Public display of deposited theses

DOCTORAL DEGREE IN AGRI-FOOD TECHNOLOGY AND BIOTECHNOLOGY

• FERNANDEZ GONZALEZ, POL: Structural and functional characterization of rhodopsin mutants associated with retinitis pigmentosa and their modulation by small molecules
  
  Author: FERNANDEZ GONZALEZ, POL
  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 AGRI-FOOD TECHNOLOGY AND BIOTECHNOLOGY
  Department: Department of Agri-Food Engineering and Biotechnology (DEAB)
  Mode: Normal
  Deposit date: 09/01/2026
  Deposit END date: 22/01/2026
  Thesis director: GARRIGA SOLE, PERE
  Thesis abstract: G protein-coupled receptors constitute the largest superfamily of membrane proteins in mammals and play essential roles in signal transduction. Among them, rhodopsin serves as the primary photoreceptor in rod cells, mediating vision under dim light conditions. Mutations in the rhodopsin gene are the leading cause of retinitis pigmentosa, an inherited retinal degenerative disease characterized by progressive photoreceptor death and eventual blindness. Despite the severity of this condition, therapeutic options remain limited, making the development of novel stabilization strategies crucial. This thesis presents a comprehensive investigation of retinitis pigmentosa-associated rhodopsin mutations and evaluates the therapeutic potential of small molecule stabilizers as pharmacological chaperones. Through systematic biochemical, biophysical, and structural analyses, we characterized three pathogenic mutations located in transmembrane helix 3 (T108P and G121R) and the N-terminal region (M39R), revealing distinct molecular mechanisms underlying photoreceptor dysfunction. The T108P mutation preserved protein trafficking and chromophore binding but exhibited reduced thermal stability and severely impaired G protein activation due to conformational rigidity of the ERY motif. In contrast, G121R displayed features of a misfolding phenotype with complete loss of chromophore binding and partial intracellular retention, likely triggering endoplasmic reticulum stress-mediated apoptosis. The M39R variant, associated with sector retinitis pigmentosa, showed slightly reduced folding efficiency but partial significant preservation of native-like structure.Analysis of the G90V mutation, in transmembrane helix II, in a conformationally stabilized background (with the engineered N2C/D282C disulfide bond) demonstrated that while structural stabilization enhanced thermal and chemical resistance, it could not rescue the fundamental photoactivation defects. Solid-state nuclear magnetic resonance spectroscopy revealed subtle perturbations in retinal configuration and reduced conformational flexibility in key structural elements.Finally, evaluation of geraniol as a potential pharmacological chaperone showed promising results, enhancing M39R rhodopsin thermal stability without affecting chromophore regeneration, photobleaching, or activation dynamics. Its hydrophobic nature suggests interaction with the opsin membrane environment, establishing it as a candidate for further therapeutic development.Molecular dynamics simulations provided atomic-level insights into mutation-induced conformational changes, supporting experimental findings and revealing how subtle structural alterations lead to distinct pathogenic outcomes. Additionally, we successfully developed and optimized protocols for rhodopsin expression, purification, and solid-state nuclear magnetic resonance analysis, establishing a promising methodological framework applicable to other G protein-coupled receptors.These findings advance our understanding of rhodopsin-associated retinal degeneration mechanisms and demonstrate the feasibility of small molecule stabilization as a therapeutic strategy. The work provides a foundation for developing targeted interventions for retinitis pigmentosa and potentially other G protein-coupled receptors-related disorders, while highlighting the importance of mutation-specific therapeutic approaches.
  

DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY

• RIVERA VIDAL, AMANDA CATALINA: EARTH & FIBERS, Local Technologies Earthen Composites (LoTEC). Local reuse of by-products for zero-waste building materials, appropriate building solutions in vernacular and contemporary architecture.
  
