piura (Peru), with a geometric scale of 1:57.9 defined, conditioned by spatial constraints of the model site. The range of flow rates tested in the model varied between 7.7 and 32.8 l/s.The experiments were designed considering different flow combinations, characterized by a Q_tributary/Q_main flow ratio, whose values ranged between 0.33 and 3.97.The experimental campaign included the calibration of triangular weirs for flow control and the definition of boundary conditions through one-dimensional modeling, using information from the prototype.Sixteen cross-sections were measured, with special emphasis on sections 6, 8, 9, and 11, near the reference transect. A total of 1641 three-dimensional velocity measurements (u, v, w) were taken, recorded at 25 Hz for 120 seconds per point, generating more than 3000 data points per measurement.Data processing was performed in Matlab using proprietary algorithms that included correlation and noise filtering (AADV and CADV), application of the Space-Phase Thresholding method, and Wavelet decomposition. The latter allowed the signal to be separated into low-frequency components (pulsations) and high-frequency components (turbulent fluctuations), facilitating a more in-depth analysis of the flow's temporal structure.Additionally, low-frequency pulsations were identified in each measurement; over a 2-minute period, these pulsations were observed to repeat 6 times. The application of dyes visually confirmed these periodic mixing patterns.From the three-dimensional velocity field, different stress components were estimated: Reynolds stress, low-frequency stress, total stress, cross stresses, and near-bottom stresses. The stresses obtained were compared with the critical stress at the onset of movement for a dimensionless Shields parameter of 0.03 (sands and gravels), allowing the identification of potential bed mobilization zones.Finally, the main contribution of this thesis lies in the detailed experimental characterization of the three-dimensional hydrodynamic field at a confluence with morphological unconformity, through the direct measurement of the three instantaneous velocity components and the analysis of their fluctuations. The results obtained provide physical and methodological criteria transferable to the study of river confluences with similar geometric and hydraulic characteristics.
LOPEZ CHACON, SERGIO RICARDO: Enhanced short-term prediction of high streamflow combining physically based and machine learning models
Author: LOPEZ CHACON, SERGIO RICARDO
Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
Department: Barcelona School of Civil Engineering (ETSECCPB)
Mode: Article-based thesis
Deposit date: 21/04/2026
Reading date: 11/06/2026
Reading time: 12:30
Reading place: UPC Campus Nord, ETSECCPB, C/ Jordi Girona 1-3, edificio C1, Sala 002, Barcelona
Thesis director: BLADE CASTELLET, ERNEST | SALAZAR GONZÁLEZ, FERNANDO
Thesis abstract: Machine learning models have demonstrated a strong potential in the recent decade for streamflow prediction purposes. Even reaching considerable accuracy, machine learning models still present some limitations and little explore aspects on this topic: the accuracy decrease on high streamflow, uncertainty estimation applications, and hydrological interpretation of models. High streamflow values are the most relevant for early warning systems of flood mitigation. However, these records are scarce in the data. Hence, a decrease in accuracy is seen, which gets deeper in extrapolated scenarios. This thesis proposes two methodologies that support machine learning models with the outputs of a physically based model to enhance the prediction capabilities in high streamflow prediction. The first methodology produces a machine learning model trained with a combination of observed and synthetic high streamflow events generated by a physically based model. The second methodology creates a hybrid model that combines outputs based on a physically based model and the prediction of its residuals by a machine learning model. Both methodologies have shown accuracy improvements compared to models trained only with observed data, reaching reductions of root mean square errors of more than 23% for streamflow values larger than the 3-year return period in the study area. However, the second methodology reaches closer approximations to the peak observed value with significant extrapolation capabilities. Despite the accuracy, the uncertainty related to the model is a main topic to explore. A methodology to estimate the uncertainty of the output of a streamflow prediction model by employing machine learning techniques is developed in the thesis. The results of the methodology show that the distributions of the residuals can be acceptably described. Consequently, the uncertainty interval covers 87.9% of the observed values higher than the 3-year return period with a width of interval significantly smaller than the broadly used Box-Cox method. Finally, the hydrological interpretation of a machine learning model for streamflow prediction is undertaken. The results show that the model may identify areas of the catchment whose runoff considerably contributes to the control point, as well as period of previous soil saturation, and the impact of the highest precipitation values in the model’s prediction. When the hydrograph rises steeply, the model acceptably considers the recent accumulated precipitation as the most relevant features along with previous saturation. As the hydrograph peak approaches and during the falling limb, previous streamflow acquires main relevance supported by runoff of distant regions. The machine learning model can suitably interpret the catchment system and provide valuable information.

DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS

LOPEZ ALVAREZ, CIBRAN: Unveiling correlated charge dynamics and recombination pathways in energy materials via quantum simulations and machine learning
Author: LOPEZ ALVAREZ, CIBRAN
Programme: DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS
Department: Department of Physics (FIS)
Mode: Article-based thesis
Deposit date: 19/05/2026
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: CAZORLA SILVA, CLAUDIO | SAUCEDO SILVA, EDGARDO ADEMAR
Thesis abstract: Understanding how atomic-scale mechanisms govern ionic and electronic transport is crucial for the design of next-generation energy materials. Here, we combine first-principles simulations and machine-learning techniques to provide predictive and transferable approaches for modelling and understanding at the atomistic scale solid-state electrolytes and pnictogen chalcohalide (MChX, with M = Bi, Sb; Ch = S, Se; and X = I, Br) photovoltaics.Our first-principles calculations and unsupervised learning investigations revealed that ionic diffusion in solid-state electrolytes is fundamentally governed by correlated motion of multiple ions. These cooperative events are strongly influenced by lattice vibrations, linking ionic conductivity to both vibrational dynamics and elastic properties of the non-diffusive crystal framework. Characteristic correlation lengths, remarkably independent of temperature, were identified, providing new descriptors for the design of fast-ion conductors. In addition, a comprehensive first-principles simulations database and automated analysis tools were developed, offering a scalable platform for understanding ionic transport across diverse material families and compositions.At the same time, first-principles simulations combined with deep learning and device-level modeling identified and experimentally validated MChX-based solid solutions with tunable band-gaps (1.2–2.1 eV) and strong absorption coefficients (up to 66 μm⁻¹), demonstrating the potential of MChX tandems to achieve short-circuit currents exceeding 18 mA/cm². Further ab initio calculations revealed chalcogen vacancies as dominant non-radiative centers in MChX, potentially limiting efficiencies down to 24% in BiSeI. However, targeted anion substitution and synthesis conditions were shown to suppress these detrimental recombination-active centers.Together, the work realised during this doctorate establishes generalizable frameworks that connect atomistic mechanisms to macroscopic device performance. The methodologies introduced here are readily transferable to other families of materials and functional applications, providing a roadmap for the rational design of high-performance, sustainable energy technologies.

