DOCTORAL DEGREE IN APPLIED MATHEMATICS

• DE OLAZÁBAL, RAMIRO: Advancing Solver Performance in Large-Scale Computational Fluid Dynamics: Generalizing the Linelet Preconditioner for the Pressure Correction Equation
  
  Author: DE OLAZÁBAL, RAMIRO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN APPLIED MATHEMATICS
  Department: School of Mathematics and Statistics (FME)
  Mode: Normal
  Deposit date: 17/03/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: LEHMKUHL BARBA, ORIOL | VÁZQUEZ, MARIANO
  Thesis abstract: This thesis presents the Global Linelet Preconditioner (GLP), a preconditioning strategy designed to overcome these limitations and improve scalability in extreme-scale Computational Fluid Dynamics (CFD) applications. The method extends and generalizes the traditional linelet approach by introducing a communication step within the preconditioning operation, allowing interdomain coupling and preserving connectivity across partition boundaries. This modification significantly enhances convergence rates in highly anisotropic meshes by ensuring that the strongest couplings in the linear system are treated effectively, regardless of domain decomposition constraints. A key contribution of this work is the development of a purely algebraic linelet construction algorithm, which eliminates the need for geometric information when defining linelets. While conventional methods rely on explicit mesh structures to determine anisotropic directions, the algebraic approach constructs linelets based solely on matrix properties, allowing greater flexibility and applicability to general unstructured meshes. Furthermore, the geometric-based construction was also explored and integrated within the framework, demonstrating superior performance in structured meshes with well-defined anisotropic features. The comparison between the geometric and algebraic approaches revealed that while the former achieves better performance when clear directional stiffness is present, the latter provides a robust alternative when mesh topology is complex or unavailable. The effectiveness of GLP was assessed through extensive numerical experiments, including benchmark problems and real-world CFD applications such as the 30P30N high-lift airfoil, the Stanford diffuser, and the DrivAer model. Results demonstrated that GLP significantly improves solver convergence over existing preconditioners, including previous versions of the linelet preconditioner, particularly in cases where a high percentage of elements lie within the boundary layer. Performance analyses revealed that while GLP incurs a higher preprocessing cost due to linelet construction and communication, these overheads are outweighed by the substantial reduction in solver iterations, leading to overall computational savings in large-scale simulations. In addition to improving convergence, GLP introduces a partition-agnostic formulation, making it independent of the domain decomposition strategy. Unlike traditional preconditioners, which are sensitive to mesh partitioning, GLP maintains its numerical performance across varying decomposition configurations, enabling more flexible and balanced parallel execution. The parallel implementation of the method, tailored for High Performance Computing environments, ensures scalability across a wide range of core counts, as demonstrated by detailed scalability analyses.
  

DOCTORAL DEGREE IN ARCHITECTURAL DESIGN

• ORTIGOSA DUARTE, NURIA: Exposiciones de arquitectura en Barcelona 1939-2019. Una colección.
  
  Author: ORTIGOSA DUARTE, NURIA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL DESIGN
  Department: Department of Architectural Design (PA)
  Mode: Normal
  Deposit date: 13/03/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: CALLÍS FREIXAS, EDUARD | MONTEYS ROIG, FCO JAVIER
  Thesis abstract: The objective of this research is the study of the collection comprising the 950 architectural exhibitions held in Barcelona from the end of the Spanish Civil War to the present day. The study focuses on the «what» rather than the «how», that is, on their content beyond their display. The most common way architectural exhibitions have been studied is through their individuality or, in some cases, in small associations, but never through the entirety of their exhibition activity. However, in this dissertation, the exhibitions are understood as a whole, as an architectural collection that allows for establishing a series of relationships among them, revealing qualities that can only be uncovered through «the whole». Nor have they been considered from the plurality of the city that hosts them, despite their temporal concurrence and their dispersion across numerous locations in the city, whereas here they are taken as a body equivalent to the architecture of the city to which they belong and simultaneously help to shape.Somewhere between theory and practice, architectural exhibitions serve as a platform for the dissemination and debate of ideas; they are part of and contribute to the architectural discourse of the city in which they are held. This is achieved by conveying a specific argument that stimulates architectural thinking through its content. Such content is composed of a selection of «pieces» usually taken from architectural collections or archives, generally housed in specialized institutions, as well as some elements produced ad hoc. In other words, the collections and archives from which this content is drawn represent an invaluable reserve for the «construction» of new exhibitions. The group of exhibitions that forms the body of study for this thesis is itself a collection, comprising 950 archives. Based on the above, this collection can be seen as a tool for the formation of new arguments and, therefore, new architectural discourses.This research will dissect the exhibitions held in Barcelona from the perspective of the collection, extracting knowledge from both their morphology as exhibition act and the content of their discourse in relation to the city. This body of study will also allow for the revelation of characteristics of architectural exhibitions as an architectural practice in themselves, which, as a recent field of study, remain unexplored. Additionally, with the aim of highlighting the propositional role of architectural archives and collections and «learning to handle» the one addressed here, it will discuss reference case studies through which it will be demonstrated that the collection under study can be taken as an active and usable resource, stemming from the propositional idea intrinsic to all architectural projects. Through this research, it will be shown that this collection of exhibitions, in addition to having the capacity to reveal previously unknown issues that can only be evidenced through its collective condition, is not a passive repository of architectural elements but a latent gathering of ideas awaiting activation. It is a project tool capable of generating potential arguments that open new perspectives on the ongoing transformation of our built environment and its exhibitions.
  

DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE

• UGRINOVIC KEHDY, NICOLAS: Modeling and Reconstruction of 3D Humans under Context
  
  Author: UGRINOVIC KEHDY, NICOLAS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE
  Department: Department of Computer Science (CS)
  Mode: Normal
  Deposit date: 05/02/2025
  Reading date: 04/04/2025
  Reading time: 15:00
  Reading place: Sala de Juntes de la FME
  Thesis director: SANFELIU CORTES, ALBERTO | MORENO NOGUER, FRANCESC D'ASSIS
  Thesis abstract: The study of human's and their behavior through the analysis of images and videos has long been a central topic in Computer Vision. The reconstruction and modeling of human behavior have garnered increasing attention, due to their potential applications in virtual environments, including AR/VR, sports, fashion, and the film industry. Despite this growing interest, accurately capturing and generating the 3D pose and motion of humans remains an important challenge, primarily due to the vast diversity of human movements and the inherent complexity of the human body. Furthermore, the ability to capture and replicate subtle human interactions---such as a hug---that are intuitively understood by humans continues to be a significant obstacle for machines. This complexity arises from the need for a deep understanding of the physical world, its constraints, and the nuanced ways in which humans interact with it.This thesis presents the development of several methodologies for reconstructing and modeling various aspects of humans in 3D, including detailed shape, pose, and motion, mainly from RGB images. A key emphasis is placed on capturing or incorporating contextual information as additional information. First, we introduce a method for modeling the detailed body shape of individuals, which includes elements such as clothing across a wide range of poses. Subsequently, the focus shifts to the simultaneous pose estimation of multiple individuals, wherein scene constraints are employed to enhance the accuracy of these estimations. This approach addresses the fundamental challenges of depth and scale ambiguity inherent in 3D reconstruction. The work is then extended into the temporal domain, to reconstruct interacting individuals, particularly in scenarios involving close interactions. A significant challenge under such situations is the lack of compliance with physical laws, such as body collisions. To address this, we integrate a fully-featured physics simulator within a motion estimation pipeline to account for these physical inconsistencies. Lastly, we propose a method capable of generating human motion that interacts with a virtual environment. All proposed methods have undergone extensive evaluation.In summary, this thesis introduces a suite of tools for the modeling and reconstruction of 3D humans, advancing the field towards more accurate capture and recreation of realistic behavior for virtual humans, with a particular emphasis on their interactions with its surrounding environment.
  

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

• DELMAS, GINGER: Linking Human Poses With Natural Language
  
  Author: DELMAS, GINGER
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Institute of Robotics and Industrial Informatics (IRI)
  Mode: Normal
  Deposit date: 10/03/2025
  Reading date: 23/05/2025
  Reading time: 10:00
  Reading place: Sala d'Actes, Facultat de Matemàtiques i Estadística, Universitat Politècnica de Catalunya (FME), Carrer de Pau Gargallo, 14, 08028 Barcelona
  Thesis director: MORENO NOGUER, FRANCESC D'ASSIS | WEINZAEPFEL, PHILIPPE
  Thesis abstract: Human pose is key to multiple human-centric applications, in a wide range of domains such as art (person depiction), sport (fitness coaching), robotics (skill teaching), entertainment (motion capture in movies, digital animation) or digitization (avatar design). In order to materialize such systems, researchers have designed deep learning models which address the related, underlying tasks of pose-guided image synthesis, 3D human pose estimation, human motion generation, mesh synthesis, pose prior production, and so forth.Until very recently, human pose had mostly been studied in conjunction with images. The field twitched with the arrival of efficient language models, which fostered the incorporation of linguistic in vision frameworks, and thereby powered multi-modal applications.This thesis fits into this dynamic. We aim to leverage Natural Language (NL) to bud human pose understanding in human-centric tasks. In contrast to prior endeavors, we juggle with static 3D human poses, images and detailed NL texts all together. We further explore novel multi-modal applications, requiring fine-grained understanding of the human pose.First, to alleviate the lack of data, we introduce new datasets linking 3D human poses with NL texts. We notably investigate two settings. One where the text is a description of the target pose, and another where the text provides modification instructions to reach the target pose from a source pose. These datasets result both from (i) the collection of crowd-sourced annotations, and (ii) the automatic, rule-based generation of texts, which consists in the incorporation of classified pose measurements into templates sentences. Next, we use these datasets to develop several cross-modal generation models like text-driven pose synthesis, pose captioning, text-guided pose editing and generation of textual posture feedback. Eventually, we connect 3D, text and images through a novel combinating framework, so as to derive a versatile, multi-modal pose representation, to be leveraged for downstream tasks akin to pose estimation or NL posture feedback from visual input.In summary, we tackle multiple machine learning tasks entailing human pose understanding, thanks to the connection of human pose and Natural Language.
  
• TIAN, YI: Bio-inspired Event-driven Intelligence for Motion Estimation
  
  Author: TIAN, YI
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Institute of Robotics and Industrial Informatics (IRI)
  Mode: Normal
  Deposit date: 18/03/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: ANDRADE CETTO, JUAN
  Thesis abstract: Motion estimation problems can range from low degrees of freedom (DOF) ego-motion estimation to complex, high-DOF motion, which includes dense pixel displacement or optical flow. This information is essential for enabling robots to perceive and navigate their environments. However, existing vision systems for motion estimation are less robust and efficient than biological systems, largely due to limitations in sensor technology and processing methods. This thesis builds on the bio-inspired sensor -event camera-, and the brain-inspired computing approach -Spiking Neural Networks (SNNs)-, presenting a promising solution that bridges these gaps. Event-based cameras have high temporal resolution, low latency, reduced data redundancy, and are power efficient. These unique capabilities make them particularly well-suited for environments and tasks where traditional frame-based cameras struggle. They show great potential for the solution of motion estimation problems across a wide range of applications, such as providing accurate and low-latency motion estimation for autonomous vehicles or aerial robots. SNNs are inspired by how neurons in the human brain communicate through synapses using spikes, which are brief and discrete electrical signals that allow highly efficient and robust information processing. The thesis begins with estimating 3-DOF ego-motion, progresses to sparse optical flow, and ultimately tackles dense optical flow. In the first step, the thesis addresses event-based ego-motion estimation by integrating SNN approaches with traditional optimization-based techniques. It explores the ego-motion estimation problem from inference optical flow obtained by an SNN and proposes a pooling method to address the aperture problem encountered in the sparse and noisy normal flow output of the SNN. In the next step, modern artificial neural network (ANN) architectures are leveraged to improve event-based optical flow estimation. This step proposes a U-Net transformer-based architecture with a recurrent neural network as the backbone. In the final phase of this research, the visual transformer architecture is further extended to flow encoders, incorporating spatiotemporal attention to enhance the extraction of temporal information. This led to the development of a swin transformer-based ANN model and its spiking counterpart. Notably, this work marks the first use of spikeformers in event-based optical flow estimation, demonstrating the potential of combining transformer architectures with SNNs for regression tasks. Overall, this thesis advances the understanding of motion estimation using event cameras. It sets the stage for their application in real-world scenarios such as high-speed object tracking and simultaneous localization and mapping (SLAM). The biologically inspired methods developed in this thesis offer promising avenues for balancing the performance and efficiency of computer vision and robotics systems, paving the way for future innovations in this field.
  