  Author: RIVERA VIDAL, AMANDA CATALINA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY
  Department: Department of Architectural Technology (TA)
  Mode: Change of supervisor
  Deposit date: 16/01/2026
  Deposit END date: 29/01/2026
  Thesis director: NAVARRO EZQUERRA, MARIA ANTONIA | ACHENZA, MARIA MADDALENA
  Thesis abstract: This doctoral research addresses the environmental and cultural challenges of the construction sector by re-examining local materials and traditional knowledge, through scientific experimentation. Entitled EARTH & FIBERS Local Technologies Earthen Composites (LoTEC), the thesis investigates earth and vegetal-fiber composites derived from agricultural and excavation by-products as low-impact, circular, and regenerative materials for the decarbonization of the built environment.The study integrates comparative analyses of vernacular construction, experimental material testing, and architectural applications. Case studies from Europe and Latin America document the hygrothermal logic and cultural intelligence of traditional earth-and-fiber systems. Laboratory analyses characterize local raw materials (soils and vegetal residues), leading to the formulation and testing of new earthen composites. Their physical, chemical, and hygrothermal properties—including thermal conductivity, vapor permeability, acoustic absorption, and fire response—have been systematically evaluated. Medium-scale prototypes constructed and monitored under real conditions confirm their technical feasibility and architectural applicability.Results indicate that LoTEC composites display versatile hygrothermal behavior, ranging from thermal insulation to heat storage depending on mixture density and fiber composition. Produced without chemical alteration of the raw materials —only sieved soils and cut vegetal fibers—they require minimal energy for transformation from raw matter to building element. At the end of their service life, they can be rehydrated and reused without performance loss or safely reintegrated into the environment. Their permeability and moisture-buffering capacity make them particularly compatible with the vapor-open nature of historical materials, enabling effective retrofitting and improved indoor comfort while preserving architectural heritage. They also perform efficiently in new constructions based on sufficiency, circularity, and locality.Beyond technical results, the research reframes architectural sustainability within a post-growth paradigm, shifting the focus from expansion and consumption toward care, adaptation, and material responsibility. By merging traditional knowledge with scientific analysis and contemporary design, EARTH & FIBERS advances a model of architecture that minimizes extractive dependence and supports ecological and cultural regeneration, positioning earthen and vegetal-fiber materials as essential components of a decarbonized and contextually grounded built environment.
  

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

• GARCÍA SÁNCHEZ, CARLOS ANDRÉS: Genetic Programming Algorithms for Controller Design in the Time Domain
  
  Author: GARCÍA SÁNCHEZ, CARLOS ANDRÉS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Department of Automatic Control (ESAII)
  Mode: Normal
  Deposit date: 19/01/2026
  Deposit END date: 30/01/2026
  Thesis director: VELASCO GARCIA, MANUEL | ANGULO BAHON, CECILIO
  Thesis abstract: This work presents a symbolic evolutionary framework for the automatic design of interpretable controllers via Genetic Programming (GP), developed entirely in the time domain and applicable to both single-input and multi-input control systems. In contrast to traditional model-based and blackbox artificial intelligence methods, the proposed approach evolves algebraic control expressions that integrate differential operators — such as integrals and derivatives — and operate exclusively on observable variables, without requiring internal system models. The methodology is initially validated on Single-Input Single-Output (SISO) systems and later scaled to complex Multiple-Input Single-Output (MISO) plants, with experimental emphasis on hydrogen generation systems composed of up to 36 parallel-connected modules. Controllers are evolved to replicate dynamic reference profiles, distribute workload equitably, and adapt to degradation across structurally heterogeneous packs. The approach includes a multi-objective fitness function with dynamic weighting, enabling convergence to compact, high-performance symbolic expressions that respect operational constraints. Results show that the evolved controllers achieve smooth tracking, scalable behavior, and structural modularity, even in high-dimensional settings. The symbolic nature of the solutions allows for post-process reuse, interpretability, and adaptation to changing system configurations. Furthermore, the analysis confirms that symbolic self-organization supports proportional effort distribution and efficient power coordination, without explicit synchronization mechanisms. Overall, this model-free strategy offers a reusable and explainable alternative for deploying advanced control in real-world energy systems.
  
• MEDRANO DÍAZ, MANUEL ALEJANDRO: Estimación de series de tiempo de imágenes mediante técnicas de aprendizaje profundo
  