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

DE LIMAS SANTANA, ALEXANDRE: Beyond 512-bit vectors: Optimized and performance portable AI operators on vector-length-agnostic architectures
Author: DE LIMAS SANTANA, ALEXANDRE
Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
Department: Department of Computer Architecture (DAC)
Mode: Normal
Deposit date: 11/05/2026
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: CASAS GUIX, MARC | ARMEJACH SANOSA, ADRIÀ
Thesis abstract: This thesis addresses the challenges of producing high-performance, portable code for arithmetic-intensive operations in Deep Neural Network (DNN) workloads, such as convolutions and matrix multiplications.It targets emerging vector and matrix architectures exposing software interfaces to program accelerators via Instruction Set Architecture (ISA) extensions.It proposes techniques to handle three main challenges related to accelerating DNN workloads on contemporary data-parallel CPU architectures: i) extrapolating software optimization techniques designed primarily for high-end general-purpose vector processors to also accomodate edge devices and long vector accelerators hardware, ii) providing performance portability for open standard vector ISA ecosystems, like RISC-V, characterized by their unprecedent micro-architectural discrepancy among implementations, and iii) designing matrix multiplication ISA extensions that uphold the core principles of emerging vector architecture concerning implementation flexibility, such as vector length agnosticism.This thesis presents empirical evidence that existing software optimization techniques for generating high-performance implementations of DNN operators for modern vector processors are biased toward high-end general-purpose systems with 512-bit vectors (e.g., Intel Cascade Lake, Fugaku AF64X).The techniques presented in the thesis support the idea of hardware/software co-design and the need to consider microarchitectural features, such as vector length, non-conventional memory subsystems, and the presence/lack of out-of-order pipelines, when generating code for vector and matrix processors.Specifically, this thesis employs runtime specialization to adapt established DNN algorithms to a broader range of processor designs, equipping applications with flexible code generators that dynamically optimize the algorithms for the specific combination of the platform's microarchitectural features and the operation's hyperparameters. The thesis makes three key contributions.First, it provides the first performance analysis of convolution workloads on a 16,384-bit vector processor, identifies cache conflict misses in existing techniques, and proposes software corrections that yield up to 1.83x speedups over prior approaches.Second, it introduces a dynamic matrix multiplication and convolution code generator that adapts algorithmic optimization techniques, such as register unrolling, to the vector width of the target platform.A performance analysis of three commercially available RISC-V systems running computer vision workloads shows geometric speedups ranging from 1.43x to 3.58x compared to state-of-the-art libraries.Third, it proposes a Matrix Tile Extension (MTE) to supplement vector-length-agnostic ISAs with geometry-agnostic matrix multiplication and memory operations.Two microarchitectures supporting this extension are described: a lean extension of an 8192-bit vector processor and a systolic-array-based design, both of which utilize vector registers for matrix storage and demonstrate 1.35x geometric mean speedups on GEMM and convolution workloads.
SHAKESPEAR MILES, HAILEY JOSEPHINE: Multi-Agent Systems for Optical Networks
Author: SHAKESPEAR MILES, HAILEY JOSEPHINE
Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
Department: Department of Computer Architecture (DAC)
Mode: Normal
Deposit date: 15/05/2026
Reading date: 09/07/2026
Reading time: 16:00
Reading place: Sala de Actos Manuel Martí Recober, FIBC. Jordi Girona, 1-308034 Barcelona
Thesis director: VELASCO ESTEBAN, LUIS DOMINGO | BARZEGAR, SIMA
Thesis abstract: Unlike earlier mobile generations, 6G is expected to support a wide range of applications such as immersive communications, remote healthcare, autonomous transportation, and smart cities. These use cases will significantly increase the number of connected devices and impose stringent requirements on bandwidth, latency, reliability, and energy efficiency. As a result, the networks supporting these services will face major challenges in scalability, resource management, and control. In this context, this doctoral thesis investigates the use of Multi-Agent Systems (MAS) as a foundation for next-generation network control. The goal of this thesis is to design and evaluate MAS-based solutions that improve the intelligence, scalability, and energy efficiency of optical networks across both the optical and packet layers.The first objective addresses the optical layer by investigating centralized and distributed MAS-based approaches for dynamic spectrum control in point-to-multipoint (P2MP) connections. A centralized solution based on traffic prediction and integer linear programming computes optimal allocations under near-real-time constraints, achieving high spectrum utilization but introducing synchronization and scalability limitations. To overcome these issues, distributed architectures are proposed in which transponder agents perform decision-making locally. Three strategies are studied: a mixed-strategy gaming model, a distributed deterministic algorithm, and a multi-agent reinforcement learning (MARL) approach. The MARL solution achieves the best overall performance by anticipating traffic variations and allocating capacity proactively, while distributed methods significantly improve scalability and robustness. Communication efficiency is also studied with the MARL approach allowing for asynchronous operation and reducing inter-agent messaging. Results show that distributed MAS can approach centralized performance while avoiding bottlenecks and single points of failure.The second objective focuses on the packet layer, where an extended MAS architecture enables end-to-end near-real-time control of network services (NS) through autonomous flow operation. Routing decisions are driven by telemetry and optimized using Deep Reinforcement Learning (DRL) to minimize delay and operational cost, while agents monitor performance and coordinate with the software-defined networking (SDN) controller. The architecture supports the full lifecycle of a NS, including deployment, dynamic reconfiguration, and handover scenarios. A model-selection approach based on offline training and real-time telemetry is proposed, together with an active probe-testing mechanism and long short-term memory (LSTM) based traffic prediction trained online by flow agents. Simulations demonstrate that transferring of trained models between agents enables accurate predictions and knowledge generation allowing for fast reconfiguration decisions while maintaining QoS over the NS. This MAS architecture provides the foundation for the third objective where experimental results demonstrate reliable QoS maintenance and effective MAS reconfiguration during operation.In conclusion, this thesis shows that MAS combined with learning-based decision-making, predictive analytics, and distributed control provide a flexible and effective framework for managing future networks. The proposed solutions improve scalability, adaptability, and energy efficiency while maintaining strict performance guarantees, establishing MAS as a key enabler for intelligent and autonomous 6G networks.

DOCTORAL DEGREE IN EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS

MOMIN, SAMAR: An AI-Augmented Scalable Framework for High-Resolution Exposure and Seismic Risk Assessment
Author: MOMIN, SAMAR
Programme: DOCTORAL DEGREE IN EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS
Department: Department of Civil and Environmental Engineering (DECA)
Mode: Normal
Deposit date: 13/05/2026
Reading date: 06/07/2026
Reading time: 16:00
Reading place: ETSECCPB.UPC, Campus NordBuilding C1. Classroom: 002C/Jordi Girona, 1-308034 Barcelona
Thesis director: CARREÑO TIBADUIZA, MARTHA LILIANA
Thesis abstract: Large-scale high-resolution probabilistic seismic and multi-hazard risk assessments depend critically on how exposure is represented and how appropriately vulnerability functions are assigned to heterogeneous building stocks. While hazard modelling has achieved a high degree of harmonisation and vulnerability modelling has achieved a high level of computational maturity, the exposure–vulnerability interface remains manual, typology-driven and difficult to scale consistently. In Barcelona and across Catalonia, vulnerability functions derived from single buildings or limited samples have frequently been extrapolated across portfolios using coarse classifications. When hazard, exposure and damage-to-loss models are held constant, this practice produces substantial spreads in portfolio loss metrics. It first quantifies that variability through a controlled vulnerability-only sensitivity analysis for Barcelona. Using a consistent probabilistic seismic hazard backbone and unified damage-to-loss mapping, published vulnerability-function sets are interchanged while all other components remain fixed. Results show that Average Annual Loss (AAL) varies from approximately €25.6 million to €348.0 million depending solely on the selected vulnerability dataset, demonstrating order-of-magnitude sensitivity attributable to function assignment. A focused pilot in the Eixample district confirms that detailed, manual reassignment (e.g., corner versus centre block positions) improves local realism but does not scale to city- or regional-level portfolios.To address this structural limitation, the second step moves from ad-hoc assignment toward repeatable and transparent exposure. The thesis develops a geometry-driven exposure structuring workflow through Building Footprint Analysis, Classification and Grouping (BFA/BFC/BFG). High-resolution cadastral building footprints from Catalonia are used to extract dimensions and are transformed into interpretable, reproducible plan-shape classes using previously computed shape metrics to define sides-based classes. Results from comparative analysis of several shape metrics show that simple compactness measures agree on regular rectangles and squares but blur important differences for elongated, irregular and opening-based plans. This reveals redundancy among scalar compactness indices and limited discriminatory power for articulated and opening-based geometries, highlighting the need for an alternative capable of preserving fine-grained distinctions relevant to structural behaviour.The Building Footprint Analysis, Recognition and Classification framework (BFARC-YOLO) builds on this basis to enable scalable AI-augmented exposure classification. Approximately 1.8 million building footprints are rendered as oriented silhouettes and progressively trained using ~0.34% labelled samples. The final model achieves mean average precision (mAP@0.5:0.95) ≈ 0.96 across 44 fine-grained classes. GPU optimisation reduces regional inference time from over 490 hours (CPU baseline) to ~72 hours, demonstrating operational feasibility. Interoperability with the GEM taxonomy enables direct integration into established risk platforms and a lightweight web interface supports auditable batch inference.Rather than developing novel fragility functions, this thesis offers modelling infrastructure. It creates a replicable bridge from cadastral geometry to vulnerability-aligned exposure classification, minimising subjectivity in vulnerability assignment and allowing for scalable, transparent portfolio risk modelling. By reframing exposure as a structured, learning-enabled modelling layer, the study lays the groundwork for future fragility calibration, and next-generation multi-hazard risk assessments for dense and heterogeneous cities, regions, countries and the global scale.

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

ROSSI, FRANCESCA: Machine Learning Tools for Power Systems Optimal and Stable Operation
Author: ROSSI, FRANCESCA
Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
Department: Department of Electrical Engineering (DEE)
Mode: Normal
Deposit date: 19/05/2026
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: PRIETO ARAUJO, EDUARDO | GOMIS BELLMUNT, ORIOL
Thesis abstract: The rapid decarbonization of power systems and the large-scale integration of inverter-based resources (IBRs), high-voltage direct current (HVDC) links, and power-electronics-based technologies are profoundly transforming the dynamic behavior of modern electric grids. These changes introduce new stability challenges, particularly related to small-signal stability, which are not adequately addressed by conventional operational tools. At the same time, system operators face increasing requirements for fast, reliable, and optimal decision-making under highly variable operating conditions.This thesis proposes a comprehensive framework based on machine learning (ML) techniques to support the optimal and stable operation of modern power systems. The core contribution is the development of data-driven surrogate models for small-signal stability assessment and stability performance indicators, enabling their efficient integration into operational decision-making processes. To support this objective, and to address the scarcity of representative training data, an efficient methodology for large-scale synthetic data generation and multidimensional operating space exploration is developed, with particular attention to systems with high penetration of IBRs.Building on these surrogate models, the thesis introduces regression-based small-signal stability constraints that can be embedded into optimization frameworks. In particular, a stability-constrained optimal power flow (SSSC-OPF) formulation is proposed for computing statically feasible and dynamically stable operating points in online operation and operational planning, while a small-signal stability-constrained online feedback optimization (SSSC-OFO) framework is developed to enable continuous, model-free, real-time adjustment of generator dispatch based on measurements.Furthermore, the work addresses the critical role of power electronic converter control by proposing data-driven methods for the selection and assignment of converter control roles in hybrid AC/DC grids. Clustering, dimensionality reduction, and knowledge extraction techniques are employed to identify stability-enhancing control configurations across the system operating space.Finally, a data-driven multi-criteria decision-making framework is presented to support real-time converter control role assignment, combining ML-based performance prediction with operational criteria. Case studies on realistic power system models and academic test systems demonstrate the effectiveness, scalability, and computational advantages of the proposed approaches. Overall, the thesis shows that ML-based tools can significantly enhance the ability of system operators to ensure optimal and small-signal stable operation in future power-electronics-dominated grids.