• ZHANG, SHUANG: STATE ESTIMATION, DIAGNOSIS AND CONTROL USING SET-BASED APPROACHES FOR LPV SYSTEMS
  
  Author: ZHANG, SHUANG
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Institute of Industrial and Control Engineering (IOC)
  Mode: Normal
  Deposit date: 10/01/2025
  Reading date: 25/04/2025
  Reading time: 10:00
  Reading place: Aula Capella de l'Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB), Av. Diagonal, 647, 08028 Barcelona
  Thesis director: PUIG CAYUELA, VICENÇ | IFQIR, SARA
  Committee:
       PRESIDENT: MAMMAR, SAID
       SECRETARI: NEJJARI AKHI-ELARAB, FATIHA
       VOCAL: COMBASTEL, CHRISTOPHE
  Thesis abstract: Considering that Linear Parameter-Varying (LPV) technique has beendemonstrated as an effective way to represent nonlinear systems, results concerning the design of observers and controllers in LPV framework have been widely studied.This thesis contributes to the state-of-the-art in the field of robust state estimation, fault diagnosis and control for LPV systems, particularly in the presence of processing disturbances and measurement noise. The research is motivated by the safety-critical systems, such as autonomous vehicles, which require reliable fault diagnosis schemes for detecting and identifying potential actuator/sensor faults under uncertainties, and control strategies that are able to handle both the uncertainties and faults to achieve optimal and reliable performance. State estimation plays a crucial role in both fault diagnosis and controller design. To ensure robust performance, a set-membership state estimation method is developed for LPV systems subject to disturbances and measurement noises. These uncertainties are assumed to be unknown but bounded by zonotopes. The optimal state estimates are obtained by minimizing the radius of the bounding zonotope, formulated as an optimization problem in the form of Linear Matrix Inequalities (LMIs). Furthermore, the proposed method is extended to handle fault detection and estimation in more complex scenarios, including switched LPV systems and Nonlinear Parameter-Varying (NLPV) systems. In addition, Minimum Detectable Fault (MDF) and Minimum Isolable Fault (MIF) are characterized using zonotopic set-invariance approach. In the area of control, this thesis develops a Linear Quadratic Zonotopic (LQZ) control for the state feedback problem in the presence of uncertainties, in which the feedback loop is closed using the optimal estimates provided by a Zonotopic Kalman Filter (ZKF). The proposed LQZ control is less conservative, as it models uncertainties using zonotopic sets rather than Gaussian probability distributions. This formulation establishes the LQZ control as a zonotopic counterpart to the well-known Linear Quadratic Gaussian (LQG) control. Furthermore, in the presence of actuator fault, a Fault Tolerant Tracking Control (FTTC) strategy is developed. This strategy comprises a ZKF for state and fault estimation, a fault compensation mechanism and a state-feedback controller designed to achieve $\mathscr{H}_\infty$ performance.The above-mentioned contributions have been applied to state estimation, fault diagnosis and path-tracking control in vehicle lateral dynamics. Application to real data recorded with a prototype equipped vehicle demonstrates the relevance and efficiency of the proposed approaches.
  

DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING

• DAVIS ORTIZ, ALBERTO: Development of a Fuzzy Logic-Based Algorithm for Stroke Detection in Non-Contrast Computed Tomography Images
  
  Author: DAVIS ORTIZ, ALBERTO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING
  Department: Department of Automatic Control (ESAII)
  Mode: Normal
  Deposit date: 18/02/2025
  Reading date: 09/05/2025
  Reading time: 16:30
  Reading place: Aula 28.8, 1a planta, Edifici I, Escola Tècnica Superior d'Enginyeria Industrial de Barcelona, Campus Diagonal Sud, Av. Diagonal, 64708028 Barcelona
  Thesis director: AYMERICH MARTINEZ, FRANCISCO JAVIER | GORDILLO CASTILLO, NELLY
  Thesis abstract: The present work addresses the problem of early stroke detection, not only from the perspective of detection accuracy, but also focusing on computational efficiency, considering the limited availability of cases for training. To this end, several algorithms have been developed to optimize different processes, such as a brain extraction algorithm, an affine transform algorithm, and a specific adaptive filter for noise in computed tomography images. This research has generated valuable resources, such as a brain atlas of healthy Mexican patients and a template of vascular territories. The use of atlases allowed the extraction of features from specific areas. The features used were relatively simple, such as histograms and Haralick textures, which were combined with linear discriminant analysis and an adaptive neuro-fuzzy inference system as a second layer of feature extraction, and finally with a support vector machine as a classifier. Together, these methods achieved a performance of 98.25%. The results show that using the adaptive neuro-fuzzy inference system as a feature extractor improves the performance of other classifiers due to its ability to handle uncertainty and identify nonlinear relationships between variables. This study contributes to the development of low computational cost algorithms and provides new perspectives and tools that could be applied in a real environment in the future
  
• ZIVANIC, MILICA: Cold plasma-treated hydrogels for multimodal cancer therapy
  
  Author: ZIVANIC, MILICA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING
  Department: Department of Materials Science and Engineering (CEM)
  Mode: Change of supervisor
  Deposit date: 10/03/2025
  Reading date: 04/04/2025
  Reading time: 12:00
  Reading place: Aula A1.06, Edifici, A, Av. d'Eduard Maristany, 16, 08019 Barcelona
  Thesis director:
  Thesis abstract: Cold atmospheric plasma (hereon just plasma) is a weakly ionized gas that gained attention as a cost-efficient and well-tolerated cancer treatment that selectively targets the altered redox metabolism of malignant cells. The short penetration depth of direct plasma treatment limits its clinical applications to surface targets. Plasma-treated hydrogels (PTHs) emerge as vehicles for local delivery of therapeutic plasma-derived reactive oxygen and nitrogen species (RONS) to internal targets. To prepare a PTH, an aqueous solution containing low concentrations of polymers is exposed to plasma to enrich it with RONS and is then crosslinked into the three-dimensional hydrogel network entrapping RONS inside. Once in contact with the target, RONS can diffuse from PTH and, above a cell-specific threshold, cause irreversible damage and death to cancer cells. Importantly, PTHs could broaden the clinical application of plasma not only by acting as RONS vehicles but also by being a versatile physicochemical platform that can incorporate different bioactive polymers or drugs for combined therapeutic effects, as explored for the first time in this Thesis.This Thesis proposes and follows an iterative workflow cycle for the development and characterization of PTHs. Here, alginate was chosen as a biopolymer for the preparation of PTHs, due to its biocompatibility, relevance, and versatility in biomedical research, as well as the ability to crosslink under mild conditions. In the first place, an optimized protocol for the preparation of alginate-based PTHs was identified, in order to ensure high retention of therapeutic RONS during the crosslinking process and obtain an injectable, shear-thinning formulation useful for minimally-invasive delivery and shape-adaptability of the PTH. Before this Thesis, biological characterization of PTHs was limited to cancer cytotoxicity reports. Here, the ability of a PTH to induce immunogenic cell death was demonstrated for the first time. As a result, PTH-treated osteosarcoma cells were increasingly phagocytized when co-cultured with immature dendritic cells derived from human monocytes isolated from healthy blood donors. Following the initial physicochemical and biological characterization, the feasibility and efficacy of incorporating a secondary therapeutic modality to the PTH were investigated. For this, a bioactive polymer or a chemotherapeutic drug was introduced into the alginate PTH formulation to achieve biological effects beyond or in synergy with plasma-derived RONS. Importantly, these effects were studied in a relevant model: an in ovo cancer model, where three-dimensional and vascularized tumors were grown on the membrane of a fertilized chicken egg (in ovo). This enabled the assessment of cancer cells in an environment more similar to a native, clinical one. In ovo tumor models emerge as cost- and time-effective models and can help replace, reduce, and refine in vivo experiments in preclinical research. In contrast to mono-therapy with PTH or drug alone, which showed no effect in ovo, a single administration of PTH-drug co-therapy could diminish osteosarcoma tumor weight and the expression of a protein linked to treatment resistance.Altogether, the work presented in this PhD Thesis helped characterize and establish PTHs within the plasma community as a novel modality that can broaden the clinical application of plasma. Furthermore, it provided a proof of concept that PTHs can be used as versatile dual platforms for multimodal cancer management.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• , DUOLAN: Integration of Spatial and Temporal Patterns for ecological environment management in River-Riparian System
  
  Author: , DUOLAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Article-based thesis
  Deposit date: 18/03/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: BLADE CASTELLET, ERNEST | SANCHEZ JUNY, MARTI
  Thesis abstract: Rivers are important carriers of water resources and important components of ecosystems. In some areas, rivers have been artificially narrowed, riparian areas have been encroached upon, riparian resources have been over-exploited, and artificial restrictions have been placed on the river channel. This resulted in the loss of the river's role in receiving and storing flood waters, which leading to the collapse of river banks and the destruction of river embankments, severely affecting the stability of the river, threatening the safety of bridges, culverts and other critical river-related infrastructure, and endangering the ecological environment. The definition of riparian zones is particularly important for the management and protection of rivers. In the implementation of policies to promote river management in various countries, emphasis has been placed on strengthening the management of riparian zones, ensuring the safety of flood control and giving full play to the comprehensive ecological benefits of rivers. In recent years, various countries have proposed laws and regulations in recent years mainly to control overdevelopment, restore natural vegetation growth in riparian areas, protect habitats and achieve flood control. With the progress of water-related social development, the balance between environmental impact and benefits is increasingly emphasized. Changes in river shape, man-made riverbeds, and riverbank construction affect aquatic life and destroy wildlife habitats. River regulation also alters ecosystems. To reduce these impacts, government agencies implement protocols for riparian assessment and monitoring, including physical habitat, hydromorphological, and hydrological regime evaluations.The research first begins with a retrospective analysis as the starting point to acquire how existing laws and regulations on development and restoration lack effective integration and induce weak adaptability. A river-riparian model is developed based on two-dimensional hydraulic modelling integrated with numerical modelling by relying on topographical, hydrological, vegetation, and soil data to analyze the hydro-ecological cycle within the riparian zone and delineate the boundary of riparian. The model aims to provide a site-specific approach to riparian zone delineation. In addition, a system of parameters for ecological status assessment is proposed which focuses on the main contradictions between the environment conservation and the ecosystem services of riparian zones. In order to develop and analyze strategies for a good ecological status of the water bodies and riparian zones, the methodology of riparian zone delineation will provide tools for enhancing the coordination of the needs of riparian resource development and ecosystem protection and use, and the ecological environment assessment system will evaluate the hydromorphological quality and promote the healthy development of the ecological environment. The findings of this research propose a convenient and effective method for delineating riparian zones which can be basically universally applied. It is noteworthy for its applicability in riparian zone management practices and as a reference for policy strategy development. The proposed quantitative evaluation method covers the key aspects of hydromorphological quality evaluation. This eliminates the highly subjective assignment of weights and classification of evaluation levels while also avoiding the inclusion of complex calculation procedures. The river-riparian areas evaluation method allows the decision-makers to easily analyze the problems through the resulting calculations and lay the foundation for further solutions.
  

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

• PUJOL TORRAMORELL, ROGER: Improving Real-Time Guarantees of Cache Coherence and Advanced Interconnections in Real-Time Systems
  
  Author: PUJOL TORRAMORELL, ROGER
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 18/03/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: CAZORLA ALMEIDA, FRANCISCO JAVIER | ABELLA FERRER, JAIME
  Thesis abstract: The dissertation, research on enhancing timing predictability and performance for Critical Real-Time Embedded Systems (CRTES), focusing on Multi-Processor Systems on Chip (MPSoCs). CRTES are essential in critical domains like automotive and avionics, where complex functionalities and high performance are increasingly required for operations such as AI and multi-sensor data processing. However, MPSoCs face significant timing verification and validation (V&V) challenges, especially related to shared resources like caches and interconnects, which can introduce unpredictable delays. This thesis addresses three core areas to improve CRTES predictability: cache coherence, interconnection predictability, and application performance through vector extensions.Cache Coherence: In MPSoCs, cache coherence protocols ensure consistent data across multiple cores, but shared caches introduce contention that affects timing predictability. Traditional approaches to improving coherence often involve modifying protocols, a costly and complex task. This thesis takes an alternative approach by leveraging hardware event monitors (HEMs) to observe cache contention, providing valuable data for timing V&V without altering existing protocols. This methodology is applied to commercial MPSoCs like the NXP T1040 and T2080, which are widely used in real-time domains.On another note, the Remote Protocol-Contention Tracking (RPCT) method is proposed, which enables fine-grained tracking of delays due to inter-core contention, offering insights into cache coherence impacts on software predictability and informing developers on optimization strategies. Additionally, the thesis proposes a novel Multiple HEM Validation (MHV) method to improve the accuracy of contention measurements by validating HEM reliability through inter-HEM relationships, mitigating known issues with single-event HEM inaccuracies.Interconnections: MPSoCs rely on point-to-point (P2P) communication protocols like AXI4 for data transfer between cores, but the standard AXI protocol lacks timing constraints, making it unpredictable under real-time requirements. Addressing this, this thesis introduces AXI4 Real-Time (AXI4RT), an extension to the AXI protocol that specifies timing parameters to control the duration of transactions between manager and subordinate interfaces. By defining timing guarantees directly within the protocol, AXI4RT ensures predictable communication, enhancing system reliability for real-time applications. Additionally, this thesis provides some initial steps for contention tracking on modern AXI5 interconnects by doing an in-depth analysis how can contention be tracked with currently available HEMs and proposing some HEMs that could improve this tracking.Application Performance with Vector Extensions: To meet growing performance demands in CRTES, MPSoCs often use GPUs and custom accelerators, but these present certification challenges due to their complexity and unpredictable timing. This thesis explores using vector extensions (VExt) as an alternative. Single Instruction Multiple Data (SIMD) processing units are already available in many embedded processors, which perform parallel operations on multiple data elements, effectively improving data processing speeds. Unlike GPUs, VExt are integrated within processors and comply with high-integrity system standards, making them easier to certify. The thesis provides an analysis of VExt in COTS processors like NVIDIA’s AGX Xavier and show their potential to enhance performance while maintaining compliance with standards such as MISRA-C.In summary, this thesis advances the state-of-the-art in CRTES predictability, presenting solutions that ensure more reliable timing for complex embedded systems in safety-critical applications. By addressing cache coherence, interconnect timing, and performance, this thesis provides tools and methodologies for better timing analysis, enabling MPSoCs to improve real-time guarantees.
  