  Author: MEDRANO DÍAZ, MANUEL 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 AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Department of Automatic Control (ESAII)
  Mode: Change of supervisor
  Deposit date: 20/01/2026
  Deposit END date: 02/02/2026
  Thesis director: PUIG CAYUELA, VICENÇ | RODRÍGUEZ RANGEL, HÉCTOR
  Thesis abstract: An image time series (ITS) is a chronologically ordered sequence of images showing the spatial change of its elements over time. Satellite images of meteorological events can be treated as ITS by displaying their values through pixel color intensity.Estimating from a ITS with a deep learning model is a complex problem that requires analyzing various configurations that determine how images are processed. It is a computationally intensive problem, which, due to its non-deterministic characteristics, requires combining different parameter configurations to extract spatio-temporal relationships. Thus, the complexity of the problem increases as the dimensions to be evaluated increase.To solve this problem, a robust and scalable conceptual model for ITS estimation is proposed that extracts the spatiotemporal relationships between pixels and their neighborhoods. Based on the specifications of the proposed model, a methodological proposal is developed that allows the estimation of meteorological maps using deep learning models. The proposed methodology is implemented through the design of a software architecture that translates abstract elements into software components, allowing the methodology to be evaluated through the use of deep learning models in different case studies.In the case study of the United States (US) drought monitor, experimentation with deep learning models based on ConvLSTM and Multi-CNN mostly yielded an F1-score of over 0.90 for the estimation of step t+1, with the best model obtaining an F1-score of 0.9953. Due to the high memory demand of the data dimensions, together with the physical limitations of the hardware equipment, dimension reduction techniques were applied to the images. Using the fragmentation technique with the ConvLSTM architecture, an F1-score of 0.9684 was obtained by reducing the dimension of the samples by 48%. By applying recursive and direct multi-step estimation strategies, medium-term estimates could be made. However, due to the complexity of the spatiotemporal analysis, there is an accumulated error that affects the quality of the medium-term estimate.In a second case study on US standardized precipitation index (SPI) maps, a ConvLSTM architecture is used to estimate step t+1. The results show that the best learning model obtains an F1-score of 0.5268, while the Naïve model obtains an F1-score of 0.3408. The results demonstrate the capabilities of deep learning models to extract spatiotemporal relationships from a sequence of images, laying the foundation for a branch of research focused on image estimation.
  
• VINARDELL MAGRE, LAURA: FULL-SCALE WATER DISTRIBUTION NETWORKS MODELLING FOR DISINFECTION BY-PRODUCTS ESTIMATION
  
  Author: VINARDELL MAGRE, LAURA
  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: 09/01/2026
  Deposit END date: 23/01/2026
  Thesis director: PEREZ MAGRANE, RAMON | JUBANY GUELL, IRENE
  Thesis abstract: The quality of the water that reaches our homes depends on multiple factors: the origin of the water, the treatment it undergoes, and the distribution network that delivers it. To ensure water safety not only at the treatment plant’s outlet but also at the points of consumption, chemical disinfectants are often added. Chlorine is one of the most widely used disinfectants worldwide due to its low cost, versatility, and its ability to maintain residual disinfectant power throughout the network. However, despite these advantages, chlorine can form potentially harmful by-products under certain conditions. For this reason, the latest European Union directive (2023) mandates the regulation of several disinfection by-products: trihalomethanes (THMs), haloacetic acids (HAAs), chlorate, chlorite, and bromate.This thesis presents the development of several models to estimate the concentration of by-products resulting from the use of hypochlorite as a disinfectant. Two case studies have been examined: one high-pressure distribution network and another with both high and low-pressure distribution. Over the course of a year, multiple sampling campaigns were carried out to collect sufficient data to calibrate and validate the estimation models. Prior to this, hydraulic models were adjusted to provide input for the water quality models.The study focuses on three types of disinfection by-products regulated by European standards: the THM family, the HAA family, and chlorate. It was observed that the speciation of THMs and HAAs is strongly influenced by the water source. Moreover, the evolution of the concentration of these compounds varies depending on network operation and the number of rechlorination stations. For chlorate, its formation was studied in relation to the use and storage of concentrated hypochlorite, both in primary disinfection and in rechlorination stations.Two modelling approaches were applied for THMs and HAAs: mechanistic models and data-driven models. The mechanistic models are based on the relationship between compound formation and chlorine decay, whereas data-driven models identify patterns among variables without explicitly relying on the underlying physical or chemical processes. In the latter case, specific models were developed for each case study, as well as a general model applicable to both networks, despite their differences in size, water origin, and operation.All models developed for THMs and HAAs were applied both to individual compounds and to the regulated totals (TTHMs and THAAs). The study assessed which strategy yields better estimations: summing individual models or directly modelling the total concentrations. In this study, direct estimation of totals gave slightly better results. However, modelling individual compounds can provide added value, both from a risk management perspective (since each compound may have a different impact) and for a deeper understanding of their formation mechanisms.Finally, for chlorate, a mechanistic model was developed based on the known kinetics of hypochlorite degradation. The formation of chlorate in concentrated hypochlorite storage tanks was integrated into a hydraulic model simulating the behavior of the water tank receiving chlorination, enabling estimation of the chlorate concentration at the outlet. The model provided accurate predictions and can be applied to other distribution networks.
  