DOCTORAL DEGREE IN ENGINEERING, SCIENCES AND TECHNOLOGY EDUCATION

JULIAN TRUJILLO, EDWIN CRISTIAN: Modelización Flexible y actividad matemática en Ingeniería: análisis de la interpretación, simulación y validación de sistemas dinámicos no lineales
Author: JULIAN TRUJILLO, EDWIN CRISTIAN
Programme: DOCTORAL DEGREE IN ENGINEERING, SCIENCES AND TECHNOLOGY EDUCATION
Department: Institute of Education Sciences (ICE)
Mode: Normal
Deposit date: 12/05/2026
Reading date: 25/06/2026
Reading time: 12:00
Reading place: Aula ferroviària. 2.08. Edifici VGA. EPSEVGAvda. Victor Balaguer 108800 Vilanova i la Geltrú
Thesis director: GOMEZ URGELLES, JOAN VICENÇ
Thesis abstract: The teaching of differential equations in engineering remains marked by a dissociation between procedural rigor and the need to interpret, simulate, and validate dynamic systems in professional settings. This dissertation examines how a Flexible Modeling approach transforms the mathematical activity of engineering students when their work with differential equations shifts away from isolated solution procedures toward exploration, comparison, and model-based justification. Adopting a situated, longitudinal, and mixed-methods design, the study articulated didactic units, computational laboratories, and discipline-based projects, which were analyzed through the triangulation of academic products, artificial intelligence auditing, laboratory work, and technical defenses. The analysis reveals a consistent shift toward forms of mathematical activity centered on parametric sensitivity, dynamic system interpretation, and the technical validation of results. In particular, simulation functioned as an environment for epistemic contrast, while the auditing of automated responses strengthened students’ ability to question results that were inconsistent with the Jacobian, the phase plane, and the physical plausibility of the phenomenon. The dissertation concludes that Flexible Modeling shifts the focus of instruction from algorithmic execution toward interpretation, validation, and technical justification, although this process shows uneven appropriation depending on students’ prior mathematical background. In this sense, mathematics is repositioned as a language of diagnosis and auditing in the age of automation

DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING

CUESTA I MOTA, DÍDAC: Desenvolupament de tecnologies electroquímiques per a l’obtenció d’hidrogen en el tractament d’efluents industrials tèxtils
Author: CUESTA I MOTA, DÍDAC
Programme: DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING
Department: Department of Civil and Environmental Engineering (DECA)
Mode: Normal
Deposit date: 12/05/2026
Reading date: 14/07/2026
Reading time: 11:00
Reading place: Place: ETSECCPBUPC, Campus NordBuilding C1. Classroom: 002C/Jordi Girona, 1-308034 Barcelona
Thesis director: LOPEZ GRIMAU, VICTOR | CANALS CASALS, LLUC
Thesis abstract: In the current context of climate emergency and water stress, the textile industry faces the challenge of reducing its high water consumption and its greenhouse gas emissions. This thesis investigates the feasibility of an innovative electrochemical system capable of simultaneously performing the purification of complex waste effluents and the production of hydrogen, thus integrating wastewater treatment with the generation of an energy vector without direct CO2 emissions.The study identifies dye effluents with reactive dyes and mercerizing effluents as the most suitable for the integration of a dual system, thanks to their high conductivity and alkalinity. While mercerizing effluents act as an ideal electrolyte for alkaline electrolysis due to their 20% NaOH content, dye effluents contain recalcitrant azoic reactive dyes that cannot be removed by conventional biological methods, but are highly sensitive to electrochemical oxidation.One of the pillars of the thesis is the design and validation of a sandwich-type bi-compartmentalized electrochemical cell with an anion exchange membrane (AEM). This configuration allows separating the waste effluent at the anode from the alkaline electrolyte at the cathode, avoiding hydrogen contamination and improving the energy efficiency of the treatment. Experimental results demonstrate a decolorization efficiency higher than 99% for diverse reactive dyes and hydrogen generation with a purity of 98,7%. The optimal configuration that balances energy efficiency, treatment time, and material cost for the treatment is also determined, with a current density of 150 mA/cm2 and a combination of a Ni cathode and an Ir-Ru/MMO or BDD anode depending on whether the effluent contains NaCl or Na2SO4.Furthermore, a computer model has been developed using the eCherry library (Modelica) that allows predicting the behavior of the system with a maximum error of 5% in the expected decolorization and 2,1% in the working voltage.In conclusion, the work demonstrates that electrochemical treatment is not only an effective solution for the decolorization of dye effluents but also becomes a strategic pathway for the circular economy, allowing the energy recovery of hydrogen through blending in boilers, and opening the door to the reuse of water, salts, and alkali.

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

ALHARFOUCH, LOUJAIN: Integrating ecohydrological, isotopic, and numerical approaches to assess water use by montane Scots pine under varying wetness conditions
Author: ALHARFOUCH, LOUJAIN
Programme: DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING
Department: Department of Civil and Environmental Engineering (DECA)
Mode: Normal
Deposit date: 14/05/2026
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: HIDALGO GONZÁLEZ, JUAN JOSÉ | LATRON, JÉRÔME
Thesis abstract: Ecohydrology provides a critical framework for understanding interactions between vegetation and the hydrological cycle, particularly in forested ecosystems that strongly regulate water fluxes and ecosystem resilience. In Mediterranean mountain regions, increasing climate variability and recurrent droughts place forests close to their hydraulic limits. Despite these mounting pressures, key uncertainties remain regarding how trees access, store, and utilize water across contrasting wetness conditions, and how these processes can be represented in ecohydrological models.This thesis investigates tree water uptake dynamics and their representation by integrating high temporal- and spatial-resolution field observations, stable water isotopes, and process-based modeling. The study was conducted in the Vallcebre Research Catchments (NE Spain), focusing on Scots pine (Pinus sylvestris L.). Field observations combined meteorological measurements, sap flow and stem diameter variations, soil water content and potential, groundwater levels, and weekly water stable isotopes sampling of precipitation, soil water, groundwater, and xylem water. These data were analyzed using statistical approaches and numerical modeling to examine tree water uptake at the plot scale during contrasting dry and wet periods.Field-based ecohydrological and isotopic analyses revealed that Scots pine water use is strongly constrained by soil water potential during drought, with trees relying on internal stem water storage and showing limited coupling to recent precipitation inputs. Stable isotope evidence demonstrated a dominant contribution of winter-recharged soil water stored in tightly bound soil pores, even following intense summer rainfall events. Only after sustained soil rewetting did trees begin incorporating summer precipitation, ultimately sourcing water from a mixture of winter and summer inputs. These findings indicate a clear preference for stable water pools with longer residence times and highlight the critical role of winter precipitation in sustaining tree hydraulic functioning in Mediterranean mountain forests.Building on these plot-scale observations, the second part of the thesis develops a physically grounded, calibration-free root water uptake parameterization based on soil moisture drying rates and constrained by sap-flow-derived transpiration. When implemented in a numerical model, this approach consistently outperformed commonly used empirical root distribution functions in reproducing soil water content and soil water potential dynamics. Independent validation using stable water isotopes confirmed the robustness of the proposed modeling framework and revealed tree water-use patterns under dry and wet conditions that were consistent with the field-based ecohydrological and isotopic findings.Agreement between field-based and modeling-based findings demonstrates that integrating ecohydrological observations, stable isotopic tracers, and physically grounded modeling provides a coherent and robust framework for advancing understanding of tree water uptake. The research in this thesis contributes to improving the realism of root water uptake representations in ecohydrological models and emphasizes the importance of stored winter precipitation for forest resilience in water-limited environments.