• SEYGHALY, RASOOL: A Federated Learning Approach to Smart Advertising
  
  Author: SEYGHALY, RASOOL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 17/03/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: GARCÍA ALMIÑANA, JORDI | MASIP BRUIN, XAVIER
  Thesis abstract: This thesis presents a Federated Learning-based Smart Advertising System designed to enhance user engagement, optimize network efficiency, and ensure data privacy in digital advertising. Traditional advertising systems face significant challenges in balancing personalization with privacy, managing network overhead, and scaling efficiently. This study addresses these issues by integrating Edge Computing and Federated Learning (FL) to enable real-time, decentralized ad targeting while keeping user data secure.The proposed system consists of a decentralized recommendation engine, where local models are trained on users’ devices and aggregated using meta-heuristic optimization techniques, particularly the Whale Optimization Algorithm (WOA). Experimental results demonstrate that WOA outperforms other aggregation techniques, such as the Firefly Algorithm (FA) and Bat Algorithm (BA), in terms of convergence speed and overall efficiency. The system also leverages formal verification techniques, including model checking, to ensure correctness, security, and compliance with privacy regulations.Comprehensive evaluation through both simulated and real-world case studies (such as the AROUND system) shows that the proposed architecture reduces network traffic, minimizes computational overhead, and significantly improves Click-Through Rates (CTR) and user engagement compared to traditional centralized models. The system is particularly beneficial for applications in museums, shopping malls, and retail chains, providing real-time tracking, indoor mapping, and personalized content delivery.The findings underscore the potential of Federated Learning and Edge Computing in privacy-preserving smart advertising, offering a scalable, cost-efficient, and user-centric solution for the future of digital marketing.
  

DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING

• RAMONELL CAZADOR, CARLOS: Graph-driven digital twins as assistants to bridge maintenance
  
  Author: RAMONELL CAZADOR, CARLOS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 10/03/2025
  Reading date: 28/05/2025
  Reading time: 10:00
  Reading place: C1-002
  Thesis director: CHACÓN FLORES, ROLANDO ANTONIO
  Thesis abstract: Bridges are vital components of transport infrastructure networks which are facing a widespread lack of resilience due to aging and changing environmental conditions. Finding more efficient methods for monitoring bridge networks and effectively planning their maintenance is crucial for maintaining reasonable serviceability levels. Simultaneously, digital twins are emerging across industries as dynamic digital replicas of physical assets. These are continuously updated with information from their physical counterparts and serve as the foundation for digital tools that enhance workflows in decision-making processes throughout the lifecycle of any product.This dissertation translates the concept of digital twins to the bridge maintenance domain and presents a framework for developing graph-driven digital twin systems to assist bridge managers in tracking the state of their asset portfolio.For this purpose, two different proof-of-concept systems are presented: System A and System B. Both systems are cloud-based, modular, and use graphs to integrate multiple data sources describing the bridges, their context, and relevant maintenance information. The systems are tested with real data corresponding to two demonstration cases of road and railway bridges in the Spanish infrastructure network. Through these demonstrators, the digital twin systems are developed to integrate BIM, GIS, sensor time-series data, and data related to the results of monitoring processes that is structured according to regional standards.System A focuses on hosting digital twins of individual bridges. It uses a labelled property graph (LPG) to interconnect IFC data with IoT sensor data and the results from visual inspections and load tests. Data integration is achieved by matching GUIDs of data contained the graph with data stored in the different databases and systems connected. The implementation of the system is demonstrated through a web-based digital twin platform, containing applications that allow visualizing and interacting with contextualized inspection and load test data.System B focuses on interconnecting multiple bridge digital twins within the same network. It employs a knowledge graph built from Resource Description Framework (RDF)-based graphs and a set of ontologies. The system integrates geographical data according to INSPIRE data models, IFC models, and data from visual inspections. The system presents a data management approach based on strata, which manage and compartmentalize information subsets, and implements the information containers for linked document delivery (ICDD) standard for exchanging graph data with linked documents. The system is demonstrated through a set of fictitious scenarios that simulate interactions between bridge administrators and third parties.Through these systems, this dissertation demonstrates the usefulness of graph technologies in developing digital twins of bridges that are aligned with current industry standards and practices. It emphasizes the advantages of the Knowledge Graph-based approach for simplifying interactions with connected applications, enabling decoupled application development, and enhancing the system scalability and expandability with new datasets. Notwithstanding, real implementation of these systems requires further validation and use cases, as well as collaboration among system developers, administrators, academia, and industry stakeholders to generate a coherent digital ecosystem that enhances the efficiency and productivity of bridge maintenance practices.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• AL HANAINEH, WAEL HASAN AHMAD: Designing and Development of Secure Protection Strategies for Distribution Network Integrated with Distributed Energy Resources
  
  Author: AL HANAINEH, WAEL HASAN AHMAD
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Article-based thesis
  Deposit date: 10/03/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: MATAS ALCALA, JOSE | GUERRERO ZAPATA, JOSEP MARIA
  Thesis abstract: Global electricity generation increasingly incorporates Distributed Generation (DG) resources, such as solar and wind, into distribution systems (DS), offering benefits like improved reliability, power quality, rapid integration, and reduced payback periods, while lowering greenhouse gas emissions. However, their integration presents challenges, including overvoltage, voltage fluctuations, and imbalances caused by improper synchronization with the grid. DGs alter short-circuit currents, necessitating updates to protection relay settings. As DG penetration rises, distribution networks become more complex, requiring advanced protection systems to handle bidirectional power flows, which challenge existing schemes. Inverter-based DGs, such as solar and wind, generate lower fault currents due to inverter power electronics, diminishing the effectiveness of traditional fault detection methods, leading to potential protection blinding or false tripping. These challenges highlight the need for precise fault detection, accurate localization, and rapid protective responses. Disconnecting DGs during faults is increasingly undesirable, requiring innovative protection schemes to minimize unnecessary disconnections and address limitations like fault resistance, pre-fault load conditions, and noise interference. Traditional fault location techniques, often computationally intensive, struggle with accuracy, prolonging restoration times and increasing downtime, further emphasizing the need for advanced fault protection systems. Total Harmonic Distortion (THD) analysis has proven effective for fault detection in systems with complex harmonic profiles caused by DG integration. Faults induce increased harmonic distortion, making THD monitoring a valuable indicator. Despite its promise, protection systems for grids with high DG penetration, especially those using inverter-based DGs, are underexplored, and existing protection algorithms rarely incorporate THD. To address this, three novel protection systems utilizing grid voltage harmonic content for fault detection and localization in medium-voltage (MV) DS are proposed. The first system combines THD measurements with voltage amplitude and zero-sequence components using a finite state machine (FSM)-based algorithm. It focuses on third harmonic (triple-n) components, unique to inverter neutral points and unaffected by other grid harmonics. Fault-induced voltage dips excite harmonic components, amplifying THD, making it an effective fault indicator. THD is calculated using the Multiple Second Order Generalized Integrator (MSOGI) method. However, this system relies on communication channels, which could fail, limiting its robustness. To mitigate this, a two-layered protection system is introduced. The first layer employs the SOGI-FLL grid monitoring technique, optimizing computational efficiency by reducing the number of required SOGIs while maintaining accurate THD calculations. Fault detection is achieved by filtering the THD signal and comparing pre-fault and fault-time averages, with significant deviations indicating faults. The second layer implements a communication-less fault localization algorithm based on positive and negative voltage sequence components to determine fault symmetry. This approach enables each protection device (PD) to operate independently, ensuring reliable fault localization even without communication, albeit with slightly slower detection times compared to communication-based methods. To enhance overall reliability, especially during communication failures, a third system, priority system, is proposed. It integrates the two-layered protection, with the first layer as the primary fault detection and communication-based trip signal initiator. If communication fails, the second layer provides backup protection by analyzing voltage sequence components locally. The effectiveness of these systems is validated against different protection method under various conditions.
  

DOCTORAL DEGREE IN ELECTRONIC ENGINEERING

• MORADMAND JAZI, HAMED: Design and implementation of lowinterference, high efficiency, power electronicbased power system for PV applications
  
  Author: MORADMAND JAZI, HAMED
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRONIC ENGINEERING
  Department: Department of Electronic Engineering (EEL)
  Mode: Normal
  Deposit date: 13/03/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: MARTINEZ GARCIA, HERMINIO | VELASCO QUESADA, GUILLERMO
  Thesis abstract: Nowadays, high step-up converters with fast-dynamic response are demanded for many applications such as uninterruptible power supplies which are used to feed sensitive loads and DC-DC converters in grid connected micro inverters to absorb the maximum power from the PV panels. Several studies have been carried out on high step-up converters to increase voltage gain and efficiency as well as reduce the voltage stress of semiconductors while less attention has been paid to their dynamic response. A converter which can compensate load variations rapidly would have faster dynamic response and lower undershoot and overshoot output voltage and current. In this research, various switching converters will be investigated to achieve new topologies having the capability of faster dynamic response and obtaining higher voltage gain for the above-mentioned applications. Merging some converters has the potential of removing right half plane zero and making converters respond load variations at a faster pace without making any changes in the control circuit and filters. If the integrated converter can deliver power form the input to the load in all operating modes whether the switch is on or not, the converter would compensate load variations with lower interruption. This theory can be evaluated and proved by doing some theoretical and mathematical calculations on the control response and the situation of Zeros and Poles of the closed loop transfer function of the converter. To rate the achievements of this research, the dynamic quantities in the step response of the converters (e. g. overshoot, rise time, and settling time) can be investigated. Also, the voltage gain and efficiency of the converters are important qualities which have to be considered in comparisons. A time table is considered for each stage to ensure that this research can be finished through the next three years.
  

DOCTORAL DEGREE IN MARINE SCIENCES

• RAYA RODRIGÁLVAREZ, VANESA MARIA: Spatial and temporal dynamics of larval fish communities in relation to environmental variability in the NW Mediterranean
  
  Author: RAYA RODRIGÁLVAREZ, VANESA MARIA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MARINE SCIENCES
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 10/03/2025
  Reading date: 15/05/2025
  Reading time: 10:00
  Reading place: ETSECCPBUPC, Campus NordBuilding C1. Room 002.C/Jordi Girona, 1-308034 Barcelona
  Thesis director: SABATÉS FREIJÓ, ANA MARIA
  Thesis abstract: The early developmental stages of fish, eggs and larvae, found in the planktonic environment are subject to a high mortality. Thus, the study of larval survival has been a key issue in fisheries science since the early 20th century. Spatial patterns in the larval fish communities are influenced by a complex array of environmental processes that interacts with fish biology at different temporal and spatial scales. These processes include those of large scale, such as climate patterns and seasonal and interannual environmental variability, which determine adults’ distribution and their spawning strategies. At local and short time scale, larval fish communities are shaped by the hydrodynamics that influence fish larval dispersal and retention, and by biologic factors, such as food concentration and predation, that ultimately determine their survival.This thesis characterises the structure of the larval fish community in summer and winter in the Catalan coast (NW Mediterranean), an area with a wide array of environmental conditions and high hydrodynamic activity. The aim is to understand its spatial and interannual variability in response to changes in environmental conditions, including oceanographic variables and hydrodynamic processes. Within the context of climate change, the thesis describes long-term changes in the structure of the summer larval fish communities and aims to understand the interactions between larvae of established species and species that are expanding northwards in the area.To investigate the influence of winter environmental conditions on the structure of fish larval communities, two winters, 2017 and 2018, with contrasting environmental conditions were compared. 2017 was mild, while 2018 was more severe, with intense vertical mixing and deep-water formation and cascading events that enhanced shelf-slope water exchanges. Differences in the structure of larval fish community were found in relation to shelf-slope water exchange processes.A high spatial heterogeneity in larval fish communities was detected in the summers of 2003, 2004 and 2012, related to environmental factors, such as the continental shelf structure, latitudinal difference in surface temperature, primary productivity, and stratification level. Hydrodynamic structures such as instabilities of the Northern Current and anticyclonic eddies, also played an important role in the configuration of these communities.In summer, over three decades, 1980s, 2000s and 2010s, an increase in sea water temperature and a decrease in chlorophyll were detected. Changes in the composition and abundance of the larval fish community were also detected. These were mainly due to the presence of warm water species in the area for the first time, or to their increase in abundance, in the 2000s in relation to the northward expansion of the adults' range. Other species showed a decline in abundance over time, probably due to the decrease in chlorophyll.This work quantitatively compared the survival chances for larvae of E. encrasicolus (a established species) and S. aurita (a species expanding northwards). To this aim, a new method, the Box-Balance Model, was developed to evaluate the role of hydrodynamic structures in their mortality. The model revealed that despite the warming trend would contribute to the expansion of S. aurita, it has not yet developed an adaptation strategy as successful as that of E. encrasicolus, a well-established species in the area.
  