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

• GARYFALLOS, SPYRIDON: Deep Learning Methods for Transient Performance Analysis and Optimization of Non-Markovian Nonstationary Queueing Systems
  
  Author: GARYFALLOS, SPYRIDON
  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: 19/01/2026
  Deposit END date: 30/01/2026
  Thesis director: CABELLOS APARICIO, ALBERTO | LIU, YUNAN
  Thesis abstract: Empirical studies show that real-world service queueing systems, such as contact centers and healthcare facilities, often exhibit non-Markovian behavior, including non-exponential service and abandonment times, as well as nonstationary dynamics driven by time-varying arrivals and staffing. These complexities make performance analysis and capacity planning particularly challenging. Traditional methods face notable limitations: Monte Carlo simulation, while flexible, can be computationally intensive for large systems or real-time decisions; and heavy-traffic analysis is a model-specific approximation that applies only to certain queueing structures, depends on the service-level metric of interest, and its accuracy may deteriorate for small-scale systems.To address these challenges, this thesis develops machine learning frameworks for analyzing and optimizing non-Markovian, nonstationary queueing systems. Trained on simulated data, the models learn the spatio-temporal structure of complex service systems and provide extremely fast inference, enabling real-time decision support. They are effective and robust across problem scales, and their design and training are universal, in contrast to heavy-traffic formulas that must be re-derived for each model and performance measure. By integrating accurate prediction with real-time optimization, this work advances queueing theory by introducing modern data-driven tools for dynamic capacity management in complex service operations.The thesis consists of three main contributions: (1) a neural network framework for performance analysis of non-Markovian nonstationary queueing systems with fixed capacity; (2) a deep learning framework based on a transfer learning approach that enables model adaptation to queueing systems with time-varying server capacity; (3) an optimization framework for staffing in non-Markovian nonstationary environments. All of these methods are accompanied by accuracy, robustness, and computational runtime experiments, demonstrating the effectiveness of the proposed approaches compared to traditional methods.
  
• SAMADI GHARAJEH, MOHAMMAD: Mapping of Real-Time Computation to Parallel Platforms
  
  Author: SAMADI GHARAJEH, MOHAMMAD
  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: 20/01/2026
  Deposit END date: 02/02/2026
  Thesis director: PINHO, LUIS MIGUEL | ROYUELA ALCÁZAR, SARA
  Thesis abstract: Time-critical systems are a special type of application that must complete computing tasks within specific time constraints to guarantee the required level of service. As these systems have become more complex in recent years, they have increased performance requirements, which necessitates the need to use more powerful hardware platforms, providing higher performance. The performance of these systems can be improved by utilizing multi-core processors and parallel programming models (e.g., OpenMP). However, the predictability and schedulability of these parallel applications easily become intricate due to the potentially complex structure of execution graphs and the several resources available in modern architectures. Therefore, mapping tasks to computing resources needs to be performed efficiently in these applications to improve the work-conserving of the mapping process and the load-balancing of the job queues. This process can lead to reduced application response time (and WCRT), as well as its variability.To address the problems mentioned above, this thesis tackles the challenge of maintaining system predictability and schedulability while maximizing performance in real-time parallel computing systems. Accordingly, it (i) proposes task-to-thread mapping methods based on heuristics that exploit knowledge about the behavior of predictable parallel applications, considering both the offline design of the system as well as the online execution phase, to reduce the variability of response times and the WCRT, as well as to improve the average response time in OpenMP applications, (ii) uses efficient methods for measuring parallel tasks in terms of schedulability and predictability as well as discovering the longest execution path through the parallel execution (i.e., WCRT), (iii) evaluates the impact of the configurations of mapping algorithms (e.g., static and dynamic mapping) and hardware platforms on the task execution time and application response time, and (iv) proposes and evaluates the performance of task-to-accelerator mapping using different heuristics to reduce the response time by executing high-workload tasks in the accelerator.Evaluation results, based on simulations and experiments using random graphs and real-world applications, demonstrate that the new approaches, in most cases, minimize response time (and WCRT) and reduce the variability of response times compared to existing mapping approaches. In addition, a prototype implementation of the main heuristics is evaluated using real-world applications, showing that the WCRT and response time variability obtained using the new methods are lower than those obtained using LLVM's default scheduler in most configurations. These achievements show that the proposed methods can improve the predictability and schedulability of real-time parallel applications.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• BRAGANTINI, ANDREA: Learning-based State Estimation for Low Voltage Distribution Grids Using Neural Networks
  