DOCTORAL DEGREE IN MARINE SCIENCES

CARRILLO LOSADA, MARÍA PAULA: Effects of pollution on invertebrate-associated microbiomes across freshwater and marine systems
Author: CARRILLO LOSADA, MARÍA PAULA
Programme: DOCTORAL DEGREE IN MARINE SCIENCES
Department: Department of Civil and Environmental Engineering (DECA)
Mode: Article-based thesis
Deposit date: 20/05/2026
Reading date: 19/06/2026
Reading time: 10:00
Reading place: Place: ETSECCPBUPC, Campus NordBuilding C2. Classroom: 212C/Jordi Girona, 1-308034 Barcelona
Thesis director: BARATA MARTI, CARLOS | VILA COSTA, MARIA
Thesis abstract: Human activities have driven major environmental alterations, including the release of synthetic chemicals that exceed our capacity to assess their ecological impacts. Aquatic ecosystems, acting as major sinks for contaminants, are exposed to complex pollutant mixtures differing in persistence, bioaccumulation and toxicity. However, conventional ecotoxicological approaches, largely based on chemical analyses and simplified exposures, often fail to capture the biological consequences of chronic, low-dose and mixture exposures. Moreover, early integrative indicators of exposure remain poorly developed, while omics-based research is strongly biased towards vertebrates, limiting understanding in ecologically dominant groups such as invertebrates.This thesis evaluates invertebrate-associated microbiomes as potential bioindicators of pollutant exposure across freshwater and marine environments. Laboratory experiments and field studies were integrated to assess microbiome responses, compare experimental and environmental patterns, and explore links between microbial shifts and host health. Model organisms, including Daphnia magna and the marine copepod Paracartia grani, were studied alongside natural populations such as Antarctic amphipods and Hydropsyche exocellata. Field campaigns included Mediterranean rivers impacted by wastewater discharges, a trans-Atlantic pollution gradient and Antarctic coastal systems. Microbiome responses were characterized using 16S rRNA gene sequencing, complemented by chemical analyses and host health endpoints.Across all studies, pollutant exposure consistently altered host-associated microbiomes, regardless of habitat, host species or pollutant class. These shifts were reproducible and often involved enrichment or depletion of specific taxa, supporting the hypothesis that microbiomes capture early biological responses to chemical stress. Host-associated microbiomes were generally more sensitive than environmental bacterial communities, particularly for bioaccumulative and hydrophobic contaminants, which induced more persistent perturbations than more polar compounds.Although no universal microbial indicator was identified, consistent context-dependent patterns emerged. In marine systems, taxa such as Pseudoalteromonas, Alteromonas and Rhodobacteraceae were repeatedly associated with organic pollutant exposure, while freshwater studies highlighted taxa linked to antibiotic resistance and wastewater influence, including Microbacterium and Microtrichaceae. Recurrent enrichment of broader groups such as Proteobacteria further suggests that functional traits, including xenobiotic degradation capacity, may underpin consistent responses.Links between microbiome perturbations and host health were also identified. In D. magna, microbioplastics exposure reduced Limnohabitans and increased Pseudomonas, coinciding with impaired reproduction, altered behaviour and transcriptomic changes. In copepods, shifts in core microbiome composition were associated with reduced reproductive output. While these results support links between microbiome disruption and host fitness, causality remains unresolved.Overall, this thesis demonstrates that invertebrate-associated microbiomes provide a sensitive and ecologically relevant approach to assess pollution exposure in aquatic ecosystems. Despite challenges regarding standardization and causal inference, the proposed framework aligns with new approach methodologies (NAMs) and offers strong potential for future integrative biomonitoring under increasing global chemical pressure.
CARRION BERTRAN, NIL: Influence of topobathymetric and offshore forcing uncertainties on beach morphodynamic predictability
Author: CARRION BERTRAN, NIL
Programme: DOCTORAL DEGREE IN MARINE SCIENCES
Department: Department of Civil and Environmental Engineering (DECA)
Mode: Normal
Deposit date: 11/05/2026
Reading date: 19/06/2026
Reading time: 10:30
Reading place: FIB. Campus Nord. Sala d'Actes Manuel Martí Recober B6 Planta 0
Thesis director: CALVETE MANRIQUE, DANIEL | RIBAS PRATS, FRANCESCA
Thesis abstract: Sandy beaches are among the most important, yet most vulnerable, environments on Earth. These regions are home to over 30% of the world's population and host a vast array of socioeconomic activities. As the interface between sea and land, they are highly dynamic systems where numerous processes occur at different temporal and spatial scales, continuously reshaping the morphology of the coast. Furthermore, climate change could modify these processes, producing not only long-term effects but also, in the short and medium term, impacts that significantly affect beach morphology.In order to investigate these effects, morphodynamic numerical models are key tools, allowing the analysis of past and present conditions, as well as to explore future scenarios. However, their application involves several sources of uncertainty. This thesis focuses primarily on uncertainties related to offshore forcing and initial topobathymetric conditions across multiple temporal and spatial scales.In the short term, the process-based XBeach model was employed to develop a conceptual model of how the initial topobathymetry influences the generation of washover deposits on a synthetic beach inspired by Castelldefels data (Spain) during a storm event. The study highlighted the importance of using detailed initial topobathymetries that incorporate potential morphological patterns to accurately analyse washover deposit generation. In particular, the inclusion of morphological patterns with varying wavelengths was shown to significantly affect hydrodynamic behaviour and sediment transport patterns, thereby influencing the distribution, extent, and volume of washover deposits. For instance, the presence of megacusps of certain wavelengths could enhance washover deposition by up to a factor four compared to scenarios in which such patterns were not included. This study proved the significant potential modelling uncertainties linked to unknowns not only in the initial topobathymetry but also in the incident wave group chronology, which can be included in this model, and may have a stronger influence on washover deposit formation than variations in the initial cross-shore profile. In the medium term, both the process-based XBeach model and the reduced-complexity Q2Dmorfo model were used to investigate how different hydrodynamic forcing sources, including waves and sea level, affect the modelling of the embayed Castell Beach (Palamós, Spain) over a six-month period. The study demonstrated that inaccurate representations of wave conditions can significantly affect the modelling of an embayed beach in the medium term, whilst different sea level sources produced similar results. In particular, biases in wave direction from hindcast data resulted in poor representations of shoreline evolution, although the model could recover if hindcast data was only employed for only a couple of months. These results highlight the uncertainties related with the selection of forcing sources to simulate the evolution of an embayed beach.In the long term, the Q2Dmorfo model was employed to investigate the influence of wave storm chronology on the projected evolution of the Llobregat Delta up to 2100. The study highlighted the strong dependence of the model response on the initial adaptation period, which appeared to be influenced by the wave chronology. However, once the model reached a quasi-equilibrium state during this adaptation phase, the subsequent low dynamism, resulting from the model calibration, was primarily controlled by the resulting topobathymetry rather than by the wave chronology. Consequently, the multiple realisations performed converged towards a similar morphological response up to 2100, limiting the ability to assess the role of storm chronology in long-term shoreline evolution. To address this limitation, several methodological improvements are proposed, with the objective of capturing the potential role of wave chronology in further work.

DOCTORAL DEGREE IN OPTICAL ENGINEERING

RAMÍREZ CANO, NATALIA: Medida morfológica de la tortuosidad de los vasos retinianos mediante análisis digital de imagen
Author: RAMÍREZ CANO, NATALIA
Programme: DOCTORAL DEGREE IN OPTICAL ENGINEERING
Department: Department of Optics and Optometry (OO)
Mode: Article-based thesis
Deposit date: 07/05/2026
Reading date: 12/06/2026
Reading time: 11:00
Reading place: Auditorio del Centro Universitario de la Visión. Paseo 22 de Julio, 660. 08222 Terrassay tambien por MEET: meet.google.com/sti-qkko-ihk
Thesis director: MILLAN GARCIA VARELA, MARIA SAGRARIO
Thesis abstract: Retinal vascular tortuosity has been widely identified by the medical community as a direct and non-invasive biomarker for the development of ocular, vascular, and systemic diseases. This is because the retinal vascular network is a delicate structure highly sensitive to alterations in blood pressure and other hemodynamic factors. These alterations produce observable changes in its vessels, modifying morphological parameters such as thickness, curvature, deviation, and tortuosity level. This makes the retinal vascular network a prime target organ for the early detection of ocular and vascular pathologies.Quantitative analysis of tortuosity in the retinal vascular network is typically performed by processing digital retinographies using algorithms that allow for the assessment of tortuosity indices. Local (characterizing the tortuosity of vessel segments free of bifurcations) and global (synthesizing the tortuosity information of the entire vascular network) indices are used. However, the calculation of these indices is conditioned by technical factors such as the spatial resolution of the images, the framing used in the acquisition of the retinographies (centered on the macula or the optic disc), as well as the choice of combinations of weighting schemes and local indices for calculating the global tortuosity indices.This doctoral thesis, presented as a compilation of three scientific publications, comprehensively addresses these challenges. First, it studies the impact of the retinographies’ framing (macula or optic disc) on the estimation of local tortuosity. Second, it evaluates the influence of image resolution on the robustness of the calculation of the local indices. Finally, an objective and quantitative validation framework for global indices based on the mathematical composition of local tortuosity index measures is proposed.The results obtained allow for the establishment of usage criteria for the selection of reliable local indices, demonstrate the limitations arising from acquisition conditions, and propose a methodological bridge between local and global measures. Thus, the thesis contributes to the standardization of tortuosity analysis in retinal images, with the aim of improving its clinical applicability and its value as a biomarker for systemic diseases.