• ZOELLER, VICTORIA CHRISTINE: Stability and Dynamics of Geophysical Neutral Vortices
  
  Author: ZOELLER, VICTORIA CHRISTINE
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MARINE SCIENCES
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 13/03/2025
  Reading date: 10/04/2025
  Reading time: 16:00
  Reading place: Sala de actos del Instituto Ciencias del Mar Pg. Marítim de la Barceloneta, 37, Ciutat Vella, 08003 Barcelona
  Thesis director: VIUDEZ LOMBA, ALVARO
  Thesis abstract: Mesoscale and submesoscale vortical structures are ubiquitous in the ocean and atmosphere. Most of these vortices are long-lived with a lifetime of several months. They often travel considerable distances and can interact with currents, other vortices, or topographic features. They play an important role in the distribution of heat, salt, and other tracers in the global ocean circulation. This PhD dissertation consists of the numerical investigation of the stability and dynamics of these meso-and submesoscale ocean vortices in both two-dimensional (2D) isochoric Euler flows, and three-dimensional (3D) quasi-geostrophic (QG) flows. In particular, this dissertation places special emphasis on neutral vortices, with a continuous vorticity distribution in 2D or potential vorticity anomaly (PVA) distribution in 3D QG flows.A neutral vortex is defined as a vortex with vanishing circulation at its outer boundary. This kind of shielded neutral vortex is a much more realistic approximation to vortices in the ocean than other theoretical approximations of shielded vortices. The neutral and non-neutral vortices used in this dissertation are linear combinations of vorticity layer-modes (or PVA spherical layer-modes in 3D QG), which consist of conveniently normalized cylindrical (or spherical) Bessel functions of order 0, truncated by a zero of the Bessel function of order 1. A necessary condition for vortices to be unstable is the change of sign of PVA somewhere inside the vortex. Thus, neutral vortices are subject to being unstable, which would be at odds with their observed long-time persistence. Therefore the first aim of this thesis is to present new exact 3D QG solutions for neutral vortices with distributed PVA. Depending on the superposition of the different layer-modes, some vortices remain axisymmetrically robust to small vorticity perturbations, while others are slightly unstable and evolve into stable multipolar structures. Robust axisymmetric neutral vortices have no exterior potential flow, thus generating no physical impact on the vortex surroundings. Furthermore, the robust vortex solutions found in this dissertation could explain the long persistence of baroclinic vortices in the ocean. The exact solutions of neutral vortices described in this dissertation are used to investigate further the interactions of these vortices.The first interaction studied is the interaction between a small-amplitude shear current and different vortices, specifically a neutral robust vortex, a neutral unstable vortex, and a non-neutral vortex. The results show that neutral vortices are good models for geophysical vortices as these vortices remain robust during their interaction. Both the vortices and the shear current remain robust while the vortices cross the shear current until reaching their stable equilibrium location, which is of the same vorticity sign as its amount of circulation.The second interaction is between two neutral vortices. This includes the interaction of two neutral unstable vortices and the interaction of one neutral unstable vortex and one neutral robust vortex. It reveals that some pairs of neutral vortices reach an oscillating near-equilibrium state due to a vorticity (or PVA) exchange mechanism. This involves a periodic exchange of vorticity and the generation of dipolar moments within the vortices. These dipolar moments separate the vortices. However, the formation of an exterior potential flow arising from the breaking of circular symmetry, and the subsequent vorticity advection and redistribution of peripheral vorticity causes the vortices to attract.The last interaction investigated is between a Lamb-Chaplygin dipole and an axisymmetrical unshielded vortex. It shows that vortex interactions can be elastic, indicating that interactions with almost no vorticity exchange, or vorticity loss to the background field, between vortices are possible. The interaction implies a change in their direction and velocity.
  

DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING

• MORENO MARTÍN, SIRO: Collocation methods for the synthesis of graceful robot motions
  
  Author: MORENO MARTÍN, SIRO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING
  Department: Department of Mechanical Engineering (EM)
  Mode: Normal
  Deposit date: 10/03/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: CELAYA LLOVER, ENRIC | ROS GIRALT, LLUIS
  Thesis abstract: Graceful motion can be loosely defined as the one we observe in natural movements executed by animals and humans, which are characterized by being agile, efficient, and fluid. The generation of graceful robot motions is typically sought through the minimization of cost functions involving not only path length, but also aspects related to smoothness, like the time derivative of acceleration, called jerk, or that of the controls. A widely used approach to compute optimal trajectories is through direct collocation, a technique that converts the continuous-time optimal control problem into a finite-dimensional NLP problem. Collocation proceeds by discretizing the trajectory using so-called collocation points, and imposing the dynamics constraints at such points. The formulation of most collocation methods, however, assumes that the system is governed by a first order ODE, whereas robotic systems are typically described by second or higher order ODEs. As a result, the usual practice is to initially convert those ODEs into first order form via introducing new variables, and adding new equations that link these variables with their integral counterparts. An often overlooked effect of this transformation is that it generates inconsistencies between the trajectory of each variable and that of its time derivative. This is so because a collocation method only imposes the differential relationships at the collocation points, but not in between such points. A closer examination of this effect reveals that the dynamic equations, which should be satisfied in the collocation points, are actually violated in them, despite apparently having been enforced. This thesis introduces new collocation methods designed to overcome these problems. Specifically, we develop improved versions of the most popular piecewise and pseudospectral collocation schemes, including the trapezoidal and Hermite-Simpson methods, as well as the LG, LGR, and LGL methods. The new algorithms are able to treat differential equations of arbitrary order M ≥ 1 without having to convert them into first order form. In all of them, the trajectory obtained for each variable coincides exactly with the time derivative of its corresponding integral variable, and the dynamic constraints are satisfied accurately at the collocation points. These properties allow a drastic reduction of the dynamics error of the obtained trajectories in many cases, meaning that the governing equations are better respected along the continuous time horizon of the problem. Our methods also provide trajectories that are smoother than those of conventional ones, and easily treat variables such as jerk or the time derivative of the controls in the cost function. An hp adaptive refinement algorithm is also proposed to combine the benefits of our piecewise and pseudospectral methods so as to speed up convergence to the solutions.
  

DOCTORAL DEGREE IN PHOTONICS

• LI, GENG: Fourier Transform Infrared Spectroscopy of Twisted Bilayer Graphene
  
  Author: LI, GENG
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 10/03/2025
  Reading date: 11/04/2025
  Reading time: 10:00
  Reading place: ICFO Auditorium
  Thesis director: KOPPENS, FRANK
  Thesis abstract: The goal of this thesis is to probe the infrared optical response of twisted bilayer graphene (TBG) using Fourier transform infrared spectroscopy (FTIR). First, I used a commercial FTIR to measure the TBG in the mid-infrared range at room temperature. I improved the device fabrication technique and fabricated the TBG devices with a large area and simultaneously a low inhomogeneity. I observe that the TBG has abundant optical absorption features originating from the interband transitions that are uniquely determined by the twist angle. Then, I want to probe the interband transition of the TBG that lies in the terahertz range, which evolves the flat band of the TBG that hosts strongly correlated effects. I built a homemade FTIR that works in both the mid-infrared and terahertz range. I wired the cryostat carefully and achieved an electrical noise level approaching the Johnson noise limit. By guiding the light from the FITR into the cryostat, I successfully measured the exciton states in the Bernal bilayer graphene device over a broad spectral range, demonstrating that the system is ready for future experimental study of TBG.
  

DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS

• DOROST, POROCHISTA: Nanoparticles made of poly(gamma-glutamic acid) derivatives for drug delivery systems
  
  Author: DOROST, POROCHISTA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 14/03/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: GARCIA ALVAREZ, MONTSERRAT
  Thesis abstract: Polymers have become one of the primary options in biomedical fields due to their diverse properties, functionalities, and applications. Characteristics such as mechanical strength, biocompatibility, and biodegradability have made these materials highly attractive for various medical applications. One of the most intriguing applications of these polymers is drug delivery. Biodegradable polymers and copolymers are the primary materials used for producing temporary medical and pharmaceutical devices. These polymers can be chemically synthesized or naturally produced.Biotechnological polymers, produced through biotechnological processes, have garnered significant attention due to two major advantages. First, they are derived from renewable resources; second, as they are biologically produced, they are usually biocompatible, biodegradable and bioresorbable. Therefore, modifying these polymers to tune their properties or functionalities is an effective strategy for developing biomedical materials.Poly(γ-glutamic acid) PGGAH is a biocompatible and biodegradable poly-γ-peptide with carboxylic side groups that can be substituted to modify the polymer’s properties. In this study, PGGAH was hydrophobically and cationically modified. Through hydrophobic modification and altering the hydrophilic properties, amphiphilic copolymers were produced, capable of self-assemble into nanoparticle systems for drug encapsulation and controlled release. This modification was carried out by partial esterification of carboxylate side groups with 4-phehyl-butyl bromide (4-PhBBr). Further decoration to produce stealth and targeting nanoparticles was achieved by reaction of some remaining carboxylate side groups with amino ended poly(ethylene glycol) (NH2-PEG) and NH2PEG derivatized with folic acid, respectively. Cationic modification of this biodegradable polymer enabled the formation of nanopolyplexes with DNA. This modification was carried out by esterification of carboxylate side groups with cationic 2-bromoethyl trimethylammonium bromide (BrETABr). The obtained derivatives were used to prepare nanoparticles through emulsion solvent evaporation or nanoprecipitation dialysis techniques. Nanoparticles with an approximate size of 100 to 380 nm were obtained, demonstrating their potential as drug delivery systems capable of encapsulating the anticancer drug doxorubicin.The chemical structure of the derivatives were characterized using proton and carbon-13 nuclear magnetic resonance (NMR) spectroscopy, and the physicochemical properties by gel permeation chromatography (GPC), and thermal gravimetric analysis (TGA). Functional group analysis was conducted through Fourier-transform infrared spectroscopy (FT-IR). Hydrolytic degradation was monitored by 1H NMR, while the appearance of the nanoparticles was observed using scanning electron microscopy (SEM), and their size and surface charge were determined by dynamic light scattering (DLS) and zeta potential measurements, respectively.For the hydrophobic copolymer series, cytotoxicity assays were carried out, confirming the low toxicity of the synthesized derivatives. Drug encapsulation and release was initially evaluated under physiological conditions, revealing that the release rate was higher in acidic pH and affected by the degree of polymer modification. On the other hand, cellular uptake nanoparticle tests demonstrated that the nanoparticles successfully penetrated cancer cells. The results of this study indicate that the biotechnological polymer PGGAH is a promising material for designing and developing biodegradable drug delivery systems with potential therapeutic applications for challenging diseases in pharmacological treatment.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• LOPEZ MOLINA, CARLOS ALEJANDRO: On the Majorization-Minimization framework and g-convex optimization: Exploiting diversity using sparse-aware and information theoretic criteria
  
  Author: LOPEZ MOLINA, CARLOS ALEJANDRO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 13/03/2025
  Reading date: 22/04/2025
  Reading time: 10:30
  Reading place: Sala Teleensenyament, Edifici B3, ETSETB
  Thesis director: RIBA SAGARRA, JAUME
  Thesis abstract: Diversity is a well-established concept in wireless communications whose purpose is to quantify the potential robustness of a receiver when multiple independent copies of the informative signal are received. Indeed, there exists a formal definition of this concept within the context of wireless communications that takes into account its practical usage, i.e. it is defined with respect to the symbol error probability averaged over the channel statistical fluctuation. However, there is no consensus on the generalization of the previous definition to other forms of signal processing applications. For this reason and being inspired by an intuitive definition of diversity extracted from the multimodal data fusion framework, the purpose of this dissertation is to explore the concept of diversity through the lenses of Information theory, a numerical optimization framework based on the Majorization-Minimization principle and the Grassmann manifold. The motivation behind the Majorization-Minimization algorithms is that they fit perfectly to the optimization problems arising from information theoretic cost functions, while the Grassmann manifold emerges naturally in the context of sparse-aware signal processing problems that exhibit some sort of diversity. All these ideas are surveyed through three different scenarios: the multisensor fusion, the Covariance Conversion from wireless MIMO communications and the detection of correlation. All of the scenarios share the fact that the intrinsic dimension of the data is much smaller than the ambient space dimension.In the multisensor fusion problem, we analyze the intuitive definition of diversity in a straightforward manner for three fusion policies. Firstly, the Covariance Intersection principle is reviewed to highlight its connection to the minimum error entropy criterion and the waterfilling algorithm for optimal power allocation in communications. Secondly, we derive a bounded descriptor based on the R\'enyi entropy of a sensor network contamination worst-case scenario (unbounded variance). Thanks to the aforementioned descriptor, it is possible to provide an operational interpretation to the commonly used L0 norm regularization particularized for this problem. Finally, we consider a fusion scheme that incorporates a subspace-based regression technique into the fusion operation. This proposal, which is inspired by a duality with the problem of unstructured interference mitigation in navigation receivers, is motivated by the fact that it is possible to obtain a measure of the fusion integrity when the temporal redundancy of the measurements and the intersensor covariance matrix are estimated in a joint manner.Besides, a different kind of diversity is unveiled in the Covariance Conversion problem for Frequency Division Duplexing schemes from wireless communications. In essence, this problem consists in the estimation of the Downlink channel covariance matrix using a prior estimation of the Uplink channel covariance matrix. Particularly, we are interested in those cases where sparsity can be defined on the second-order statistics, which are found in the mmWave and ultra-wide band channels. Through a detailed analysis of this problem, we show a promising conversion algorithm founded on the Alternating Direction Method of Multipliers.Lastly, the detection of correlation between two Gaussian vectors problem serves as a way to explore an information theoretic approach for the quantification of diversity. In fact, we transform this setting into a Mutual Information estimation problem of M parallel Gaussian channels to yield the aforementioned information theoretic measure. However, the Maximum Likelihood estimation of the Mutual Information suffers from bias when a subset of these channels provide no information. In light of this, we propose the adoption of model-order selection rules, well-known in other areas, as a means for estimating information under a bias-variance trade-off.
  

