Public display of deposited theses

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

• CARRIZOSA RENDÓN, ÁLVARO: Advances in Set-Based Motion Planning for Safe Interaction of Autonomous Vehicles
  
  Author: CARRIZOSA RENDÓN, ÁLVARO
  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: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: PUIG CAYUELA, VICENÇ | NEJJARI AKHI-ELARAB, FATIHA
  Thesis abstract: This thesis presents several contributions in the field of safe driving of autonomous vehicles, focusing on motion planning and prediction of environmental agents based on their behaviour. The methodologies combine set-based techniques, LPV models and optimisation, seeking to ensure safety with low computational cost in realistic scenarios.First, a comprehensive review of the literature on the use of set-based methods to address safety in autonomous driving is presented. The study focuses on three main families of techniques: reachability analysis, invariant sets, and feasibility theory, describing how they have been applied to different planning, control, and supervision problems. Their advantages, disadvantages, differences and similarities are analysed. With this review, a unified framework for interpreting the existing literature is proposed, which serves as a basis for justifying the design decisions adopted in the subsequent contributions of the thesis.The following contribution consists of a safe motion planner designed for structured convex scenarios with complete knowledge of the environment and the actions of the agents surrounding it. To this end, a formulation based on LPV models and reachability analysis using zonotopes with constraints is proposed, which is integrated into a predictive control scheme formulated as a quadratic problem. This approach allows explicit safety constraints to be imposed on the optimiser, ensuring collision avoidance and achieving safe trajectories with lower computational cost and less conservatism than classical robust approaches.Subsequently, an efficient prediction method is proposed to estimate the future occupancy of surrounding vehicles online, based solely on their observed actions. The approach is based on optimisation and zonotopic propagation techniques to construct occupancy sets that adapt dynamically without the need for trained models or prior assumptions. The result is a refined and computationally lightweight estimator, designed to be integrated into real-time planners.Finally, a motion planner capable of working in complex urban scenarios is presented, extending the two previous contributions. Based on the first safe planner, a new structure is formulated that maintains the QP problem but now employs a purely zonotopic reachability analysis combined with constraints, allowing it to work in non-convex environments and with partial knowledge of the intentions of surrounding vehicles. The prediction module is proposed as an evolution of the previous one, taking advantage of the known geometry of the road to obtain more refined occupancy sets.
  

DOCTORAL DEGREE IN BIOINFORMATICS

• MANZINI, ENRICO: Deep Learning Strategies for Longitudinal EHRs: Patient Trajectory Modelling, Survival Analysis and Semantic Representations in Chronic Diseases
  
  Author: MANZINI, ENRICO
  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 BIOINFORMATICS
  Department: School of Mathematics and Statistics (FME)
  Mode: Article-based thesis
  Deposit date: 02/02/2026
  Deposit END date: 13/02/2026
  Thesis director: PERERA LLUNA, ALEXANDRE
  Thesis abstract: The growing availability of longitudinal electronic health records (EHRs) offers unprecedented opportunities to advance personalized medicine and improve patient care. Motivated by recent breakthroughs in deep learning (DL) and the transformative impact of large language models and foundation models in other domains, this thesis explores how similar computational approaches can be adapted to the complexities of healthcare data. The work investigates how neural architectures can capture temporal patterns, non-linear interactions, and latent structures within sparse, heterogeneous clinical datasets, enabling the prediction of disease trajectories and clinical outcomes with greater precision. A central focus is on chronic diseases, particularly type 2 diabetes and chronic obstructive pulmonary disease, where patient trajectories vary widely and outcomes depend on dynamic interactions among biomarkers, treatments, and comorbidities. By developing and adapting attention-based and recurrent neural networks, the thesis shows that DL can predict disease evolution, identify patient subgroups with distinct clinical trajectories, and estimate the risk of key clinical events over time. Hence, by learning meaningful representations of patient histories, these models support dynamic, data-driven decision-making that moves beyond static risk scores toward truly personalized care. In doing so, the work shows how the principles underlying generative foundation models and LLMs—such as sequence modelling, attention mechanisms, and contextual embeddings—can be translated into clinical applications, enabling DL models to generate interpretable, actionable insights from complex longitudinal data. Beyond predictive performance, this thesis emphasizes interpretability, usability, and the integration of patient-generated data. Techniques to translate patient-reported symptoms into structured medical ontologies, for example, illustrate how artificial intelligence can bridge communication gaps, enhance data quality, and facilitate real-world implementation. The work also reflects on methodological considerations, highlighting the importance of tailoring architectures to irregular, multidimensional clinical data, leveraging pre-training and defining embedding strategies to improve robustness, generalisation, and reproducibility. Specifically, this thesis is organized around four complementary lines of research, each addressing a different aspect of applying deep learning to healthcare data. The first focuses on unsupervised techniques, clustering longitudinal trajectories in type 2 diabetes and identifying patient subgroups with distinct disease progression patterns and clinical profiles to support personalized management. The second and third lines focus on supervised learning: the second develops a transformer-based model to predict longitudinal outcomes, emphasizing model architecture and the adaptation of attention-based networks to irregular, multidimensional EHR data, while the third is centred on modelling the complex dynamics of clinically relevant outcomes through deep survival analysis. Finally, the fourth line investigates the translation of layperson medical terminology into structured ontologies, enabling patient-reported data to be integrated into standardized clinical vocabularies and facilitating usability and research applications. Taken together, the four lines of research of this thesis demonstrate both methodological innovations and clinically meaningful results, spanning predictive modelling, patient stratification, and the enhancement of healthcare data usability. They represent a step forward in precision medicine and AI-assisted healthcare, showing that thoughtfully designed deep learning frameworks can transform complex, heterogeneous EHR data into interpretable, actionable knowledge.
  

DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING

• FUENTES LLANOS, JUDITH: Development of 3D Bioengineered Skeletal Muscle-based Bioactuators for Biorobotic and Biomedical Applications
  
  Author: FUENTES LLANOS, JUDITH
  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: Article-based thesis
  Deposit date: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: SÁNCHEZ ORDÓÑEZ, SAMUEL | GUIX NOGUERA, MARIA
  Thesis abstract: Biohybrid systems are engineered constructs that integrate living materials, like cells or tissues, with synthetic components, such as electronics, mechanical structures, or other artificial materials. This integration aims to leverage the unique capabilities of biological materials, including self-assembly, responsiveness to certain stimuli, adaptability, and self-repair, being features challenging to replicate in their synthetic counterparts. By combining these traits with the robustness and compliance of synthetic structures, biohybrid systems emerge as versatile platforms capable to both adapt and actuate in dynamic environments. Among the various biological components explored, skeletal muscle stands out due to its high force-to-weight ratio, controllable contraction, and compatibility with 3D biofabrication strategies, making it ideal for applications in soft robotics, drug testing, and regenerative medicine.This PhD thesis focuses on the development of 3D bioengineered skeletal muscle bioactuators, addressing key aspects from the biofabrication to functionality improvement, actuation control, and regenerative capacity.We developed and optimized a Pluronic-Assisted Coaxial 3D bioprinting (PACA-3D) method capable of biofabricating fascicle-like skeletal muscle bioactuators with improved maturation, sarcomere formation and contractile force when compared to muscles generated using conventional extrusion-based 3D bioprinting. To improve actuation and directional control, we introduced magnetic responsiveness into the bioactuators by developing a biocompatible ferrofluid-based bioink, used to fabricate the Ferromuscle, in collaboration with Waterloo and Aalto Universities. Such bioactuators exhibited improved cell alignment and force output, as well as magnetically guided actuation. In collaboration with the University of Cagliari (UniCa), we also evaluated the integration of flexible Organic Field-Effect Transistor (OFET)-based strain sensors for real-time monitoring of contractile behavior. These devices allowed tunable force sensing, showing no signal cross-talk when using standard electrical stimulation protocols, which is paving the way for closed-loop stimulation strategies and automated drug screening platforms. Moreover, we evaluated the self-healing capacity of the bioactuators after damage conditions, designed to mimic the mechanical stress that they typically undergo during manipulation of biohybrid systems. We observed partial to full force recovery and structural remodeling without external interventions, although the underlying biological mechanisms remain to be elucidated.Finally, additional collaborative work that enriched this thesis will be also discussed. Such studies include the integration of tendon-like structures to develop muscle-tendon unit (MTU) actuators with enhanced biomimicry, performance, and stability (ETH Zurich). Moreover, it will also be covered the design of biohybrid flexure mechanisms powered by skeletal muscle, evaluating how skeleton architecture and voltage- or current-based stimulation influence actuation output (SSA and UniCa).Altogether, the work presented in this thesis contributes to the field of biohybrid robotics by combining advanced fabrication, actuation control, integrated sensing, and regenerative capacity. These developments move us closer to robust, autonomous, and functional biohybrid machines for applications in soft robotics, tissue engineering, and biomedical research.
  