  Author: BRAGANTINI, ANDREA
  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: 20/01/2026
  Deposit END date: 02/02/2026
  Thesis director: SUMPER, ANDREAS
  Thesis abstract: This doctoral thesis investigates how learning-based methods, particularly artificial neural networks (ANNs), can provide a practical and cost-effective solution for state estimation in low-voltage (LV) distribution grids, where measurement infrastructure is typically scarce or absent. Traditional state estimation (SE) approaches, such as Weighted Least Squares (WLS), are effective at transmission and, with adaptations, at medium-voltage level, but are economically and technically unfeasible for LV networks. Their radial topology, unbalanced operation, high R/X ratios, and large number of nodes make dense metering and communication systems prohibitive for distribution system operators (DSOs).This work proposes a simulation-driven methodology to train ANN-based state estimators (ANNSEs) capable of monitoring LV grids in near real time using a limited set of synchronized measurements, primarily those available at secondary transformer substations.The research begins by defining a standardized design and evaluation framework for ANNSEs. Monte Carlo–based probabilistic power flow simulations are used to generate synthetic training datasets from minimal grid information. Initially, a single-phase approximation is adopted, and ANN models are trained to map four basic substation measurements (voltage, current, active and reactive power) to nodal voltage magnitudes. A bi-dimensional performance assessment combining mean absolute error (MAE) and R² is introduced. Case studies on rural, village, and suburban networks show MAE values typically below 1 V, with higher robustness in larger grids exhibiting stronger voltage gradients. Input voltage measurement accuracy emerges as the main limiting factor.The methodology is then benchmarked against alternative machine learning models, including linear regression, random forests, gradient-boosted trees, and multilayer perceptrons. While prediction accuracy remains comparable, custom feed-forward neural networks (FFNNs) demonstrate superior scalability and architectural flexibility, supporting their selection as the preferred ANNSE architecture.The core contribution extends the methodology to realistic three-phase, four-wire LV networks. A multi-network FFNN architecture with separate sub-networks for each phase and the neutral conductor is combined with a three-phase probabilistic power flow. Validation using real pilot data confirms accurate prediction of phase-to-ground voltages, including severe voltage drops and neutral voltage rise, with MAE below 0.3 V and down to 0.2 V when an additional measurement device is optimally placed.The final study addresses robustness and deployment challenges. Sensitivity analyses quantify the impact of grid-model inaccuracies, network evolution, and measurement errors. Moderate errors in line parameters, load growth (up to 9%), or PV penetration (up to doubling) only marginally affect performance, postponing retraining. In contrast, incorrect phase allocation and biased or missing voltage measurements significantly degrade accuracy. Local Sensitivity Analysis shows that ANNSE predictions are primarily anchored to voltage inputs, while power and current measurements contribute locally within feeders, yielding physically interpretable sensitivity patterns.Taken together, these studies define a coherent methodology for deploying ANN-based state estimators as a scalable and cost-effective monitoring tool for LV distribution grids. The thesis demonstrates that ANNSEs, trained offline on digital twins with simulation-driven data, can be deployed in practice to detect voltage deviations and fluctuations in near real time using minimal instrumentation, enhancing observability and reliability in currently unmonitored LV networks.
  
• NOLASCO BENITEZ, EDITH: Evaluación de programas de electrificación rural desde un enfoque de sostenibilidad: Análisis del impacto del BID-FERUM II en Ecuador
  