DOCTORAL DEGREE IN PHOTONICS

MORENO ABAJO, ÁLVARO: Optical investigation of 2D materials with in-plane engineering: exciton confinement and chirality sensing
Author: MORENO ABAJO, ÁLVARO
Programme: DOCTORAL DEGREE IN PHOTONICS
Department: Institute of Photonic Sciences (ICFO)
Mode: Normal
Deposit date: 11/05/2026
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: KOPPENS, FRANK | RESERBAT-PLANTEY, ANTOINE
Thesis abstract: Two-dimensional (2D) materials provide a powerful platform for nanoscale engineering and control of geometry and energy landscapes without directly modifying the material, owing to their interfacial nature. This thesis explores how we can harness this potential by introducing in-plane engineering in van der Waals heterostructures. We present two case studies: in one, the exciton dimensionality is reduced using a designed 1D electrostatic trap; in the other, twisting two monolayers yields a chiral configuration that modifies the interaction with other chiral systems. Together, these two parts demonstrate how inplane symmetry breaking (translational and mirror symmetry, respectively) in 2D material platforms enables new modalities of control and sensing.In the first part, we investigate electrostatically defined confinement of intralayer excitons in MoSe2. A p–i–n junction is induced in the monolayer by asymmetric gating, creating a tight 1D potential with an effective exciton confinement length down to 10nm. Combining photoluminescence and reflectance-contrast spectroscopy, we resolve a discrete spectrum of localized states arising from center-of-mass quantization, with linear polarization aligned with the trap geometry, consistent with confinement-enhanced valley-exchange interactions. Importantly for the development of this technique, we show that the confinement potential cannot be understood as a purely electrostatic effect. Illumination reshapes device operation by inducing dissociation-driven photo-doping and Auger-assisted charge extraction, thereby stabilizing a working p–i–n configuration. We resolve photoinduced carrier-redistribution dynamics on the scale of seconds and demonstrate that their dependence on excitation position produces sharp switching between confined and unconfined excitonic responses. A rate-equation description captures the competition between dissociation and Auger processes, highlighting a route to nonlocal optical control of carrier density and, consequently, of the confinement potential. Programmable excitonic potentials that reach the 0D limit could enable quantum technologies such as single-photon sources or optically addressable qubits, and open a route toward strong exciton–exciton interactions and Bose–Hubbard physics.In the second part, we leverage the structural chirality of twisted bilayer graphene (TBG) to realize a novel enantiomeric sensing strategy based on chirality-dependent non-radiative energy transfer. In the presence of TBG, the decay rate of chiral fluorophores is modified depending on handedness matching between molecule and substrate, which we read out by measuring the fluorescence lifetime in time-resolved photoluminescence experiments. The observed asymmetry is statistically tested by spatially resolving the enantioselective contrast, observing a sign reversal upon inversion of the TBG handedness, and exploring the role of the twist angle as a control parameter. We quantify the effect of chirality through a lifetime-based dissymmetry factor that reaches the 1 – 10% level, implying an enhancement of several orders of magnitude compared with the natural optical circular dichroism of both the molecule and TBG. The presented approach is conceptually distinct from schemes that rely on electromagnetic field engineering, and achieves sensitivities down to the single-molecule layer without requiring surface functionalization. This opens the door to developing a platform with tunable, strong chiral light–matter interactions with implications in optics, sensing, and chemistry, including chiral catalysis and homochiral synthesis.
NIMJE, KARTIKA NARAYAN: Photonic Strategies for Approaching Fundamental Limits in Thermophotovoltaic Energy Conversion
Author: NIMJE, KARTIKA NARAYAN
Programme: DOCTORAL DEGREE IN PHOTONICS
Department: Institute of Photonic Sciences (ICFO)
Mode: Normal
Deposit date: 06/05/2026
Reading date: 18/06/2026
Reading time: 16:00
Reading place: ICFO Auditorium and Microsoft Teams Meetinghttps://teams.microsoft.com/meet/396755562864232?p=sfg2ZBdHKIuPmehIJj
Thesis director: PAPADAKI, GEORGIA THENO
Thesis abstract: Thermophotovoltaic (TPV) systems convert thermal radiation into electricity by coupling a hot emitter to a photovoltaic (PV) cell. Despite important recent developments in the field, TPV performance is ultimately constrained by a persistent power--efficiency trade-off: broadband radiative exchange between an emitter and a cell yields high electrical power at the expense of efficiency, whereas narrowband exchange leads to high efficiency at the cost of reduced power. A more empirical way to express this constraint is the difficulty of improving both the current and voltage characteristics of a cell simultaneously. Understanding the power--efficiency trade-off is therefore fundamental to optimizing TPV performance. This thesis develops a unified framework for understanding this trade-off and identifying photonic and electronic design strategies that enable optimal operation while remaining anchored to thermodynamic bounds.The first part of the thesis establishes the conceptual and quantitative backbone. A photonic view of thermal radiation connects Planck’s law and the Stefan--Boltzmann limit to the density of optical states, coherence, and surface polaritons, and clarifies the distinction between far-field and near-field exchange. These ideas are combined with the practical building blocks of TPVs — spectral and angular emission control, junction physics, recombination, and quantum efficiency — to establish a practical design toolkit for TPVs. Within this toolkit, detailed-balance and radiative--thermodynamic analyses place TPVs on a power--efficiency landscape bounded by Carnot and exergy (Landsberg) limits and identify spectral bandwidth as a central control knob governing performance.On this foundation, the thesis explores three routes for mitigating the trade-off. First, hot-carrier TPVs introduce an internal thermodynamic degree of freedom by treating the carrier subsystem as a reservoir with its own temperature and chemical potential and by harvesting carriers through energy-selective contacts; in the ideal radiative limit, this enables a single junction to emulate multicolor performance and approach Carnot efficiency at finite power. Second, an analytical framework for a near-field TPV system based on fluctuational electrodynamics derives analytical expressions for photon tunnelling between plasmonic and semiconducting media, establishing scaling laws that show how evanescent modes can deliver super-Planckian, spectrally concentrated fluxes that support high power and high efficiency simultaneously. Third, substrate engineering is shown to be instrumental in near-field TPV design: in an ITO/InAs case study, optimizing thin, low-loss plasmonic films with tuned plasma frequency and thickness reshapes the tunnelling spectrum, concentrating useful above-bandgap transfer while suppressing sub-bandgap losses, and shifts electrical power–efficiency curves outward in the radiative limit.This thesis reframes the TPV power--efficiency compromise as malleable rather than fixed: while the global thermodynamic frontiers are immutable, the effective frontier accessible to practical architectures can be steered through controlled interventions in spectra, modes, and carrier energetics. The analytical models, thermodynamic benchmarks, and optimization strategies developed here provide a principled basis for designing and evaluating TPV systems that combine photonic control, hot-carrier extraction, and near-field coupling, and for assessing these theoretical results in relation to realistic material and device constraints.
STAMMER, PHILIPP MAXIMILIAN: Photons and Information -- A modern approach to strong-field quantum optics
Author: STAMMER, PHILIPP MAXIMILIAN
Programme: DOCTORAL DEGREE IN PHOTONICS
Department: Institute of Photonic Sciences (ICFO)
Mode: Normal
Deposit date: 06/05/2026
Reading date: 09/06/2026
Reading time: 10:00
Reading place: ICFO Auditorium
Thesis director: LEWENSTEIN, MACIEJ
Thesis abstract: Photons and Information are notions indispensable for modern quantum technologies, and their interplay provides the foundation of understanding the quantum nature of light. In particular, photons are robust information carrier and substantiate the inherent discreteness of the electromagnetic radiation field. The information of photons, and their intrinsic quantum fluctuations, are manifested in the measurement of correlation functions of the field. Central to the understanding of photon fluctuations is the quantum theory of optical coherence, and the photon signature can reveal itself in different properties. Furthermore, the measurement of correlations is needed from an information theoretic perspective to distinguish classical from quantum signatures. These concepts ultimately lead to the original goal of the present Thesis:How can we understand the notion of photons and information in a modern strong field quantum optics perspective?Strong field quantum optics aims for the generation, characterization and the control of quantum light, beyond the conventional wisdom of strong field physics. In the traditional approach to strong field phenomena, in particular the photon up-conversion process of high-order harmonic generation, the field was merely treated classically. And hence, the notion of the photon could not exist in such descriptions. However, recent advances in the field of strong field quantum optics have revealed new signatures unaccountable by classical theory. This includes the generation of genuine non-classical states of light from strong field phenomena, revealing the intrinsic entanglement between all field modes in the process of high-order harmonic generation, or finding quantum signatures in the photon emission process itself via photon anti-bunching. In this Thesis, we reveal all such properties of the generated light field, and establish the underlying theories for the description of these phenomena. This includes the development of the quantum theory of optical coherence for high-order harmonic generation, as well as introducing new quantum information theoretic perspectives to strong field quantum optics. Therefore, the work presented in this Thesis provides the foundation for the modern formulation of quantum optical phenomena in strong field physics.