• PRIOR PALOMARES, OLIVIA: Quantifying Tumor Heterogeneity in Colorectal Liver Metastases with CT-Derived Habitats
  
  Author: PRIOR PALOMARES, OLIVIA
  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 Strength of Materials and Structural Engineering (RMEE)
  Mode: Normal
  Deposit date: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: PÉREZ LÓPEZ, RAQUEL
  Thesis abstract: In colorectal cancer, mortality is primarily driven by metastatic disease, most commonly to the liver. Colorectal liver metastases are biologically heterogeneous, composed of varying proportions of viable tumor cells, fibrosis, and necrosis. Both the presence and spatial organization of these tissue components influence treatment response and patient outcome. In clinical practice, however, such information is available only through biopsy, which samples a limited tumor region, or after surgical resection, which is feasible in only a minority of patients. As a result, most patients receive systemic therapy without direct knowledge of whole-tumor tissue composition.Computed tomography (CT) is the standard imaging modality for managing colorectal liver metastases and is acquired repeatedly throughout the disease course. Despite providing non-invasive, spatially resolved information at the whole-tumor level, clinical interpretation continues to focus largely on lesion size, number, and location. Consequently, the ability of CT to characterize intratumor heterogeneity has not yet been fully leveraged.Habitat imaging has been proposed as a framework for capturing tumor heterogeneity by partitioning tumors into spatial subregions with similar imaging properties (habitats). Most habitat imaging studies rely on multiparametric MRI (mpMRI), whose quantitative maps are biologically interpretable, while applications to CT remain limited despite its widespread clinical use. In addition, existing studies rarely assess the robustness of CT-derived features, often define habitats through purely data-driven optimization without biological grounding, and generally do not report clinical relevance beyond tumor volume.This thesis addresses these gaps by investigating whether routine CT can capture biologically and clinically meaningful intratumor heterogeneity in colorectal liver metastases. First, we identified 26 radiomic features suitable for robust CT-based habitat computation based on repeatability and reproducibility criteria. Second, we developed a biologically anchored CT habitat model by incorporating co-registered mpMRI as a reference during habitat definition, rather than relying solely on statistical optimization. Within this framework, we compared multiple CT representations, including handcrafted radiomic features and deep learning embeddings, and found that handcrafted features produced more biologically coherent habitats. The resulting three habitats reflected vascular architecture: an avascular core, a cellular, perfused intermediate zone, and a highly vascularized outer rim.Third, we evaluated clinical relevance by assessing associations between habitat-derived metrics and patient outcomes in two independent cohorts. Habitat metrics provided prognostic information beyond tumor volume, but only in specific treatment contexts. In particular, habitat entropy at the tumor–liver interface predicted survival in settings in which treatment may alter tissue composition without inducing measurable size changes. Across all treatment contexts, prognostic information consistently localized to the invasive tumor rim rather than being uniformly distributed throughout the lesion.Overall, this thesis contributes both methodological and clinical advances: an open-source CT habitat imaging pipeline, a comprehensive assessment of handcrafted radiomic feature robustness, the first comparison of CT representations for habitat computation, biological grounding of CT-derived habitats using mpMRI, and demonstration of their context-dependent clinical relevance. Together, these findings establish that routine CT scans contain clinically meaningful information about tumor heterogeneity that current assessment strategies do not capture, and provide a framework for extracting it.
  

DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING

• CUADROS ROJAS, EMERSON JULIO: Out-of-Plane Flexural Behaviour of Masonry Walls Reinforced with High-Strength Steel Cord Mesh
  