  Author: NOLASCO BENITEZ, EDITH
  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: 20/01/2026
  Deposit END date: 02/02/2026
  Thesis director: GOMIS BELLMUNT, ORIOL
  Thesis abstract: Access to energy is a key driver of economic and social development, as it fosters income generation, contributes to poverty eradication, and enhances quality of life. Its significance has been acknowledged through initiatives such as the 2030 Agenda, which prioritises universal access to clean and modern energy. Nevertheless, despite notable progress, millions of people worldwide remain without access to electricity services, predominantly in rural areas of developing countries. Africa is among the most affected regions, while others, such as Latin America, the Caribbean, and East Asia, have made substantial progresses towards universal access. Factors such as the pandemic, inflation, and the global energy crisis have slowed this progress, impacting equity and sustainability in energy access.In response to this scenario, rural electrification has been approached through various technical strategies, including grid extension, stand-alone systems, and mini-grids. However, significant challenges persist regarding the sustainability and effectiveness of implemented programmes. The need for comprehensive evaluations has led to the development of methodological frameworks focused on energy sustainability.This doctoral thesis aims to evaluate a rural electrification programme using a methodology based on a sustainability framework comprising five dimensions: technical, economic, social, environmental and institutional. The evaluation is conducted at the local level, using a case study the Rural and Urban-Marginal Electrification Programme FERUM II, implemented in the province of Esmeraldas, Ecuador. Through this territorial analysis, key aspects for evaluating such programmes are identified, and specific indicators are defined to assess the achievement of objectives within each dimension. The proposed methodology seeks to offer a practical, contextualised, and replicable guide for developing countries interested in conducting rigorous evaluations of rural electrification initiatives.The research is structured in several phases: first, a systematic literature review to contextualise the problem and build the theoretical framework; then, the development of the evaluation methodology, applied to the Ecuadorian case through semi-structured interviews, questionnaires and fieldwork in rural communities. Based on the analysis of locally collected data, two fundamental questions are addressed: What elements should be considered when evaluating rural electrification programmes? and What outcomes emerge from applying the sustainability framework to the FERUM II case?Preliminary results indicate that the programme has led to substantial improvements in access to electricity services and in the quality of life of the beneficiary population in Esmeraldas. This demonstrates that the proposed sustainability framework effectively captures the multidimensional impacts of rural electrification in vulnerable contexts. The economic dimension reveals certain weaknesses, particularly regarding the promotion of productive activities and access to credit. In contrast, the social dimension shows a positive impact, with progress in education, communications, and security. From an environmental perspective, a reduction in the use of fossil fuels is observed due to the incorporation of grid electricity. Regarding the institutional component, although performance is generally acceptable, deficiencies are identified in the relationship between distribution companies and beneficiary communities, particularly in terms of user support and communication.Keywords: Rural electrification, energy sustainability, programme evaluation, energy access, social and economic development, sustainable development, Esmeraldas, Ecuador.
  

DOCTORAL DEGREE IN PHOTONICS

• BELSA CARNÉ, BLANCA MARIA: Engineering Catalyst-Ionomer Interfaces for Carbon-Efficient CO2 Electrolysis and Technology Prospects
  
  Author: BELSA CARNÉ, BLANCA 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 PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 15/01/2026
  Deposit END date: 28/01/2026
  Thesis director: GARCÍA DE ARQUER, FRANCISCO PELAYO
  Thesis abstract: The electrochemical reduction of CO2 (CO2E) offers a promising route to convert greenhouse gas emissions into value-added chemicals and fuels. However, achieving performance metrics that enable the technoeconomic and sustainable viability of CO2E remains challenging. This is especially acute in the case of multicarbon products (C2+), important precursors for energy fuels and manufacturing, where achieving combined selectivity and carbon utilisation under industrially relevant conditions is challenged by undesired competing reactions. This thesis explores the design and implementation of new strategies to modulate electrochemical interfaces in CO2E to overcome this barrier. These are based on the implementation of ionomer coatings that specifically address key reactants and intermediates in CO2E. A key contribution is the development and mechanistic elucidation of ion management channels (IMCs), formed by co-distributing cation and anion exchange ionomers (CEIs and AEIs) within the catalyst layer. This architecture enables local regulation of hydroxide and cation populations, mitigating *OH poisoning and enhancing *CO adsorption, critical steps for promoting C–C coupling and C2+ product formation.The ionomer–catalyst interface is comprehensively characterised using SEM–EDS, FTIR, XPS, KPFM, contact angle measurements, cyclic voltammetry, and EIS. In situ Raman spectroscopy reveals the dynamic evolution of surface species, confirming that excessive *OH accumulation suppresses C2+ selectivity, while IMCs restore favourable interfacial conditions. These insights are correlated with improved electrochemical performance, carbon efficiency, and stability across a wide range of operating conditions, including highly acidic environments.The IMC concept is further implemented in membrane electrode assembly (MEA) devices operating under neutral pH. Preliminary results demonstrate improved performance and reduced cell voltages for IMC-based electrodes, indicating compatibility with scalable reactor platforms and commercially viable components.The thesis concludes with a broader analysis of the challenges facing CO2E at scale. Key bottlenecks, such as the reliance on iridium anodes and fluorinated membranes, are critically assessed, and material and performance targets for gigaton-scale deployment are proposed. A techno-economic and life-cycle analysis outlines trade-off between performance, cost, and sustainability, while global scaling efforts are reviewed. Benchmarking protocols are proposed to bridge the gap between laboratory research and industrial implementation.Together, this work advances a cohesive framework for interfacial engineering in CO2E, linking molecular-level understanding to device-scale integration, and providing pathways toward industrial deployment.
  