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

AREIAS FANZERES, LEONARDO: Sound-to-Image Translation Through Direct Cross-Modal Learning: An Exploratory and Architectural Study
Author: AREIAS FANZERES, LEONARDO
Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
Department: Department of Signal Theory and Communications (TSC)
Mode: Normal
Deposit date: 16/04/2026
Reading date: 18/06/2026
Reading time: 11:00
Reading place: Aula de Teleensenyament, edifici B3, Campus Nord, Barcelona
Thesis director:
Thesis abstract: Environmental sound conveys rich semantic and contextual information about events, objects, and spatial dynamics. However, prevailing computational approaches to environmental audio analysis, such as Acoustic Event Detection (AED), typically reduce this complexity to discrete textual labels. While effective for automated monitoring tasks, such representations oversimplify acoustic scenes and become inadequate when auditory information must be communicated across modalities. Sound-to-image (S2I) translation offers an alternative approach in which a model synthesizes images that visually depict sound-emitting sources and their surrounding environments.This thesis introduces and advances direct sound-to-image translation, a paradigm that establishes a connection between audio and visual modalities without relying on textual mediation, class supervision, or cluster-based alignment during training. The central hypothesis is that higher-level abstractions learned by deep neural networks provide a shared semantic space in which heterogeneous modalities can connect directly, enabling the generation of images that are interpretable and semantically coherent with the source sound. Such outputs are referred to as informative, meaning that they visually communicate meaningful aspects of the acoustic event.The first part of the thesis presents, to the best of our knowledge, the first study dedicated to direct S2I translation. A densely connected generative adversarial network (GAN), conditioned on audio embeddings, is developed to synthesize images directly from sound. Because multiple plausible images may correspond to a single acoustic event, translation quality cannot be evaluated through pixel-level reconstruction. To address this challenge, an informativity-based evaluation framework is proposed, employing classifiers to determine whether generated images are interpretable and semantically coherent with the source audio. Experiments reveal that, despite the inherent difficulty of the task, the model generalizes to unseen sounds and produces informative outputs for a meaningful portion of translations. Analysis further reveals that latent bottleneck dimensionality influences translation behavior, exposing a trade-off between pixel-space convergence and informativity.Building on this foundation, the second part investigates whether attention mechanisms can strengthen cross-modal alignment. Self-attention and cross-attention modules are integrated into the generator and evaluated across multiple configurations. Results show that attention improves translation performance when applied at early stages of the network, increasing informativity relative to the purely convolutional baseline while preserving the fully direct audio–visual connection.Together, these contributions formally define, validate, and extend direct S2I translation as a distinct research paradigm. Beyond architectural design and training strategies, this thesis advances methodological principles for quantitative evaluation of cross-modal translation in the absence of deterministic visual ground truth. The findings contribute to a broader understanding of multimodal representation learning and highlight the potential of direct S2I translation for applications in multimodal interaction and accessibility-oriented technologies, particularly for enhancing situational awareness in deaf and hard-of-hearing individuals.
MARTÍ ESPELT, ANIOL: Physically consistent wireless communications with statistical channel state information
Author: MARTÍ ESPELT, ANIOL
Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
Department: Department of Signal Theory and Communications (TSC)
Mode: Normal
Deposit date: 20/05/2026
Reading date: 17/06/2026
Reading time: 11:00
Reading place: Aula de Teleensenyament, Edifici B3, Campus Nord, Barcelona
Thesis director: RIBA SAGARRA, JAUME | LAMARCA OROZCO, M. MERITXELL
Thesis abstract: The deployment of 5G and 6G wireless networks enforces a paradigm shift in communication system design, driven by the move towards sub-THz frequencies and extremely large antenna arrays. These advancements leave traditional channel modeling—which often relies on far-field assumptions and neglects electromagnetic interactions between antenna elements—physically inconsistent. Furthermore, the overhead associated with acquiring instantaneous channel state information (CSI) in massive multiple-input multiple-output (mMIMO) systems presents a critical bottleneck, particularly for low-latency or high-mobility communications.This thesis addresses the aforementioned challenges by developing a framework for the design and analysis of noncoherent wireless communication systems that operate solely with statistical, rather than instantaneous, CSI. The core of this work is the establishment of a physically consistent channel model that accurately incorporates the effects of near-field spherical wavefronts and mutual coupling. We demonstrate that these complex physical phenomena can be effectively captured within a correlated Rayleigh fading model, providing a tractable yet realistic foundation for system analysis.Using this framework, we investigate the performance of one-shot, energy-based communication schemes, which are particularly well suited for low-latency applications. A key result is the existence of a fundamental error floor at high signal-to-noise ratio (SNR) for constellations with more than two energy levels when no CSI is available at the transmitter. However, we also prove that this error vanishes as the number of receiver antennas grows, highlighting the channel hardening benefits of massive arrays.A widely adopted receiver in energy-based noncoherent systems is the so-called energy detector. Although it is optimal under uncorrelated fading, its performance degrades significantly in correlated channels. To address this limitation, we introduce a novel class of quadratic detectors, including the best quadratic unbiased estimator (BQUE) as well as a practical implementation called assisted BQUE. These detectors leverage statistical CSI to achieve near-optimal performance. Furthermore, two strategies for enhancing reliability are proposed and evaluated: a constellation design methodology that minimizes the analytical symbol error rate by leveraging statistical CSI at the transmitter, and a permutational index modulation (PIM) scheme that introduces coding gain with minimal complexity.Finally, the thesis explores the impact of model mismatch, revealing that noncoherent systems exhibit greater robustness to mutual coupling than their coherent counterparts. We also demonstrate that wavefront curvature can be exploited well beyond the classical Fraunhofer distance. Moreover, we show that large antenna arrays enable the multiplexing and low-complexity detection of multiple users, even when employing noncoherent processing.
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: pending
Reading time: pending
Reading place: pending
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.
WU, RUOCHEN: Millimeter-Wave Radar-on-Chip Based Techniques for Robust Contactless Vital Sensing and Smart Healthcare
Author: WU, RUOCHEN
Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
Department: Department of Signal Theory and Communications (TSC)
Mode: Normal
Deposit date: 18/05/2026
Reading date: 18/06/2026
Reading time: 11:30
Reading place: Aula MERIT, Dept. TSC, Edif. D5-010, Campus Nord UPC, 08034 Barcelona
Thesis director: MALLORQUI FRANQUET, JORDI JOAN | BROQUETAS IBARS, ANTONI
Thesis abstract: This thesis addresses the challenges of contactless vital sensing using Millimeter-Wave (mmWave) Radar System-on-Chip (RSoC) technology for the Internet of Medical Things (IoMT). While radar sensing enables the extraction of vital signs like Respiratory Rate (RR) and Heart Rate (HR) through chest vibrations , these micro-motions are inherently weak and highly susceptible to interference. Therefore, maximizing the Signal-to-Interference-plus-Noise Ratio (SINR) through robust signal processing is crucial.To enhance detection accuracy and robustness, this thesis proposes a series of novel solutions. First, it introduces an independently developed mmWave RSoC integrated with a novel Repetitive Waveform Adaptive Matched Filter (RWAMF), successfully extracting RR, HR, and Blood Pressure Waveforms (BPW) from noisy radar echo data. Second, the thesis presents mmVital, an enhanced steering system featuring a Beam Steering Unit (BSU) based on a servo-controlled flat mirror. This system autonomously optimizes 2D beam pointing and generates a multi-biometric chest map point-by-point. Third, the research expands biometric extraction to include radar-based eyelid dynamic signals, focusing on motion patterns detection and face interference compensation. Finally, in collaboration with the Hospital Universitari Germans Trias i Pujol (HUGTiP), a high-quality, synchronized human vital signal dataset based on high-frequency RSoC was constructed and publicly released to facilitate future algorithm development.Ultimately, thiese works significantly advance the reliability of radar technologies for smart healthcare monitoring and lays a solid theoretical and practical groundwork for future IoMT applications.