DOCTORAL DEGREE IN STATISTICS AND OPERATIONS RESEARCH

• BLANC BLOCQUEL DI MARCO, AUGUSTO: Derivatives and risks
  
  Author: BLANC BLOCQUEL DI MARCO, AUGUSTO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN STATISTICS AND OPERATIONS RESEARCH
  Department: Department of Statistics and Operations Research (EIO)
  Mode: Normal
  Deposit date: 13/03/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: ORTIZ GRACIA, LUIS
  Thesis abstract: This thesis aims to provide solutions to real world problems by the use and development ofstate-of-the-art quantitative finance techniques. The first part of this work tackles the challenge of digital options hedging, particularly, at the-money digital options near maturity. The problem stems from the fact that a digitaloption has a discontinuous payoff at the strike price and has a huge delta and gamma nearexpiration. This problem is well-known among practitioners and academics. In this work, weconsider a general setting for hedging at-the-money digital options near maturity by meansof a bull spread. We solve different optimization problems, with the aim of minimizing theprobability of sub-hedging the digital option at maturity, considering transaction costs andilliquidity issues. Our contribution consists in the fact that we determine the compositionof the bull spread that minimizes the probability of sub-hedging a digital option given thatthe cost of hedging is below a certain threshold. We consider traditional and state-of-the-artmodels for driving the dynamics of the underlying asset. We also introduce the modelingof the illiquidity issue in the optimization problem, and solve that optimization problem.Finally, we calibrate one model to real market data and solve the optimization problem withtransaction costs with the calibrated model.In the second part of this work we intend to create financial tools to fight against climatechange. Over the last five years there have been increasing concerns about the impact ofcryptocurrency mining on climate. One of the main effects of climate change is its impacton agriculture and food production. In addition, climate change has clear consequencesfor human health. We propose novel bitcoin-denominated derivatives contracts on carbonbonds to address this problematic. This paper creates novel financial products which couldhelp the regulatory authorities impact the climate in an indirect fashion, agglutinating twodesired financial outcomes (hedging and volatility transfer) in a single financial instrument.Particularly, the instrument can be used by governments to hedge against climate change andinfluence the prices of carbon bonds and cryptocurrencies. In order to price this product, wedevelop novel parameter estimation techniques based on Shannon wavelets.The third part of this work also revolves around climate change, finance and mathematics.In this work we put forward a methodology to calculate the impact of an increase of the earth’sglobal surface temperature on the probability of default of a company from the agriculturesector. Extreme temperatures have a negative impact on asset prices in all sectors. Weperform a regression of firm’s stock value with predictors S&P 500 and temperature anomaliesand observe that an increase of temperature anomalies has a negative impact on the stockof the firm considered in this work. When modelling temperature anomalies time series it isimportant to identify points in time where a significant change occurs in the behaviour of thedata. These points are called breakpoints. Then, we model the time series of temperatureanomalies by means of segmented linear regression, where the breakpoints are estimatedby means of a wavelet analysis. We calibrate a Merton model with real stock data of thecompany and estimate the probability of default based on the probability that the assetvalue of the firm is below the liabilities level. We proceed to use the regression model toforecast future values of the firm’s stock influenced by the predicted temperature anomaliesand estimate a new probability of default.
  

DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE

• LIZÁRRAGA SÁNCHEZ, SALVADOR: Bacardí Tultitlán, México. Mies van der Rohe
  
  Author: LIZÁRRAGA SÁNCHEZ, SALVADOR
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE
  Department: Department of History and Theory of Architecture and Communication Techniques (THATC)
  Mode: Normal
  Deposit date: 03/03/2025
  Reading date: 11/04/2025
  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: GARCIA ESTEVEZ, CAROLINA BEATRIZ | ROVIRA GIMENO, JOSE MARIA
  Thesis abstract: This thesis focuses on the office building for Bacardí y Cía S. A. in Tultitlán, Mexico, which Mies van der Rohe and his team designed and built from 1958 to 1961. Several Mexican companies – Knoll Internacional de México S. A., Constructora Maya, Campos hermanos and SACMAG de México– were involved in the process. For its construction, Mies’ architects –Gene Summers, Jan Lippert and Friedrich Wagner– made dozens of trips from Chicago to Tultitlán, while Mies visited Mexico only once. The thesis has two main objects of study. The first is the archive of the building, which contains about a thousand documents related to the Mexican building stored in the Mies van der Rohe archive at MoMA –hundreds of letters, telegrams, photographs, sketches and plans. The second is the architecture itself, whose peculiar materiality is contrasted with the information in the archive.The Tultitlán building is placed on the margins of the history of Mexican architecture, of Mies' history and, therefore, of Western architectural history. However, by extracting the object from that marginal position and forcing it to take a central position, it drags with it an entire architectural culture and forces the hegemonic discourses of those histories to reconstruct themselves, or at least to be questioned. The unprejudiced dissection of the archive and its building puts to the test historian Manfredo Tafuri's dictum that positioning oneself at “a particular angle of observation allows facts mute in themselves to be forced to become eloquent.” Among others, the archive forces us to place ourselves in the particular angle of vision of its secondary characters in order to understand them as principal and eloquent; from the foreshortening of a marginal city for the history of Western architecture that shows us that it became actually an international center; in the standpoint of a technological and constructive reality that allowed the materialization of a Mies building, but with methods different from those of a rich country; among many others. The research does not hide an inevitable conflict between the “historical word” of our present and that of the documents of another era -because the letters, plans, publications and films used in this research were created in a reality that no longer exists-. In other words, on the one hand, the documents were forced to speak in a language unknown to them –ours– and, at the same time, they were allowed to speak freely, without trying to hide their contradictions for the sake of a supposed historical or scientific congruence acceptable for the present. The collision of times forced to seek support in other languages, disciplines and characters –from Florence Schust Knoll and Lina Bo, to popular office cinema– to make intelligible the transnational context that allowed the existence of the objects of study of this thesis: the archive of the Bacardi offices in Tultitlán and its architecture.
  

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

• GORDILLO BEL, DIDAC: De la caponera al búnquer. Evolució de la fortificació des de mitjans del segle XIX a mitjans del segle XX a Catalunya.
  
  Author: GORDILLO BEL, DIDAC
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL, CIVIL AND URBAN HERITAGE AND REFURBISHMENT OF EXISTING BUILDINGS
  Department: Departamento de Representación Arquitectónica (RA)
  Mode: Normal
  Deposit date: 28/03/2025
  Deposit END date: 10/04/2025
  Thesis director: ONECHA PEREZ, ANA BELEN | SÁNCHEZ RIERA, ALBERTO
  Thesis abstract: The thesis is composed, apart from the general introduction, of four interconnected chapters but which could be independent. The first is an overview of the evolution of fortification from antiquity to the middle of the 20th century. The second is the development of fortification in defensive enclosures since the middle of the 19th century, taking into account the curtains and bastions that gradually became low until they became covered caponiers, bastions that in principle are small forts that are part of a set but which could be independent in isolated forts, with crenellated galleries, embrasures with artillery pieces or plans protected only by parapets to place cannons to fire uncovered, and at the back of everything the tower divided into floors where the slingshots are located with the pieces to shoot at a long distance, both in slingshots under cover and pieces located on parapet at the highest point. Tortosa is taken as an excuse, because its case can be extrapolated to others in Catalonia. The fourth part is the realization of the bunker figure. There are enough cases here because unfortunately Catalonia, like the rest of the State, suffered a civil war. In this part, you can see how the bunkers were foreseen and how they gradually materialized with normalizing models that already came from before. Finally, the last part is the concrete explanation of the evolution of the bunker caponera and how it has become more and more camouflaged and more armored as the destructive power of the weaponry increases, how the traditional fortification has disappeared .
  

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

• PULESTON, THOMAS PAUL: Monitoring and optimal operation of vanadium redox flow batteries
  
  Author: PULESTON, THOMAS PAUL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Department of Automatic Control (ESAII)
  Mode: Normal
  Deposit date: 01/04/2025
  Deposit END date: 14/04/2025
  Thesis director: SERRA PRAT, MARIA | COSTA CASTELLO, RAMON
  Thesis abstract: The rapid transition to a sustainable energy paradigm demands efficient and cost-effective energy storage systems to manage the inherent intermittency and unpredictability of renewable energy sources. Redox flow batteries appear as a promising option for large scale stationary applications, given their versatility, safety, and the possibility to scale energy and power independently. Among them, All-Vanadium Redox Flow Batteries (VFBs) have garnered the most interest, standing out for the long service life that stems from employing a single active element. Despite their potential, VFBs still face some challenges that limit their widespread implementation. This thesis tackles two of these major challenges. The first is electrolyte imbalance, a discrepancy of active species concentrations between the two sides of the system, which represents the primary cause of capacity loss. To address it, a comprehensive study is conducted on how battery capacity depends on various sources of imbalance and their interactions, culminating in a systematic procedure for recovering the capacity of imbalanced VFBs. The second challenge is the lack of direct methods for determining key system variables, such as vanadium species concentrations, the state of charge, state of health, and internal parameters. To overcome this issue this thesis develops advanced nonlinear estimation strategies, which reconstruct variables of interest using only easily measurable signals, thus providing a practical alternative to costly or complex sensor setups. Finally, the aforementioned estimation and imbalance management proposals are effectively integrated into a cohesive operational strategy, developing a control framework to optimise performance, prevent unsafe conditions, and maximise capacity.By addressing these critical challenges, this work delivers practical, cost-effective solutions that enhance VFB monitoring, capacity recovery, and overall operation. These advancements contribute to expanding the capabilities of the VFB technology, fostering broader integration within sustainable energy systems.
  

DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING

• AGRELO LESTÓN, ASIER: Development of metal-enhanced TiO2-based photocatalysts for hydrogen production
  
  Author: AGRELO LESTÓN, ASIER
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 02/04/2025
  Deposit END date: 15/04/2025
  Thesis director: LLORCA PIQUE, JORDI | SOLER TURU, LLUIS
  Thesis abstract: Human activity has led to rising greenhouse gas levels, altering climate patterns and intensifying weather events. Therefore, a transition to a decarbonized energy system is needed, with hydrogen as a promising energy vector alongside solar and wind energy. However, current hydrogen production methods, such as steam methane reforming, generate significant CO2 emissions. Sunlight-driven water splitting offers a sustainable alternative, though efficiency improvements are required for industrial viability.This PhD thesis focuses on developing novel TiO₂-based catalysts for photocatalytic hydrogen production.Chapter 3 was conducted with the SYMAC team from Université Toulouse 3-Paul Sabatier. A TiO₂ catalyst was decorated with Cu nanoparticles stabilized by quinidine and compared to a sample prepared via incipient wetness impregnation (IWI) using L-ascorbic acid. The quinidine-stabilized sample exhibited 5 times superior activity under UV, as well as activity enhancement under Uv-visible irradiation. UV-vis spectroscopy revealed a plasmonic band relative to Cu, and a decrease in the bandgap was confirmed by Tauc plots. XRD confirmed Cu deposition and predominant anatase phase of the TiO2. TEM confirmed presence of Cu nanoparticles that XAS and XPS identified predominant metallic nature with minor oxide contributions.Chapter 4 was carried out with the Supra- and Nanostructured Systems group at Universitat de Barcelona (UB). Hybrid TiO₂ photocatalysts were prepared with Au(I) complexes and Au(0) systems were developed as co-catalysts. Three catalyst series incorporating coumarin-based ligands were evaluated under light and heat. Two (1 wt.% co-catalyst) were prepared via IWI and ball milling (BM), while a third (0.25 wt.% Au) was synthesized by IWI. IWI-prepared samples showed superior activity, achieving up to 2.7 times the H₂ production of conventional Au/TiO₂. UV-vis spectroscopy confirmed plasmonic bands relatives to Au and Tauc plots revealed bandgap narrowing. TEM, HAADF-STEM, and XPS confirmed the presence of Au nanoparticles with a predominant metallic nature.Chapter 5 focused on Pt/TiO₂ photocatalysts synthesized by BM, optimized through a design of experiments (DoE) approach. The most active sample was 1.4 times more efficient than an IWI-prepared Pt/TiO2 reference under UV light irradiation. HAADF-STEM-EDX revealed Pt atoms dispersed on TiO₂, with post-reaction growth into nanoparticles while there was presence of some Pt atoms dispersed. XPS confirmed partial Pt reduction during the reaction.Chapter 6 explored bimetallic PdCu photocatalysts with a total metal loading of 1 wt.%. A Pd:Cu atomic ratio of 1:2 was chosen after a screening from 3:1 to 1:3. The bimetallic sample outperformed theoretical activity of the combination of thus metals under UV light by 27%, and Cu incorporation enhanced H₂ production under UV-vis irradiation. BM-prepared samples were 1.2 times more active than IWI ones. Pd stability was improved with Cu incorporation, as seen in long-term tests, with less activity loss compared to monometallic Pd. Raman spectroscopy indicated strong metal-support interactions. UV-vis spectroscopy and Tauc plots showed enhanced visible absorption and bandgap narrowing, respectively. HAADF-STEM-EDX revealed bimetallic PdCu nanoparticles in BM samples, whereas IWI samples had separate Pd and Cu nanoparticles. BM also constrained Pd growth, as Pd nanoparticles in the monometallic sample grew 3.5 times during the reaction. XPS showed Pd reduction in both samples, with complete reduction in BM-prepared catalysts, further supported by H₂-TPR.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• FERNANDEZ, MARIANO TOMAS: Numerical techniques for the solution of thermal problems in the context of geophysical inversions
  