• LAMICH, TOMÁŠ: A single emitter emitting resonance fluorescence into a coherent beam
  
  Author: LAMICH, TOMÁŠ
  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: 15/01/2026
  Deposit END date: 28/01/2026
  Thesis director: MITCHELL, MORGAN | VEYRON, ROMAIN
  Thesis abstract: This thesis studies the statistics of light produced by a single trapped atom in free space when interfaced with two orthogonal coherent beams. The atom scatters light into the same spatial mode as a weak coherent probe beam, giving rise to controllable photon statistics. Being able to control the photon statistics of a source can be used in applications in where different photon statistics are desired.A single emitter in free space, when left to interact with a single pumping beam can only scatter one photon at any given moment leading to anti-bunched photon statistics. However, Goncalves et al. (2021) studied the possibility of interfacing the atom with a strong pumping beam, and a weak probing beam, leading to a controllable photon statistics, where super- and sub-Poissonian statistics can be achieved by varying either the pump-probe ratio or the relative pump-probe phase. By controlling the pump-probe ratio, it is also possible to control the probe transmission through the atom.The experimental implementation of the "GMC" scheme shows the predicted behaviour where the transmission can be suppressed to 62 %, and tuned by changing the pump-probe ratio. It also shows that the photon statistics can go from super- to sub-Poissonian by changing the relative pump-probe phase, and the photon bunching achieved is also pump-probe ratio dependent.In addition, measurements of the atom temperature are presented in this thesis, where the interference of the pump and probe beams on the atom lead to a direct measurements of the rms displacement of the atom within the trap, which is linked directly to the atom temperature. These measurements demonstrate a new non-destructive method of estimating the atom temperature.
  

DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE

• IAMPIERI, ARIANNA: Oriol Maspons, un archivio della memoria visiva del secondo ‘900. La fotografia come interpretazione del contesto abitato
  
  Author: IAMPIERI, ARIANNA
  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: 13/01/2026
  Deposit END date: 26/01/2026
  Thesis director: PIZZA DE NANNO, ANTONIO | BERGERA SERRANO, JOSE IGNACIO
  Thesis abstract: Oriol Maspons was one of the leading figures of the photographic scene in Barcelona during the second half of the 20th century and a key participant in the renewal of photographic language, which at the time was still anchored in academic and traditionalist canons. Although his vast and eclectic work has been studied over time, his contribution to the representation of architectural and urban space remains largely unexplored, despite this field being a constant throughout his photographic career. This thesis aims to delve into Oriol Maspons’s perspective on the inhabited environment, thereby contributing to the fascinating study of the intersections between photography, architecture, and urban space.Maspons's interest in architecture and the city emerged from the early years of his amateur practice and solidified over time, as demonstrated by the numerous professional collaborations he undertook, sometimes independently, sometimes together with his associate Julio Ubiña, with whom he founded a photography studio in 1957. Maspons and Ubiña produced photo reports for several architects and editorial projects in the field, including Cuadernos de Arquitectura (the journal of the Col·legi d’Arquitectes de Catalunya - COAC), documenting major architectural works and the ongoing urban transformation; another significant project was the work he carried out for the volume Arquitectura Española Contemporánea by Lluís Domènech i Girbau.In addition to being a visual witness to the architectural production of his time, Maspons also turned his camera toward historical heritage, capturing modernist and Gothic architecture, the latter being the focus of the photographic book Arquitectura gótica catalana, featuring texts by Alexandre Cirici and graphic design by architects Oscar Tusquets and Lluís Clotet.In parallel, Maspons visually narrated his city, Barcelona, through tourist guides such as Això també és Barcelona (in collaboration with Ubiña) and Barcelona pam a pam, contributing to the dissemination of a previously unseen image of the city. During the Olympic period, he worked alongside other photographers such as Francesc Català-Roca, Colita, and Xavier Miserachs, offering valuable testimony to the radical architectural and urban transformations that reshaped Barcelona in the 1980s.These examples highlight both the scope of Maspons’s work and his versatility. A deeper study of his oeuvre, which deserves greater attention, represents a significant contribution to both the history of photography and the history of Spanish architecture in the second half of the 20th century, given Maspons’s important role in the architectural discourse of the time and in shaping the visual imagination of the Catalan capital.Through the analysis of existing bibliography, the study of unpublished archival material, and the examination of publications illustrated with his photographs, the aim is to offer a broader and more in-depth perspective on the subject. The objective is to expand existing knowledge with new findings, consolidate certain positions, develop critical reflections on Maspons’s work in architectural and urban representation, and open up new research fields.
  