  Author: CUADROS ROJAS, EMERSON JULIO
  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: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: PELA, LUCA | ROCA FABREGAT, PEDRO
  Thesis abstract: Perforated brick masonry facades with exposed brickwork are a common feature in contemporary construction, yet they frequently demonstrate an out-of-plane response that renders them suscep-tible to wind and seismic action. Concurrently, innovative horizontal joint reinforcement systems utilising high-strength steel meshes are being adopted in increasing numbers in practice, although specific design provisions are still lacking. The present thesis investigates the mechanical behav-iour of perforated brick masonry walls reinforced with high-strength steel meshes. The investiga-tion focuses on out-of-plane bending response, and the thesis combines three different experi-mental programs in the laboratory, and numerical modelling.Initially, the experimental characterisation of the constituent masonry materials was conducted. Tests were carried out on perforated clay bricks and M5 mortar to provide their compressive and flexural strengths. Masonry prisms were subjected to compression tests and monitored using digi-tal image correlation (DIC) to determine the compressive strength, Young’s modulus and Pois-son's ratio. A methodology was proposed that utilised a co-barycentric effective area approach in order to account for the eccentricity induced by the asymmetric perforation pattern when evalu-ating compressive strength and stiffness.The shear behaviour of perforated brick masonry was the subject of a second experimental pro-gramme that involved triplet tests performed at three levels of pre-compression. The employment of DIC facilitated the observation of damage mechanisms and the estimation of Mohr-Coulomb strength parameters. The core of the research focuses on the execution of out-of-plane flexural tests of five unrein-forced masonry walls and six walls reinforced with high-strength steel mesh arranged with two different separations (0.6 m and 0.4 m, corresponding to geometric reinforcement ratios of 0.015% and 0.022%). The experimental programme was conducted in accordance with the four-point bending method specified in the standard EN 1052-2, and the damage process was moni-tored with three-dimensional digital image correlation (3D DIC). The reinforced walls demon-strated a substantial enhancement in strength and ductility in comparison to the unreinforced walls, higher overstrength ratios, and significantly greater ultimate displacements. The walls with a higher amount of bed-joint reinforcement exhibited a more distributed cracking with reduced crack widths, demonstrating crack control at low geometric reinforcement ratios compared to traditional reinforcement systems.An analytical model for the moment-curvature response and finite element micro-models were developed and calibrated based on the experimental results.
  

DOCTORAL DEGREE IN EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS

• ZAPATA FRANCO, ANA MARIA: Probabilistic Seismic Risk Assessment Integrating Soil Nonlinearity, Structural Response and Gender Perspectives
  
  Author: ZAPATA FRANCO, ANA 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 EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 04/02/2026
  Deposit END date: 17/02/2026
  Thesis director: VARGAS ALZATE, YEUDY FELIPE | GONZALEZ DRIGO, JOSE RAMON
  Thesis abstract: In recent years, soil–structure interaction (SSI) has become a key element in the estimation of seismic risk, as the soil beneath a structure acts as a filter that can amplify or attenuate the seismic response depending on its dynamic properties. This may lead to resonance phenomena in structures whose natural periods are close to those of the soil, increasing seismic demand and the probability of damage. In this regard, the growing use of advanced numerical models that explicitly incorporate SSI has significantly improved the understanding of this complex and nonlinear phenomenon.Accurate characterization of the dynamic response of soil profiles is therefore essential for a realistic assessment of seismic risk. The scientific literature emphasizes the importance of considering SSI, particularly the nonlinear behavior of soils, in the analysis of the seismic performance of structures located in areas of moderate to high seismic hazard, as well as critical infrastructure. To model these interactions, different approaches have been developed, ranging from simplified 1D models to three-dimensional finite element models capable of representing complex geometries, spatial variability, and multidirectional coupling.This research aims to deepen the understanding of the dynamic behavior of structures under realistic seismic conditions, with particular emphasis on SSI. The study analyzes seismic wave propagation through four main stages: i) probabilistic characterization of seismic motion at the bedrock level, ii) nonlinear propagation of waves through heterogeneous soil profiles, iii) evaluation of structural response under site-specific ground motions, and iv) incorporation of social vulnerability, especially gender-related inequalities, into probabilistic seismic risk estimation. This multistage approach enables the integration of engineering and social dimensions in a more comprehensive risk assessment.The research is based on two main hypotheses. The first proposes that advanced intensity measures, based on velocity and energy metrics, provide better predictive capability for seismic demand than traditional acceleration-based measures. The second argues that probabilistic modeling of soil properties within SSI frameworks enables more robust damage predictions than deterministic approaches. Finally, the integration of social factors such as income, housing conditions, and population exposure seeks to contribute to the development of more equitable and effective risk mitigation strategies, aimed at safer and more resilient built environments.
  

DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING

• IGLESIAS FERNÁNDEZ, MARC: Fundamentals of Calcium Phosphate Nanotopographies as Antibacterial Surfaces
  
  Author: IGLESIAS FERNÁNDEZ, MARC
  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 MATERIALS SCIENCE AND ENGINEERING
  Department: Department of Materials Science and Engineering (CEM)
  Mode: Normal
  Deposit date: 02/02/2026
  Deposit END date: 13/02/2026
  Thesis director: ESPAÑOL PONS, MONTSERRAT | GINEBRA MOLINS, MARIA PAU
  Thesis abstract: Bone defects exceeding a critical size require grafts that provide structural support while promoting bone regeneration. However, surgical implantation of these grafts carries a significant risk of infection, which can compromise graft integration and lead to host bone degradation. This challenge is exacerbated by the increasing prevalence of antibiotic resistance, underscoring the need for alternative antimicrobial strategies. Consequently, the development of synthetic bone grafts that combine osteogenic capacity with intrinsic antimicrobial functionality represents a major clinical and scientific priority.This thesis focuses on the development of synthetic calcium phosphate bone grafts featuring bactericidal nanotopographies effective against both Gram-negative and Gram-positive bacteria, and on elucidating the mechanisms underlying their antimicrobial action.Chapter 1 introduces the clinical motivation and scientific background of the study, providing an overview of implant-associated infections and a critical review of bactericidal nanotopographies reported in the literature, with emphasis on their key design parameters.Chapter 2 focuses on the synthesis, physicochemical characterization, and antimicrobial evaluation of two calcium-deficient hydroxyapatite (CDHA) nanotopographies obtained by hydrolysis of α-tricalcium phosphate under biomimetic and hydrothermal conditions. Both surfaces exhibit nanopillar-like architectures but differ in pillar size and interpillar spacing. The hydrothermally synthesized nanotopography, characterized by larger interpillar spacing, demonstrated superior bactericidal activity against the Gram-negative bacterium Pseudomonas aeruginosa. Ionic-exchange experiments showed that the released ionic species were not toxic to planktonic bacteria, indicating that surface nanotopography, rather than ionic release, is the dominant factor driving bacterial mortality.Chapter 3 investigates the interaction between CDHA nanotopographies and the Gram-positive bacterium Bacillus subtilis using synchrotron-based cryo–soft X-ray microscopy. Cryo-SXT revealed membrane rupture, cytosolic leakage, and multivesicular body formation in bacteria adhering to nanopillars. XANES spectromicroscopy identified a bacterial subpopulation with elevated intracellular calcium associated with substrate-derived ion release; however, this did not affect cell viability, consistent with the halotolerant nature of B. subtilis. Quantitative calcium estimation using linear absorption coefficients provided new insights into mechanochemical bacterial responses.Finally, Chapter 4 presents a time-resolved investigation of the bactericidal mechanisms exerted by CDHA nanotopographies against P. aeruginosa, integrating real-time multiplexed kinetic assays with sequential transcriptomic analyses. The kinetic data revealed four distinct phases: an initial adaptation period, metabolic activation without mortality, an abrupt metabolic collapse accompanied by a sharp increase in cell death, and a persistence phase in the surviving population. Transcriptomic profiling supported this progression, revealing early cell envelope stress and oxidative imbalance (2 h), followed by lipid peroxidation, glutathione depletion, iron dysregulation, and programmed cell death associated with mechanical membrane damage (5 h). At 7 h, global repression of metabolism and translation indicated entry into a persistence-like state, while at 24 h the surviving subpopulation showed partial metabolic reactivation and preparation for regrowth. Altogether, this chapter provides the first sequential genetic framework describing how calcium phosphate nanotopographies trigger mechano-induced oxidative damage leading to bacterial death and persistence.
  