  Author: FERNANDEZ, MARIANO TOMAS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Normal
  Deposit date: 01/04/2025
  Deposit END date: 14/04/2025
  Thesis director: DIEZ MEJIA, PEDRO | ZLOTNIK MARTINEZ, SERGIO
  Thesis abstract: The thermal structure of the Earth’s interior contains key information for the understanding of geodynamic processes, including plate tectonics, mantle convection, and the Earth’s overall thermal evolution. In particular, it is relevant to describe the geometry of the Lithosphere-Asthenosphere Boundary (LAB), separating the rigid Lithosphere from the ductile Asthenosphere. Accurately characterising this interface is key for the understanding of the thermal and mechanical structure of the Earth. Most models used in practice involve a formulation that is not physically sound, at least, in some part of the domain. These models involve smearing out regions or empirical estimations that do not fulfil the energy equilibrium equations. These estimates are useful in practice, but a formulation that respects physical principles would be preferable. This thesis focuses on developing forward solvers that allow for the computation of physically sound temperature fields within an inversion problem. The structure of the forward problem is altered by imposing the location of the LAB on the interior of the domain. The mathematical statement of this problem is presented in two versions and numerical methods to obtain solutions are developed and tested. The first solver enforces the isotherm condition by splitting the domain into Lithosphere and Asthenosphere, such that the LAB is a boundary to both, and explicitly adds equations to impose the condition. The second solver finds a mantle velocity field that enforces the isotherm condition indirectly. While the first solver needs to restore flux continuity by adding conditions, the second needs a velocity field that complies with the isotherm condition, both providing valuable information to improve geophysical understanding. The methodologies are tested across different scenarios and LAB geometries, using synthetic and non-synthetic temperatures to assess their performance in geophysical inversions. Results demonstrate that the domain-splitting solver reliably and efficiently recovers the LAB geometry, making it suitable for large-scale applications. The second solver, although computationally expensive and sensitive to parameter choices, also constitutes a robust solver. This thesis contributes to advance in the geophysics field by providing robust tools for thermal modelling. The tools have the potential to improve our understanding by solving partial differential equations providing insights into the thermal and mechanical properties of the Earth.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• ARÉVALO SOLER, JOSEP: Control of a grid of multiple AC and DC sub-systems interconnected with power converters
  
  Author: ARÉVALO SOLER, JOSEP
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 28/03/2025
  Deposit END date: 10/04/2025
  Thesis director: GOMIS BELLMUNT, ORIOL | PRIETO ARAUJO, EDUARDO
  Thesis abstract: High Voltage Direct Current (HVDC) offers clear advantages for long distance electrical transmission. This is why its implementation is rising in the interconnection of remote renewable energy and interconnection between islanded Alternating Current (AC) grids, as is the case in Europe. The majority of these systems are currently developed as point-to-point systems. However, Multiterminal High Voltage Direct Current (MT-HVDC) systems will be built shortly. The critical elements in these systems are the Interconnecting Power Converters (IPCs) that enable the transformation between AC and DC. These converters mainly use the Modular Multilevel Converter (MMC) technology, which can be controlled by leveraging the energy stored inside its cells to achieve its control objectives.The control strategy of these converters is diverse, and different control objectives can be implemented. Two subgroups exist: grid-forming (GFM) and grid-following (GFL) strategies. The main aim of the first one is to form the grid (AC and/or DC), while the second assumes a stable grid (AC and/or DC) with which to interchange power. The control strategy applied to be grid-forming or grid-following is not unique, and different control architectures are already proposed in the literature. Thus, studying the effect of combining these control architectures on the same system’s stability and performance is crucial.The main objective is to solve the question of how to properly assign and combine these roles in the emerging MT-HVDC grids to ensure stability and proper system response.Firstly, the stability of point-to-point links is studied. This includes a study on the interaction between AC and DC sides when AC-GFM and AC-GFL converters are in the same point-to-point link. It is seen how the different levels of energy buffering capability affect the level of interactions between AC and DC sides. Then, the extension of point-to-point links to MT-HVDC systems is studied. A crucial role in this case is the DC-GFM control. Thus, the stability of HVDC systems is studied when two different DC-GFM control strategies are applied.Secondly, MT-HVDC systems are studied. These systems introduce additional complexities. A key challenge in these systems is the optimal assignment of control roles to IPCs. One of the studies presents a novel methodology to optimize the control role assignment of IPCs by considering both small-signal stability and control performance. This methodology accounts for multiple power flow scenarios and analyzes the steady-state deviations and small-signal stability following selected events. The results of this study highlight the importance of control role assignment in enhancing system stability and performance.From the results extracted from the previously mentioned study, a dynamic control role assignment is proposed to solve the problems previously identified. Traditionally, the control role of IPCs has been static, with little consideration given to dynamically changing the control mode of these converters in real-time operations. However, this study advocates for a dynamic approach to IPC control role assignment, suggesting that allowing transmission system operators to adjust the control roles in response to varying conditions can lead to improved system performance, enhanced stability, and greater operational flexibility.Finally, the research also addresses the advantages of dual-port GFM control in hybrid AC/DC systems. Unlike traditional GFM and GFL controls, which must be carefully assigned to individual IPC terminals, dual-port GFM control imposes a stable voltage on both AC and DC terminals, making it suitable for deployment across all IPCs regardless of network configuration. The findings of this study indicate that dual-port GFM control offers several significant benefits, making it a promising solution for enhancing HVDC systems’ stability and dynamic performance.
  
• SALDAÑA GONZÁLEZ, ANTONIO EMMANUEL: Supervised Learning for Optimal Investment Planning in Active Distribution Networks
  
  Author: SALDAÑA GONZÁLEZ, ANTONIO EMMANUEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 28/03/2025
  Deposit END date: 10/04/2025
  Thesis director: SUMPER, ANDREAS | ARAGÜÉS PEÑALBA, MÒNICA
  Thesis abstract: Due to the exponential growth of electric vehicles and distributed generation in distribution networks, potential congestion in power lines, transformers, and voltage deviations is expected to increase in the coming years. For this reason, the development of modern distribution planning strategies to strengthen grid infrastructure needs to be studied, considering its dynamics and impacts.This thesis proposes a simulation-based optimization model for active distribution network expansion, capturing nonlinear complexities through AC power flows, voltage stability, and operational constraints. The formulation includes an objective function, constraints, and both traditional and flexible planning actions, focusing on determining the optimal battery power and capacity over projected horizons to defer infrastructure investments.Additionally, this thesis reviews and compares smart grid measurement devices based on their technical specifications and potential applications in distribution network operation and planning. A recurrent neural network model is also presented for medium- and long-term load forecasting using historical consumption data from medium-voltage (MV) transformer stations. This forecasting model was later integrated with an investment planning model to compare passive and flexible reinforcement actions in a real case study in Spain.Finally, supervised learning models (Random Forest, XGBoost, LSTM, and SVM) were trained using the proposed optimization model to predict and minimize investment costs, thereby identifying the most effective approach for DSO planning applications. This methodology was tested on a CINELDI network under various electric vehicle charging expansion scenarios and is intended for use in connection request applications.
  

DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING

• ÁLVAREZ GONZÁLEZ, ANA: BIOFERTILIZERS AND BIOSTIMULANTS FROM MICROALGAE GROWN IN WASTEWATER Characterization and Agronomic Trials
  
  Author: ÁLVAREZ GONZÁLEZ, ANA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 01/04/2025
  Deposit END date: 14/04/2025
  Thesis director: UGGETTI, ENRICA
  Thesis abstract: Chemical fertilizers have played a crucial role in modern agriculture, enabling high productivity rates to meet the demands of a rapidly growing global population. However, it is now evident that its overuse poses significant environmental risks. Biofertilizers have emerged as a promising alternative. Microalgae are photosynthetic microorganisms that show great potential as biofertilizers. They can survive in diverse environments, including wastewater. Using microalgae in wastewater treatment not only produces treated water suitable for reuse, but also generates microalgal biomass that can be converted in valuable bioproducts, including biofertilizers. Moreover, microalgae can produce compounds that function as biostimulants. This doctoral thesis aims to contribute to sustainable agriculture by developing biofertilizers and biostimulants derived from microalgae cultivated in wastewater. The research demonstrates that microalgae can act as an environmentally friendly, effective, and safe alternative to chemical fertilization. First, a microalgal biomass was grown using urban wastewater in 470L High Rate Algal Pond (HRAP) and analyzed in order to study its safety. The nutrient content was: 7.6% N, 1.6% P, and 0.9% K. The biomass did not present pathogens and the content of heavy metals was below the threshold established by the Regulation (EU) 2019/1009. Out of 29 organic compounds analyzed in wastewater and only 3 of them (caffeine, hydroxycinnamic acid, and bisphenol A) were found in the biomass. Then, the efficacy of the biomass as a biofertilizer was studied in two agronomic trials, in a greenhouse, using basil and lettuce plants. These experiments concluded that the best results were obtained by mixing the biomass with the chemical fertilizer, which allowed to reduce the dose of fertilizer by 50%. Then, a novel biofertilizer was also developed by encapsulating microalgae in an organic matrix (polylactic acid) using nanotechnology, in order to make slower the release of nutrients. A nutrient release experiment was performed and the results showed that the encapsulation successfully reduced the nutrient release rate. A life cycle and economic analysis were performed comparing lettuce production using microalgae biofertilizers with inorganic fertilizer. The life cycle assessment revealed that the production of lettuce with the microalgal biomass produced in a wastewater treatment plant has less impact in 10 out of 11 impact categories than the production of lettuce with inorganic fertilizer (ammonium nitrate in this case). The biofertilizer was cost-competitive, being potentially 30% cheaper than inorganic fertilizers. Finally, the microalgal biomass was also studied as a source of biostimulants compounds. Three microalgal strains (Scenedesmus sp., Synechocystis sp., and Phormidium sp.) were grown in wastewater using closed photobioreactos of 2.5L. The results showed that the three strains produced similar phytohormones profile, with indole-3-acetic acid (IAA) being the most abundant. The three strains produced a higher concentration of proteins than carbohydrates. Scenedesmus sp was then grown in the 470L HRAP using wastewater. This biomass presented a high concentration of phytohormones, in particular cytokinins (TZ, 21 mg/gDW) and auxins (IAA, 7 mg/gDW). The microalgal extracts were applied to 35-days-old lettuce plants, some of which were subjected to draught stress. The results showed no significant differences for stressed plants. Plant growth was also compared to a control group that received tap water instead of the microalgal extract. In this case, fresh weight increased by 12–13% when microalgae extracts were applied.
  

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

• VIDAL MONTES, RUBÉN: Thermo-Hydro-Mechanical-Chemical Impacts of High-Temperature Aquifer Thermal Energy Storage
  
  Author: VIDAL MONTES, RUBÉN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 01/04/2025
  Deposit END date: 14/04/2025
  Thesis director: OLIVELLA PASTALLE, SEBASTIAN | SAALTINK, MAARTEN WILLEM
  Thesis abstract: High Temperature Aquifer Thermal Energy Storage (HT-ATES) involves the injection and extraction of non-isothermal fluids into aquifers and triggers thermo-hydro-mechanical-chemical processes. These processes must be analysed and understood for obtaining safe and efficient HT-ATES systems. This thesis aims to deepen the understanding of these processes, provide methods and solutions that can be easily and straghtforwardly implemented, for assessing the impact and feasibility of these systems and iii) forecast the system's long-term performance.First, the coupled thermo-hydro-mechanical finite (THM) element code CODE_BRIGHT has been verified against several tests of a benchmark for thermo-hydraulic processes (TH) in geothermal situations. This code has been used in the development of other methods of the thesis. It has been showed that CODE_BRIGHT is competent in performing all these tests.Second, a method that can be used to develop analytical and semi-analytical solutions for calculating reaction rates for non-isothermal cases has been developed. The method assumes that aqueous and mineral reactions are in equilibrium. The chemistry has been decoupled from the TH processes. In the chemical part of the method, batch calculations are performed to obtain dissolution or precipitation of minerals and water chemistry changes due to temperature variations. The TH part consists of calculating temperature and spatial and temporal derivatives of temperature. From this, one can easily calculate both the chemical composition of groundwater and the rates of mineral precipitation or dissolution. The method facilitates comprehension of the dominant reactive transport processes, mineral reaction rates and porosity changes. The application of this method for simulating a HT-ATES system resulted in a reduction of computational costs by a factor of seven compared to a conventional coupled thermo-hydro-chemical numerical code.Third, a dimensional and numerical analysis of the THM behaviour of a pilot HT-ATES system has been proposed. Three dimensionless numbers that could be easily implemented have been obtained: Peclet number and two numbers for the hydraulic and thermal strains. The Peclet number, which has been decomposed in conductive and dispersive terms, is useful to identify the dominant TH flux (advection, dispersion or conduction). Hydraulic and thermal strains numbers relate the strain generated by changes of hydraulic head and temperature, respectively, with respect the initial total strain of the system. This study's findings have revealed information about the main TH fluxes and their domain areas, evolution of the energy efficiency of the system over time and the role of the hydraulic and thermal loads generated by the injection and extraction of hot water in the vertical displacement of the terrain. The study has provided information about the behaviour and efficiency of the system to long term operation.Finally, an analytical solution for calculating ground surface uplift due to point non-isothermal injections which takes into account thermal and hydraulic head changes has been presented. The main advantage of this solution is its easy implementation in a superfast way, in terms of computational cost, in comparison to a standard thermo-hydro-mechanical code. This solution has been verified satisfactorily against results from a coupled THM numerical model and field data (levelling and PS-INSAR) in a leakage case in a geothermal power plant. The results have demonstrated the contribution of hydraulic head and temperature to ground surface displacements and have facilitated an understanding of the effect of the natural geothermal gradient. The solution is useful for forecasting ground displacement resulting from point injections and extractions under various conditions and time scales.
  