DOCTORAL DEGREE IN STRUCTURAL ANALYSIS

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: pending
Reading time: pending
Reading place: pending
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.
RUBIO SERRANO, RAUL: DEVELOPMENT AND APPLICATION OF AN EIFEM-BASED SURROGATE MODEL FOR STRUCTURAL MODELLING, PRECONDITIONING AND OPTIMIZATION
Author: RUBIO SERRANO, RAUL
Programme: DOCTORAL DEGREE IN STRUCTURAL ANALYSIS
Department: Department of Civil and Environmental Engineering (DECA)
Mode: Normal
Deposit date: 14/05/2026
Reading date: 18/06/2026
Reading time: 12:00
Reading place: UPC Campus Nord, ETSECCPB, C/ Jordi Girona 1-3, edificio C1, Sala 002, Barcelona
Thesis director: HERNANDEZ ORTEGA, JOAQUIN ALBERTO | FERRER FERRE, ALEX
Thesis abstract: The continuous demand for performance in modern engineering has led to the design of highly complex structures. Analyzing these designs via the Finite Element Method (FEM) requires solving high-dimensional systems with a prohibitive computational cost when multiple solves are needed, such as in structural optimization or non-linear problems. To mitigate this, Reduced Order Models (ROMs) seek approximations in a lower-dimensional space. Traditional global ROMs obtain fast and accurate approximations but lack topological flexibility to handle continuous geometric variations, which impairs an efficient decoupling between offline training and online execution.To overcome these limitations, this thesis builds upon the Empirical Interscale Finite Element Method (EIFEM), originally introduced for the multiscale analysis of heterogeneous structures. Formulated within the standard FEM paradigm, EIFEM replaces classical shape functions with precomputed operators learned in an offline stage, aligning with data-driven principles. Unlike traditional approaches based on nested hierarchies, EIFEM directly relates fine-scale and coarse-scale behaviors through these operators. Building on this foundation, this work investigates its application to structural beam modeling, solver acceleration, and optimization.First, the thesis addresses the modeling of complex composite structures using EIFEM, where coarse-scale degrees of freedom coincide with those of a standard beam formulation. This beam Reduced Order Model (bROM) bridges full-field 3D elasticity and reduced 1D models. Kinematic assumptions are no longer prescribed a priori, but learned from offline 3D simulations. The dimensionality reduction inherent to EIFEM yields a data-driven beam element capable of capturing complex behaviors, such as orthotropy, while maintaining full compatibility with standard FEM implementations.Second, the focus shifts to the acceleration of exact numerical solvers. EIFEM is used as a coarse space preconditioner within Conjugate Gradient (CG) iterative solvers. By exploiting localized static condensation in a reduced space, this strategy drastically decreases the condition number of large-scale systems. This enables fast, full-fidelity solutions on standard desktop architectures without relying on High-Performance Computing (HPC) environments.Finally, the thesis tackles the computational cost of structural design by extending the EIFEM framework to parametric settings. The main challenge lies in efficiently evaluating interscale operators for varying geometric configurations of the unit cell during optimization. Since directly interpolating all entries of these high-dimensional mappings would be prohibitive, the Discrete Empirical Interpolation Method (DEIM) is used to identify a reduced set of representative entries. These are interpolated with respect to geometric parameters to reconstruct the full operators. This strategy enables fast, localized evaluations without requiring global matrix reassembly, accelerating the optimization process while preserving the modularity of the framework.In conclusion, this thesis exploits the offline/online paradigm of localized reduced-order modeling using EIFEM, which provides precomputable operators that encode fine-scale behavior. This approach derives data-driven beam models from 3D elasticity, accelerates exact solvers via data-informed coarse spaces, and enables efficient optimization through parametric operator interpolation, thus aligning standard FEM practice with the machine learning paradigm.
SHANG, CHENGSHUN: A Numerical Framework Based on the Discrete Element Method for Modeling Weakly and Strongly Cemented Sands
Author: SHANG, CHENGSHUN
Programme: DOCTORAL DEGREE IN STRUCTURAL ANALYSIS
Department: Department of Civil and Environmental Engineering (DECA)
Mode: Normal
Deposit date: 14/05/2026
Reading date: 12/06/2026
Reading time: 11:00
Reading place: Sala Zienkiewich (CIMNE) Building C1, UPC - Campus North Gran Capitan S/N 08034 Barcelona
Thesis director: BARBU, LUCIA GRATIELA | CELIGUETA JORDANA, MIGUEL ANGEL
Thesis abstract: Cemented sands are widely encountered in natural and engineered systems, ranging from biocemented soils to sandstones, where inter-particle bonding plays a critical role in mechanical behavior. Accurately modeling the influence of cementation on deformation and failure remains challenging due to the complex coupling between granular fabric and cementation characteristics at the particle scale. This thesis establishes a comprehensive numerical framework based on the Discrete Element Method (DEM) for modeling weakly and strongly cemented sands, integrating numerical developments, micromechanical modeling, and experimental validation.Following a modeling philosophy of progressing from simple to complex, cemented sand is represented as a combination of a clean sand skeleton and superimposed cementation. This approach enables a clear separation between granular and bonding contributions, improves physical interpretability, and reduces excessive numerical calibration. The research comprises theoretical developments in DEM methodology and application studies covering non-cemented, weakly cemented, and strongly cemented granular materials, systematically validated against experimental data.At the theoretical level, a standardized framework for particle packing generation is proposed, explicitly formalizing tacit knowledge embedded in empirical procedures. An Improved Radius Expansion with Servo control and Random shifting (IRESR) algorithm is introduced to ensure robust stress control and mitigate boundary effects, and the open-source tool DEMGen is developed to generate and characterize representative particle packings. Two bonded-particle models are established: an improved Parallel Bond Model (PBM) and a Parallel Bond Bilinear Damage Model (PBBDM), the latter incorporating fracture-energy-based progressive damage and post-peak softening. In addition, a machine learning (ML)-accelerated parameter calibration strategy is developed to improve calibration efficiency while maintaining accuracy.The framework is applied to non-cemented sand, weakly cemented sand, and strongly cemented sand. Biocemented sands are modeled using micro-CT-derived calcite characteristics, while Fontainebleau sandstone is simulated using a physics-based particle overgrowth approach. The results reveal a transition from contact-dominated to bond-dominated behavior with increasing cementation, demonstrating the robustness and generality of the proposed framework.
TORRES LERMA, JOSE ANTONIO: Additive manufacturing constraints in topology optimization using a perimeter functional and a null space algorithm
Author: TORRES LERMA, JOSE ANTONIO
Programme: DOCTORAL DEGREE IN STRUCTURAL ANALYSIS
Department: Department of Civil and Environmental Engineering (DECA)
Mode: Normal
Deposit date: 19/05/2026
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: FERRER FERRE, ALEX | OTERO GRUER, FERMÍN ENRIQUE
Thesis abstract: In the context of lightweight structural design, this thesis addresses the incorporation of additive manufacturing constraints into topology optimization in a simple, general, and computationally efficient manner. In particular, the focus is placed on two key limitations arising in additive manufacturing processes: the minimum length scale and overhang constraints. Existing approaches often rely on complex modifications of the governing physics or on additional mechanical constraints, leading to increased computational cost and implementation complexity.To overcome these limitations, this work proposes a unified framework based on regularized perimeter constraints, which can be consistently applied to both density-based and level-set formulations. To the best of the author’s knowledge, this represents the first extension of perimeter-based methods to the local enforcement of additive manufacturing constraints. Nonlinear smoothing extensions are introduced to solve the overhang constraints, while we include the definition of minimum thickness constraints through an isoperimetric analogy. A dual discretization strategy is also developed to enforce the constraints locally.In parallel, an extended null space optimization algorithm is proposed to efficiently handle the resulting multi-constraint problems while requiring minimal parameter tuning. The method is shown to be applicable to density-based approaches, shape optimization, and level-set methods with topological derivatives. Furthermore, two acceleration strategies are investigated - namely, a subiteration approach and a quasi-Newton method - demonstrating improved convergence behavior through the incorporation of nonlinearities in geometrical functionals.The results show that the proposed methodology provides an effective and computationally efficient framework for enforcing additive manufacturing constraints, while maintaining flexibility across different design representations. The combination of perimeter-based constraints and a robust optimization algorithm offers a promising alternative to existing approaches, particularly for large-scale and complex applications.

DOCTORAL DEGREE IN SUPPLY CHAIN AND OPERATIONS MANAGEMENT

MAQUIRRIAIN ANTOÑANZAS, JAVIER: Algoritmos matheurísticos para la programación de mantenimientos preventivos
Author: MAQUIRRIAIN ANTOÑANZAS, JAVIER
Programme: DOCTORAL DEGREE IN SUPPLY CHAIN AND OPERATIONS MANAGEMENT
Department: Department of Management (OE)
Mode: Normal
Deposit date: 05/05/2026
Reading date: 18/06/2026
Reading time: 10:30
Reading place: Seminari de l'IOC, planta 11, ETSEIB.
Thesis director: GARCÍA VILLORIA, ALBERTO | PASTOR MORENO, RAFAEL
Thesis abstract: This doctoral thesis addresses the problem of cyclic preventive maintenance scheduling in industrial systems, which is NP-hard due to its combinatorial complexity. The problem consists of defining a maintenance policy P that schedules the maintenance of M machines over a cyclic sequence of T time periods, where at most one machine can be serviced in each period. The objective is to determine a policy that minimizes the total costs incurred. To this end, mathematical models and matheuristic algorithms are developed and evaluated.A cost structure combining linear operating costs and stepwise maintenance costs is proposed, providing a more realistic representation of behaviour observed in industrial environments. Based on this structure, two variants of the problem are defined: • Cyclic preventive maintenance scheduling with a predetermined cycle length (SECIMAP_Tpred), in which the maintenance cycle length T is fixed in advance.• Cyclic preventive maintenance scheduling with a variable cycle length (SECIMAP_Tvar), in which T is treated as a decision variable to be determined within the problem.For the SECIMAP_Tpred variant, an exact mathematical model (MMat) is formulated, together with a relaxed version (MPR) that enables the computation of lower bounds, which are subsequently used to assess the quality of the designed (mat)heuristic algorithms. Since MMat is computationally inefficient for industrial-sized instances, three matheuristics (MH1P, MH2P, and MHFI) integrating mathematical programming and heuristic strategies are developed. A sequential procedure (MHSEC) that executes the three matheuristics and retains the best solution obtained is also proposed, achieving an average deviation of at most 3.19% from the optimal solution. In addition, a matheuristic cocktail (COMH) is developed which, by applying an early termination technique based on adaptive prioritization of subalgorithms and cancellation of non-promising solutions, obtains the same results as MHSEC while reducing execution times by 53.37%.The study is then extended to the SECIMAP_Tvar variant, in which the cycle length T is optimized. For this case, a new mathematical model for the relaxed problem (MTI) is developed, together with four hybrid algorithms combining metaheuristic procedures and matheuristic methods (MTI+MHFI, ALG1P, ALG2P, and ALGFI), a sequential algorithm (ALGSEC), and an algorithm cocktail (COALG) designed to minimize computational times. The best resolution procedures for the variable-T case (ALGSEC and COALG) achieve an average deviation of at most 1.43% from the optimal solution. Furthermore, COALG attains the same solutions as ALGSEC while reducing execution times by 33.2% through the use of early termination and intelligent pruning techniques that prevent the exploration of solution configurations unable to improve upon the best solution found so far.The comparative analysis of the results obtained for both problem variants (SECIMAP_Tpred and SECIMAP_Tvar) shows that treating T as a decision variable expands the solution space and, consequently, enables the derivation of maintenance policies that achieve a 2.68% reduction in costs.Finally, the thesis presents the general conclusions, the main methodological contributions (including the introduction of stepwise cost structures or the systematic use of lower bounds computed via mathematical programming to guide heuristic search) and directions for future research.