• ROGER GONCE, JOAN: “El barrio que (nos) construimos” Creixement i desenvolupament urbà del barri de Roquetes de Barcelona, a través del Padró Municipal d’Habitants (1940-1978)
  
  Author: ROGER GONCE, JOAN
  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: 13/01/2026
  Deposit END date: 26/01/2026
  Thesis director: ROSSELLO NICOLAU, MARÍA ISABEL | OYON BAÑALES, JOSE LUIS
  Thesis abstract: This study addresses the urban history of the Roquetes neighborhood of Barcelona during the Franco period, with the aim of analyzing its formation, consolidation and transformation over the course of more than forty years of dictatorship. The work aims to provide data and a critical reflection on the social, economic and urban processes that shaped this working-class and markedly immigrant neighborhood, in a context of accelerated growth, precarious infrastructure and territorial inequalities.The meticulous analysis of the municipal population register, systematically cross-referenced with other demographic, labor and urban sources, has allowed us to delve deeper into key issues for understanding the neighborhood's trajectory: the migratory networks and chains that sustained its growth; the forms of work and the opportunities —or limits— of social mobility for its residents; the housing conditions and models of urban production; and, finally, the construction of the neighborhood as a space for coexistence, identity and sociability in a framework of institutional abandonment and neighborhood responses.Through this combination of perspectives and sources, the research provides an integrated look at Roquetes that contributes to the broader debate on urban peripheries, Franco's socialist regime and the everyday experiences of popular sectors in 20th-century Barcelona.
  

NAUTICAL ENGINEERING, MARINE AND NAVAL RADIOELECTRONICS

• CAMPOS TORESANO, CRISTINA: Future implications of Maritime Autonomous Surface Ships (MASS) over seafarers’ jobs and Maritime Education and Training (MET). Spanish case- study.
  
  Author: CAMPOS TORESANO, CRISTINA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: NAUTICAL ENGINEERING, MARINE AND NAVAL RADIOELECTRONICS
  Department: Department of Nautical Sciences and Engineering (CEN)
  Mode: Normal
  Deposit date: 13/01/2026
  Deposit END date: 26/01/2026
  Thesis director: CASTELLS SANABRA, MARCEL·LA | BORÉN ALTÉS, CLARA
  Thesis abstract: The main objective of this PhD aims to review, update and implement the requirements for Maritime Education and Training (MET) related to Maritime Autonomous Surface Ships (MASS). In order to achieve this objective, the projects under development and existing autonomous vessels have been studied, as well as new emerging technologies and, consequently, the new knowledge that future crews will need to acquire. The impact of autonomous navigation has been analysed from different perspectives to determine its direct implications on the jobs and training of the future seafarers. Future job creation needs will generate new skills and knowledge that will need to be incorporated into current courses and degrees. These new skills have been analysed from different perspectives, with the aim of proposing a new subject as a first step toward completing the training of future seafarers.First, this thesis conducts a bibliometric analysis to explore the progress and research carried out up to the start of the project, in order to identify the most relevant academic publications and studies in the field of maritime training and autonomous vessels.Secondly, through the use of surveys, the competencies, knowledge, and skills that could be added or adapted are explored, comparing the results obtained with recent advances in education and training. As a result, a proposal is presented for a possible new subject that could constitute a future line of development in the field of autonomous vessel training.Finally, based on the results obtained, a model course has been designed and implemented in collaboration with four European Universities. This course includes an evaluation and analysis of the outcomes to develop a proposed introductory course that could be adopted by all Maritime Education and Training Institutions (METIS).