• ZHANG, SHENG: Study on rock fragmentation mechanism and ball loading parameter matching in ball mill
  
  Author: ZHANG, SHENG
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 28/03/2025
  Deposit END date: 10/04/2025
  Thesis director: RODRIGUEZ DONO, ALFONSO
  Thesis abstract: AbstractRock fragmentation in ball mills is a key topic in rock mechanics with broad scientific and engineering significance. However, the understanding of the mechanical mechanisms and ball loading optimization based on dynamic and static principles is still incomplete. The dynamic changes in both rock and ball sizes during milling add complexity, while the process involves multiple breakage mechanisms, including abrasion, compression, and impact. This study examines rock fragmentation characteristics and mechanisms under these three types of forces.(1) The indentation of spherical indenter on rock was studied through laboratory experiments and CODE_BRIGHT numerical simulations, revealing the transition of rock failure from a " jump-type " to a plastic deformation mode under the influence of indenter size. The mechanical mechanisms of rock fragmentation during spherical indentation were analyzed in terms of fracture characteristics and stress fields. (2) The fragmentation characteristics of rock under the impact of spherical indenters of varying sizes were analyzed, and an energy model for indenter impact fragmentation based on fractal theory was established. The mechanical mechanism of spherical indenter-induced fragmentation was explained from a mechanical perspective.(3) The stage-wise variation of the multi-fractal characteristics of ball milling particle size under the influence of rock abrasiveness was analyzed. Based on abrasiveness tests and PFC2D numerical simulations, the wear characteristics and evolution patterns of steel balls in the ball milling process were quantitatively described.Subsequently, a ball charge parameter calculation method was proposed based on the energy consumption laws of spherical indentation impact and compression. Building on this, a ball replenishment strategy based on Markov chain theory was developed and validated through laboratory case studies.
  

DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING

• RABOST GARCIA, GENÍS: Microfluidics for sweat monitoring
  
  Author: RABOST GARCIA, GENÍS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING
  Department: Department of Mechanical Engineering (EM)
  Mode: Normal
  Deposit date: 28/03/2025
  Deposit END date: 10/04/2025
  Thesis director: CASALS TERRE, JASMINA | FARRÉ LLADÓS, JOSEP
  Thesis abstract: This thesis began with the goal of revolutionizing continuous monitoring through the use of sweat. Over the course of this research, the field of sweat monitoring has evolved significantly, being consolidated as the most convenient non-invasive alternative to blood analysis. This thesis compiled the knowledge acquired during these years across different areas related to the design of a microfluidic sweat platform.Initially, a perspiration model was developed as an in vitro experimental setup to enable realistic and cost-effective testing of microfluidic sweat platforms. Sweat gland dimensions and structure were replicated using on-plane soft lithography, solving the fabrication challenges associated. A functional prototype was successfully operated with appropriate skin surface characteristics, demonstrating its use with adhered microfluidic devices. A microfluidic platform integrating custom electrochemical sensors was developed for the measurement of sweat volume, sweat conductivity and sweat lactate. Continuous monitoring has been proven for extended periods of time (exceeding 1 hour) with robustness and reproducibility. This system was incorporated into a complete wearable device featuring remote communication and embedded computation, becoming a novel tool for sports monitoring. The device was validated in on-body trials to assess the accuracy of the output parameters to the final user, for both sweat-based variables (sweat loss, sodium and sodium loss) and blood bioequivalence predictions (lactate).Additionally, a novel microfluidic design for the chrono-sampling of sweat was explored in vitro. It combines a passive valve and pump to renovate the volume in a sensing chamber in a cyclic manner. The mismatch between the absorption rate of the passive pump and the sweat generation at the inlet was found to disconnect the fluid, restoring the passive valve function once surpassed. The system's characteristics can be adjusted to different requirements by modifying the valve widths or passive pump properties. However, the fabrication of this design requires high resolution, which can limit throughput and complicating the current large human testing involved in a microfluidic sweat platform. Therefore, new materials and fabrication techniques at the laboratory were explored to reduce the design to test time and enhance production capacity. In summary, the initial vision of a novel microfluidic sweat wearable platform capable of providing non-invasive, real-time measurements of a variety of biomarkers has been accomplished. Moreover, several promising research lines have emerged, including advancements in perspiration models, microfluidic design, fabrication scalability and algorithm development. Finally, this research has led to the development of a commercially available product, demonstrating that continuous monitoring through sweat is now a market-ready technology.
  

DOCTORAL DEGREE IN PHOTONICS

• HEITHOFF, MAXIMILIAN: Exciton engineering for quantum confinement in an electrostatically defined PN-junction
  
  Author: HEITHOFF, MAXIMILIAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 26/03/2025
  Deposit END date: 08/04/2025
  Thesis director: KOPPENS, FRANK | RESERBAT-PLANTEY, ANTOINE
  Thesis abstract: We investigate the physics of quantum-confined excitons in an electrostatically defined PN junction. Such a PN junction can be generated in an encapsulated monolayer \MoSe{} along the patterned edge of a top-gate electrode. Applying a voltage gradient between the top and bottom gates results in the formation of an in-plane electric-field gradient in the depletion region and strong doping gradients in the P- and N-doped regions of the PN junction. The exciton experiences an attractive force within the electric field gradient and repulsion from exciton-charge carrier interactions. The combined effects are sufficiently strong to quantize the number of available excitonic states within the potential. We show measurements of these quantum-confined excitons in reflection contrast and photoluminescence spectroscopy. We demonstrate how the confinement potential results in fine structure splitting with linearly polarized excitonic states that are aligned either along or perpendicular to the top gate edge. The states can be gradually tuned between linear and circular polarization using an out-of-plane magnetic field. Our particular sample geometry, where the formation of the PN junction electrically isolates the sample from ground, allows us to investigate the electrostatic model of a photo-biased PN junction, with the bias voltage as an additional tuning parameter of the confinement potential. The bias voltage is modified by the measurement itself and varies with the location of the measurement. We demonstrate how the combined impact of exciton dissociation and Auger-assisted hot-hole tunneling modifies the bias voltage over a timescale up to $\qty{100}{\s}$. The bias voltage can be further controlled using a second laser, which enables the tuning of the energy of the quantized states over the range of $\qty{15}{\meV}$. Ultimately, these findings allow us to simulate the exact shape of the confinement potential and to investigate how the in-plane electric field modifies the internal exciton structure, impacting the exciton oscillator strength, lifetime, and dissociation. The results of this thesis illustrate the possibilities to pattern tailored exciton potential shapes for photonic and quantum technologies.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• PÉREZ PORTERO, ADRIÁN: Contributions to RFI detection, mitigation, and excision for GNSS receivers and spaceborne microwave radiometers
  
  Author: PÉREZ PORTERO, ADRIÁN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 24/03/2025
  Deposit END date: 04/04/2025
  Thesis director: CAMPS CARMONA, ADRIANO JOSE | PARK, HYUK
  Thesis abstract: Radio Frequency Interference (RFI) poses significant challenges to remote sensing systems, particularly affecting Global Navigation Satellite System-Reflectometry (GNSS-R) and microwave radiometry. This thesis advances two interconnected areas of remote sensing: geophysical parameter retrieval using signals of opportunity and RFI impact assessment on Position, Navigation, and Timing (PNT) systems. The research develops novel approaches for RFI detection, mitigation, and excision across multiple remote sensing platforms, with particular emphasis on space-qualified systems.The first part of this work advances GNSS-R instrumentation through the development of an experimental testbed and simulator. Laboratory measurements in controlled environments provided critical insights into GNSS-R signal characteristics, enabling systematic validation of signal processing algorithms. The research demonstrates the feasibility of continuous Earth observation through opportunistic platforms, specifically integrating GNSS-R instruments in commercial aviation for applications including weather nowcasting and maritime route optimization. Analysis of polarimetric data revealed significant limitations in current receiver architectures, particularly in processing Left-Hand Circular Polarization (LHCP) signals and reconstructing Stokes parameters. This continued with work conducted at JPL in 2023, analyzing data from the SMAP-R mission which modified its radar payload for GNSS-R reception. The dual capability for forward and backward scattering measurements from the same platform enabled comparative analysis of scattering mechanisms. Leveraging SMAP-R's fully polarimetric reflectometry measurements, we investigated bistatic radar scattering characteristics across varied surface conditions. The analysis focused on two aspects: comparing scattering regime behaviors across different terrains, and developing a prediction model that derives backward-scattering characteristics from forward-scattering measurements. This work extends the theoretical understanding of bistatic scattering mechanisms while providing validation through spaceborne measurements.The second part addresses RFI challenges through three complementary approaches: spectrum monitoring systems, hardware-efficient algorithms, and polarimetric detection methods. A key contribution is the development of an automatic RFI Detection, Location, and Classification (RFIDLC) system for GNSS bands, utilizing a six-sector antenna array design for real-time processing between 1525 and 1625 MHz. For Synthetic Aperture Radar (SAR) applications, novel algorithms operating on 1-bit quantized signals enabled RFI mitigation despite severe quantization effects. The FPGA implementation achieved significant resource reduction through innovative overclocking and serialization techniques while maintaining space qualification requirements.A major advancement is the development of the Polarimetric Kurtosis detector for microwave radiometry, extending conventional kurtosis-based detection to the full-polarimetric domain through a four-dimensional measurement derived from Stokes parameters. This technique demonstrates enhanced sensitivity to polarized interference signals, particularly in scenarios where conventional detection methods show limitations. The research validates these approaches through experimental testing on both ground-based and spaceborne platforms, establishing a foundation for future RFI mitigation systems in space-based Earth observation missions.
  
• ROIG MARÍ, CARLOS: Instance-level Recognition for Image Understanding
  
  Author: ROIG MARÍ, CARLOS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 01/04/2025
  Deposit END date: 14/04/2025
  Thesis director: MARQUES ACOSTA, FERNANDO | VARAS GONZÁLEZ, DAVID
  Thesis abstract: Image understanding is a fundamental task in computer vision as it aims to enable machines to visually comprehend the real world. In this thesis, the task of image understanding is addressed through the combination of instance-level recognition systems and Large Multimodal Models (LMMs). To do so, the thesis is structured in three parts, starting with a study of deep metric learning techniques for creating rich image embeddings spaces. Then, the implementation of instance-level recognition systems specifically focused on landmark recognition using content-based image retrieval. And finally, enhance the capabilities of LMMs by incorporating instance-level recognition results in order to generate improved image descriptions with instances. The first part of this thesis focuses on advancing deep metric learning methods. A novel Smooth Proxy-Anchor Loss is proposed to address the problem of having noisy labels in training data. The proposed loss introduces confidence-based sample weighting, soft proxy assignment, and adaptive margins to mitigate the negative impact of mislabeled samples, demonstrating superior performance on real-world data. Building on top of this foundation, the thesis extends the selective weighting of samples to a selective weighting of features, through the Generalized Local Attention Pooling (GLAP) method. GLAP dynamically weights different regions of feature maps according to their informational content, enabling better representation learning while reducing computational requirements. Evaluations on multiple benchmark datasets show the significant improvements of using GLAP over state-of-the-art approaches.The second part introduces the Multi-Scale Transformer-based Feature Combination (MSTFC) method for instance-level landmark recognition. This approach applies a transformer-based attention mechanisms to select and combine relevant information from feature maps. These feature maps are extracted from multiple scales and have different spatial resolutions. The combination of these multi-scale feature maps results in a compact global representation that is used for image retrieval. The MSTFC method achieves a superior performance on the challenging landmark retrieval datasets, outperforming existing approaches on the Google Landmarks Dataset v2 and the Revisiting Oxford and Paris benchmarks.Finally, the thesis explores the enhancement of Large Multimodal Models by incorporating instance-level recognition results to generate more accurate and detailed image descriptions. By bridging specialized instance-level recognition systems with the generic understanding capabilities of LMMs, this integration demonstrates how domain-specific computer vision techniques can be combined with multimodal techniques for comprehensive image understanding.Through these contributions, the thesis advances the field of image understanding across multiple levels, from robust feature learning in real-world noisy dataset, to effective techniques for combining the information of feature maps in deep metric learning, then expanded to multi-scale representation for instance-level recognition, and ultimately to the integration of specialized instance-level systems with modern multimodal frameworks.
  