DOCTORAL DEGREE IN SUSTAINABILITY

RHOUMA, ALI: Operationalizing the Water–Energy–Food–Ecosystems Nexus for the Sustainability Assessment of Mediterranean Farming Systems
Author: RHOUMA, ALI
Programme: DOCTORAL DEGREE IN SUSTAINABILITY
Department: University Research Institute for Sustainability Science and Technology (IS.UPC)
Mode: Normal
Deposit date: 24/04/2026
Reading date: 16/07/2026
Reading time: 12:30
Reading place: Salón de Grados de la EEABB Campus of Castelldefels
Thesis director: GIL ROIG, JOSE MARIA | BROUWER, FLOOR
Thesis abstract: Agricultural systems face increasing pressures from water scarcity, climate change, and environmental degradation, particularly in the Mediterranean region where resource constraints are intensifying. Addressing these interconnected challenges requires integrated analytical approaches capable of capturing the complex interactions between water, energy, food production, and ecosystems. The Water–Energy–Food–Ecosystems Nexus has emerged as a promising framework for supporting sustainable resource management; however, its operationalization at the farm level remains limited. This thesis aims to advance the application of the WEFE Nexus for the sustainability assessment of farming systems by developing an integrated analytical framework and practical evaluation tools.The research adopts a progressive methodological approach. First, water-related sustainability indicators specifically the water footprint and water scarcity footprint are applied to assess the pressures of agricultural production on water resources. These indicators provide an initial understanding of resource use efficiency and highlight critical water-related challenges in farming systems. Building on this foundation, the thesis develops a WEFE Nexus assessment framework based on system dynamics modelling to capture interactions between water use, energy consumption, food production, and ecosystem impacts. The framework is implemented through a user-friendly decision-support tool designed to support sustainability assessments at the farm level.The developed framework is subsequently applied to evaluate WEFE Nexus solutions in agricultural systems, with a particular focus on agroecological practices. By integrating multiple indicators related to resource efficiency, environmental performance, and agricultural productivity, the analysis explores how agroecological approaches influence the performance of farming systems within the WEFE Nexus. The results demonstrate that agroecological practices can improve resource use efficiency, reduce environmental pressures, and enhance the resilience of farming systems.Finally, the outcomes of the WEFE Nexus assessment are translated into key performance indicators linked to the Sustainable Development Goals (SDGs). This step enables the quantification of how WEFE-based agricultural practices contribute to broader sustainability objectives and global development targets. By linking farm-level sustainability assessment with the SDG framework, this research provides a novel methodological contribution for evaluating the sustainability impacts of agricultural practices.This thesis contributes to bridging the gap between WEFE Nexus theory and practical agricultural sustainability assessment. The proposed framework offers a robust approach for evaluating sustainable farming systems and provides valuable insights for policymakers, researchers, and stakeholders seeking to promote resilient and resource-efficient agriculture in the Mediterranean region and beyond.
VILLANUEVA ESCOBEDO, BRENT: Design and Application of an AI-Enabled Adaptive Framework for Assessing Circularity in Socio-Ecological and Technical Systems (SETs) within the WEFE Nexus
Author: VILLANUEVA ESCOBEDO, BRENT
Programme: DOCTORAL DEGREE IN SUSTAINABILITY
Department: University Research Institute for Sustainability Science and Technology (IS.UPC)
Mode: Normal
Deposit date: 14/04/2026
Reading date: 17/07/2026
Reading time: 10:30
Reading place: UPC ESEIAAT edifici TR1Planta 0 Porta 085
Thesis director: MORATO FARRERAS, JORDI
Thesis abstract: Sustainability and circular economy transitions in contemporary socio-environmental systems are increasingly challenged by complexity, uncertainty, and strong interdependencies between natural resources, infrastructures, and governance structures. Traditional sectoral and indicator-based assessment approaches have proven insufficient to capture these interactions, often overlooking systemic trade-offs, emergent behaviors, and context-specific constraints. In response to these limitations, this doctoral thesis develops, applies, and validates integrated, participatory, and adaptive assessment frameworks for sustainability and circularity, grounded in systems thinking and the Water–Energy–Food–Ecosystems (WEFE) Nexus.The thesis is structured as a compendium as follows. The first chapter is the introduction, including the research context of the main concepts, the background and rationale, and the design, starting with the research questions, hypothesis, identification of the research gap, the research lines and objectives. The second chapter, dives into the state of the art of the main concepts, presenting the bibliometric analysis as well as the institutional context and the projects that provided the scene for the applied research. The third chapter is dedicated to the methodology, starting with the global methodology framework and then focusing on the WEFE Nexus and integrated assessment. The fourth chapter, proposes an integrated multi-criteria framework for assessing sustainability and circular economy performance in public water utilities operating in Mediterranean contexts, combining environmental footprints, ecosystem services, governance, and operational performance within a decision-oriented analytical structure. The fifth chapter applies an artificial intelligence (AI)–enabled WEFE Nexus assessment tool to evaluate circular bioeconomy (specifically biochar and agroforestry) highlighting trade-offs, synergies, and context-dependent outcomes under future scenarios in a dynamic way. The sixth chapter consolidates these insights into a transferable methodological framework for participatory, AI-enabled circularity assessment across heterogeneous socio-environmental systems. The seventh chapter is focused on the discussion of the theoretical and the applied research, specifically to proof whether circularity was implemented as a static set of material loops, or if enough evidence is found that circularity was implemented as an emergent system property, resulting from interactions between resource systems, ecosystems, institutions, and stakeholder values in the frame of this thesis. The eighth and final chapter gathers conclusions to measure the degree in which the methodology and its derived applications help integrate multi-criteria decision analysis, participatory processes, artificial intelligence, and digital twin concepts to support transparent, context appropriate and adaptive sustainability assessment. Finally, limitations and future research lines are drawn to set some basic principles for replication and adaptation of the analysis tool in different contexts. Overall, the thesis aims to contribute in advancing the state of the art in sustainability science by operationalizing the WEFE Nexus through AI-enabled and participatory assessment frameworks, bridging the gap between conceptual integration and practical support for decision-making. The obtained results, demonstrate that systemic, adaptive, and governance-aware approaches are essential for informing transitions towards sustainability and circular economy in complex socio-environmental systems with resource constraints

DOCTORAL DEGREE IN THERMAL ENGINEERING

BAHRAMIAN, LINDA: Numerical assessment of parcel modeling and inertial particle separator efficiency in polydisperse two-phase flows
Author: BAHRAMIAN, LINDA
Programme: DOCTORAL DEGREE IN THERMAL ENGINEERING
Department: Department of Heat Engines (MMT)
Mode: Normal
Deposit date: 11/05/2026
Reading date: pending
Reading time: pending
Reading place: pending
Thesis director: OLIET CASASAYAS, CARLES | PEREZ SEGARRA, CARLOS DAVID
Thesis abstract: This thesis addresses fundamental and applied aspects of disperse two-phase flow modeling within the Eulerian–Lagrangian approach, with particular emphasis on the development and assessment of parcel modeling and the conservation-consistent two-way coupling approach, progressing toward application of an Inertial Particle Separator (IPS).First, the conservation properties of the two-way coupling formulation are analyzed to ensure consistent momentum exchange between the carrier and dispersed phases. The numerical implementation preserves global conservation principles and physically consistent kinetic energy evolution.The numerical method is first assessed in Direct Numerical Simulation to provide a reference solution and is subsequently extended to Large Eddy Simulation (LES) to address more realistic, application-oriented flow conditions. Building upon this foundation, a novel hybrid parcel modeling strategy is developed by combiningthe Number Fixed Model and the Volume Fixed Model for a particle distribution. The proposed approach is then validated against benchmark cases and offers an effective compromise between computational cost and predictive accuracy.Subsequently, a comprehensive numerical investigation of an IPS device is performed using LES, Improved Delayed Detached Eddy Simulation, and Reynolds-Averaged Navier–Stokes (RANS) turbulence models. The influence of turbulence resolution, flow split ratio, and Reynolds number on separation efficiency is analyzed for different particle sizes. The results indicate that turbulence modeling affects drag-dominated particles, while segregation of larger particles is mainly driven by inertial effects. This study presents a comparative assessment of turbulence modeling strategies and their impact on IPS performance prediction.The numerical framework is then extended to icing conditions. Water droplet impingement and ice accretion are first validated using a canonical cylinder benchmark. The methodology is then applied to the IPS configuration, where ice growth alters the internal geometry. Following ice accretion, solid particles are injected into the modified geometry to evaluate the separation efficiency using Lagrangian tracking, highlighting a reduction in efficiency for inertia-dominated particles as a result of scavenge blockage and modified wall interactions.In this context, a key original contribution of this study is the development and implementation of a dedicated particle–ice wall collision model. To address the lack of suitable models for solid particles impact on ice-covered surfaces in IPS, a restitution-based formulation was developed through a structured review and adaptation of existing collision models.This approach ensures a physically consistent prediction of particle rebound behavior on ice-covered surfaces.Overall, this thesis advances the predictive capability of Computational Fluid Dynamics tools for disperse two-phase flows by enhancing the implementation of conservation-consistent two-way coupling, proposing a physics-guided hybrid parcel model, quantifying the sensitivity of turbulence modeling in IPS efficiency, and introducing a novel particle–wall collision model under adverse icing conditions. The results contribute to both the methodological development of Eulerian–Lagrangian modeling and the reliable simulation of aeronautical particle separation systems.

Last update: 06/06/2026 06:45:08.