• SARMIENTO CALDERÓ, MANUEL: Contextualization of Spatio-temporal Action Localization Systems and Media Content Applications
  
  Author: SARMIENTO CALDERÓ, MANUEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 02/04/2025
  Deposit END date: 15/04/2025
  Thesis director: MARQUES ACOSTA, FERNANDO | VARAS GONZÁLEZ, DAVID
  Thesis abstract: Spatio-temporal action localization is a field of computer vision that determines both the spatial and temporal locations of actions taking place within a video. This particular task is one of the cornerstones of video understanding due to its inherent complexity. Impressive scientific advances in the artificial intelligence and computer vision industry have led to a significant performance increase.Nevertheless, even state of the art systems struggle to recognize actions that involve some kind of interaction between people, objects, or with the scene. This limitation arises because current spatio-temporal action localization models neglect contextual information when identifying a person's actions. Specifically incorporating contextual cues in these models can help to address this challenge. Furthermore, the integration of spatio-temporal action localization systems into multimedia content applications presents several challenges. The primary difficulties lies in finding ethical and practical use cases and addressing the computational requirements to run these models in production.The goal of this industrial PhD is to solve the above problems. The lack of contextual information is addressed in different forms. This thesis, is focussed on two different approaches. First, a novel system to explicitly model the relations of the different actors and objects in a scene, which includes a novel structure to model long-term temporal information is proposed. Second, an innovative multi-modal method to combine task specific features to improve action recognition is introduced. These developed contextualization systems are evaluated on different datasets. The results demonstrate the effectiveness of the proposed systems. Regarding the applications, this PhD is focused on finding, implementing and exploiting specific applications of spatio-temporal localization system for media content. The developed applications consists of an improved system for search and recommendations on video content, an smart cropping method to generate image and videos of any desired aspect ratio from another video, and the improvement of a system to generate highlight keyframes of football matches.
  
• WOODWARD RIQUELME, ALEJANDRO BENJAMÍN: Contextual Speech Recognition
  
  Author: WOODWARD RIQUELME, ALEJANDRO BENJAMÍN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 02/04/2025
  Deposit END date: 15/04/2025
  Thesis director: MARQUES ACOSTA, FERNANDO | VARAS GONZÁLEZ, DAVID
  Thesis abstract: Although Automatic Speech Recognition (ASR) technology has achieved remarkable improvements in transcription accuracy in recent years, it still struggles to correctly transcribe certain words. In particular, proper nouns often exhibit lower accuracy due to their unique pronunciations and alternative spellings. To address these challenges, contextualisation is commonly integrated into ASR models to improve the transcription of rare proper nouns and disambiguate between similar-sounding proper nouns.This industrial PhD thesis focuses on the development of contextualisation systems for ASR models. The ASR technology employed in this thesis is used to generate automatic transcripts for podcast content. The objective of the contextualisation system is to improve the accuracy of proper nouns; for example, the names of podcast shows, hosts, and guests.The contextualisation system developed in this thesis is composed of two parts. First, an ingestion pipeline gathers proper nouns relevant to the podcast episode to be transcribed. This pipeline has an automated component that extracts proper nouns from the metadata of each podcast episode, such as the title and description, using tools like a named entity recogniser. Additionally, a module that allows the manual addition of proper nouns to specific podcast shows has been developed. The second part, which represents the most relevant contribution of this thesis, is a novel ASR contextualisation algorithm based on deep neural networks. The contextualized ASR model utilises the gathered proper nouns, resulting in an improvement in accuracy when compared to the same model without contextualization capabilities.The accuracy of the ASR system developed in this thesis is evaluated and analysed using episodes from popular public podcast shows. A human evaluation of the word error rate was employed during this assessment.This evaluation compares the quality of the ASR model system's transcripts to those provided publicly by the podcast content creators. The results show that the system developed in this thesis produces transcripts that contain four times fewer errors than the transcripts offered by podcast hosting providers.The contextualization method is also evaluated on a public dataset and compared to state-of-the-art methods. The results show that the contextualization method proposed in this thesis significantly outperforms the existing systems.
  

DOCTORAL DEGREE IN STATISTICS AND OPERATIONS RESEARCH

• PACHÓN GARCIA, CRISTIAN: Contributions on dimensionality reduction and interpretable machine learning
  
  Author: PACHÓN GARCIA, CRISTIAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN STATISTICS AND OPERATIONS RESEARCH
  Department: Department of Statistics and Operations Research (EIO)
  Mode: Normal
  Deposit date: 28/03/2025
  Deposit END date: 10/04/2025
  Thesis director: DELICADO USEROS, PEDRO FRANCISCO
  Thesis abstract: This thesis is divided into two parts. The first one is devoted to dimensionality reduction for large data sets, while the second one focuses on the field of Interpretable Machine Learning. Part of the material presented in this thesis has been published either in journals or workshops. Concretely, the original work of Chapter 1 can be found in Delicado and Pachón-García (2024a). Regarding Chapter 3, the original publication is Pachón-García et al. (2024) and the material of Chapter 4 is Hernández-Pérez et al. (2024). Finally, Chapter 5 is intended to be sent to a journal, but Delicado and Pachón-García (2024b) is a preprint version.To begin with, we present a set of algorithms implementing multidimensional scaling (MDS) for large data sets. MDS is a family of dimensionality reduction techniques using a n×n distance matrix as input, where n is the number of individuals, and producing a low dimensional configuration: a n × r matrix with r << n. When n is large, MDS is unaffordable with classical MDS algorithms because their extremely large memory and time requirements. We compare six non-standard algorithms intended to overcome these difficulties. They are based on the central idea of partitioning the data set into small pieces, where classical MDS methods can work. Two of these algorithms are original proposals. In order to check the performance of the algorithms as well as to compare them, we have done a simulation study. In addition, an open-source R package implementing the algorithms has been created.Regarding the field of machine learning (ML), it is worth noting that its presence in our society is increasing, which brings with it the need to understand the behaviour of ML mechanisms, including machine learning predictive algorithms fed with tabular data, text, or images, among other types of data. Therefore, this thesis focuses on the problem of interpretability. On the one hand, we present SurvLIMEpy, an open-source Python package that implements the SurvLIME algorithm. This method allows to compute local feature importance for machine learning algorithms designed for modelling Survival Analysis data. The presented implementation uses a matrix-wise formulation, which allows to speed up the execution time. Additionally, SurvLIMEpy assists the user with visualisation tools to better understand the result of the algorithm. The package supports a wide variety of survival models, from the Cox Proportional Hazards Model to deep learning models such as DeepHit or DeepSurv. We study the ability of the algorithm to capture the importance of the features by means of a simulation study.With the goal of employing SurvLIMEpy, we train and compare three types of machine learning algorithms for Survival Analysis: Random Survival Forest, DeepSurv and DeepHit, using the SEER database to model cutaneous malignant melanoma. Our work underscores the importance of explainability methods for interpreting black-box models and provides insights into important features related to melanoma prognosis.On the other hand, we consider the field of Functional Data Analysis in order to provide it with interpretability tools. Designing interpretability methods for functional data models implies working with a set of features whose size is infinite. In the context of scalar on function regression, we propose an interpretability method based on the Shapley value for continuous games, a mathematical formulation that allows to fairly distribute a global payoff among a continuous set players. The method is illustrated through a set of experiments with simulated and real data sets. The open source Python package ShapleyFDA is also presented.
  

DOCTORAL DEGREE IN STRUCTURAL ANALYSIS

• TAHERZADEH FARD, ALIREZA: On the study of delamination and failure of composite materials under static and cyclic loads
  
  Author: TAHERZADEH FARD, ALIREZA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN STRUCTURAL ANALYSIS
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 01/04/2025
  Deposit END date: 14/04/2025
  Thesis director: BARBU, LUCIA GRATIELA | OÑATE IBAÑEZ DE NAVARRA, EUGENIO
  Thesis abstract: Composite materials, particularly fiber-reinforced polymers and fiber metal laminates have gained significant attention in industries such as aerospace, automotive, and marine engineering due to their high strength-to-weight ratio, excellent fatigue resistance, and corrosion durability. Despite these advantages, their structural performance is often limited by various damage mechanisms, including fiber failure, matrix cracking, and delamination. Among these, delamination is one of the most critical failure modes, as it can significantly compromise structural integrity. The accurate prediction and modeling of delamination and its interaction with other damage mechanisms remain a major challenge in the field of computational mechanics. This thesis aims to develop a robust constitutive model capable of predicting these failure mechanisms within a homogenized framework, enabling computationally efficient and physically realistic simulations.The research begins with an extensive evaluation of existing models for intra-laminar and inter-laminar damage mechanisms. Conventional modeling approaches, including stress-strength-based criteria, fracture mechanics methods, and cohesive zone models, are examined to determine their suitability for delamination damage prediction. By utilizing previously developed numerical frameworks within Kratos Multiphysics, the fundamental aspects of damage modeling are explored and benchmarked against experimental data. The key challenge addressed in this thesis is the integration of these theories into a homogenized computational approach, which eliminates the need for explicit layer-wise modeling while preserving accuracy in capturing damage initiation and propagation.To achieve this, a delamination homogenization theory is developed, allowing for the efficient representation of inter-laminar failure without the computational burden of explicitly modeling each interface. This framework is further extended to cyclic loading conditions, where fatigue-induced damage plays a crucial role in long-term structural degradation. The fatigue model incorporates a damage evolution law calibrated against experimental S-N curves, enabling the accurate prediction of crack growth rates (da/dN) under various loading conditions. The proposed methodology is validated through standardized benchmark test cases, demonstrating its capability in capturing both intra-laminar and inter-laminar damage progression.The applicability of the developed model is assessed through a series of component-level simulations to ensure its real-world usability. One of the primary case studies involves the open-hole problem, a well-known benchmark in composite mechanics, which is analyzed under both tensile and bending conditions. These simulations help evaluate stress concentration effects and the initiation and growth of delamination cracks. Additionally, a cross-beam member—previously studied with a steel material—is reanalyzed using a composite material, incorporating both delamination and intra-layer damage mechanisms. These case studies illustrate the efficiency and accuracy of the homogenized approach in predicting failure mechanisms under complex loading and geometrical conditions.The findings of this research contribute to the advancement of composite damage modeling by offering a computationally efficient framework for predicting delamination and intra-laminar damage. The homogenized approach significantly reduces preprocessing complexity while maintaining a high level of accuracy in failure prediction, making it particularly suitable for large-scale structural applications. Future research directions include incorporating fiber bridging effects, extending the framework to dynamic and thermal loading conditions, and utilizing mixed strain/displacement finite elements. Additionally, the application of machine learning techniques to enhance predictive capabilities presents an exciting avenue for further investigation.
  

DOCTORAL DEGREE IN URBAN AND ARCHITECTURAL MANAGEMENT AND VALUATION

• GARCÍA HARO, ALAN: Isla de frío de los parques urbanos: Hacia la definición de parámetros de composición para la optimización del efecto de enfriamiento en distintos contextos climáticos mediante análisis remoto
  
  Author: GARCÍA HARO, ALAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN URBAN AND ARCHITECTURAL MANAGEMENT AND VALUATION
  Department: Department of Architectural Technology (TA)
  Mode: Normal
  Deposit date: 02/04/2025
  Deposit END date: 15/04/2025
  Thesis director: ROCA CLADERA, JOSE NICASIO | ARELLANO RAMOS, BLANCA ESMARAGDA
  Thesis abstract: Due to their composition, generally characterized by the predominant presence of vegetation and permeable soils, urban parks exhibit lower temperatures compared to other areas of the city. In many cases, this thermal reduction extends to the surrounding areas, generating the phenomenon known as the "park’s cool island" (PCI). This effect makes parks essential elements for regulating and mitigating urban heat, a problem exacerbated by the urban heat island effect, the global increase in temperatures, and the growing frequency and intensity of extreme heat events associated with climate change. These situations pose significant threats to public health, disproportionately affecting vulnerable groups and increasing heat-related mortality rates. Moreover, the limited availability of updated and detailed climatic data hinders the planning and design of effective mitigation strategies at the local level.This research aims to establish design parameters that optimize the cool island effect of urban parks (PCI) in various climatic contexts, employing remote sensing techniques. To achieve this, a flexible methodology was developed based on satellite data analysis and statistical models, adaptable to both the availability of information and the specific characteristics of each case study. The methodology is structured into three main stages: 1) quantification of the intensity and spatial extent of the cool island effect generated by parks; 2) estimation of physical descriptors derived from remote sensing data; and 3) statistical analysis of the influence of the physical characteristics of parks and their surroundings on cool island effect indicators.This study focuses on the cases of Barcelona (Mediterranean climate) and Mexicali (hot arid climate), selected for their contrasting climatic conditions and differing levels of institutional data availability. Initial results reveal that in Barcelona, with 86 urban parks, the average daytime summer PCI intensity was 1.51°C with a spatial extent of 78.02 meters, whereas Mexicali, with 435 parks, recorded an intensity of 0.90°C and a spatial extent of 119.03 meters. A notable contrast emerges in these parameters, as two parks in Barcelona showed no cool island effect (2.3%), while in Mexicali, this number increased to 133 parks (30.6%). The results demonstrate that vegetation is the primary regulator of urban temperature in both cities. In Mexicali, explanatory models incorporating variables derived from NDVI and supervised land cover classification using Random Forest achieved R² values exceeding 90% in spring and summer. In Barcelona, although NDVI was also relevant, the analysis highlighted limitations related to proximity to the sea and forested areas.In conclusion, this research establishes a methodological framework to define design parameters for urban parks using remote sensing data, tailored to the functional and temporal needs of each context. This represents a significant step toward developing specific tools for urban planning decision-making, integrating key considerations for regulating and mitigating urban heat.