DOCTORAL DEGREE IN PHOTONICS

• CAGETTI, MARTA: Integrated Charge Sensing and Electromechanics in Suspended Carbon Nanotube Quantum Devices
  
  Author: CAGETTI, MARTA
  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: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: BACHTOLD, ADRIAN | FORSTNER, STEFAN
  Thesis abstract: In this thesis we present an ultrasensitive, fast and widely tunable charge detection architecture, suitable for the readout of both electronic states and mechanical motion. The platform is implemented in suspended carbon nanotube (CNT) devices. Our approach employs a radiofrequency (RF) readout scheme operating without impedance matching, thereby avoiding one of the main practical limitations of conventional reflectometry. The readout achieves charge sensitivities exceeding state of the art RF detection techniques, while relying on a comparatively simple measurement setup. The device is based on an integrated single nanotube platform, in which a system of gate defined quantum dots and a proximal quantum dot based charge sensor are hosted in the same suspended CNT and separated by a short metallic drain electrode. The drain is connected to an RLC resonator with a resonance frequency fRLC approximately 1.25 MHz and a bandwidth of 50 kHz, enabling RF readout of the charge sensor current at the circuit resonance. This geometry provides strong capacitive coupling while maintaining independent electrostatic control of the sensor operating point and of the target quantum dots. Using this platform, we achieve self charge sensitivities of order 10^-7 e/sqrt(Hz) and an exceptionally low single shot infidelity, 1 - F approximately 10^-15, for an integration time tau approximately 3.5 microseconds. Beyond the readout of electronic charge transitions in the target quantum dots, the same charge sensor provides highly sensitive access to the mechanical degrees of freedom of the suspended nanotube in the system region. Mechanical displacement is transduced into variations of the charge sensor quantum dot conductance, enabling measurements ranging from driven nonlinear dynamics to thermomechanical motion in the few phonon regime. Crucially, our platform allows operation in a regime where electromechanical backaction, which is typical of suspended carbon nanotubes hosting quantum dots, is strongly suppressed. This addresses one of the central challenges of CNT based nanomechanics: in single dot electromechanical architectures, achieving strong or ultrastrong coupling generally requires operation near charge degeneracy, where coupling to electronic reservoirs and stochastic tunneling lead to excessive dissipation, frequency noise and a pronounced reduction of the mechanical quality factor. Indeed, in previous experiments in the ultrastrong coupling regime, measurement backaction broadened the mechanical response to the point of obscuring access to the intrinsic mechanical properties. In contrast, in our devices we maintain high readout sensitivity without any observable degradation of the mechanical quality factor Q, enabling quantitative spectroscopy of the resonator while preserving its intrinsic mechanical properties. This capability to perform quantitative spectroscopy of a nanomechanical resonator coupled to a two level system in the few phonon regime constitutes a key requirement for advancing towards experiments in the quantum regime, where preserving intrinsic mechanical coherence is essential. The high degree of tunability of our platform enables precise control of charge occupation, tunnel couplings and electrostatic potentials, allowing systematic studies of electromechanical coupling from the single electron regime in a simple quantum dot to the double quantum dot configuration. We demonstrate ultrastrong electromechanical coupling, opening the door to future work on nonlinear nanomechanics, mechanical qubits, quantum delocalization and carbon nanotube based quantum simulation.
  

DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS

• CASTREJON COMAS, VICTOR: Electroresponsive hyaluronic acid-based hydrogel for wound healing with real-time monitoring of bacterial metabolism to prevent infection
  
  Author: CASTREJON COMAS, VICTOR
  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: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: ALEMAN LLANSO, CARLOS ENRIQUE | PÉREZ MADRIGAL, MARIA DEL MAR
  Thesis abstract: Chronic skin wounds represent a major healthcare and socioeconomic challenge due to their high prevalence, prolonged healing times, and elevated risk of complications, particularly in conditions such as diabetic foot ulcers and vascular ulcers. In this context, the development of advanced wound dressings capable of promoting tissue regeneration while simultaneously monitoring the wound status constitutes a critical clinical need. Hyaluronic acid (HA), as a natural component of the skin extracellular matrix, stands out as an ideal biomimetic platform for the design of hydrogels intended for cutaneous wound healing, owing to its excellent biocompatibility, high water-retention capacity, and regulatory role in the wound-healing process.In this thesis, HA-based hydrogels crosslinked via click chemistry are developed using a three-arm polyethylene glycol (PEG) as a crosslinking agent, enabling the formation of well-defined three-dimensional networks under mild and biocompatible conditions. These hydrogels (clickHA) are designed to maintain a favorable moist environment, absorb wound exudate, and promote autolytic debridement, thereby contributing to the removal of necrotic tissue and to the reduction of bacterial burden. The trifunctional architecture of PEG allows precise control over the crosslinking density and, consequently, over the mechanical and structural properties of the hydrogel, ensuring adequate mechanical compliance with skin tissue and ease of clinical handling.The incorporation of a semi-interpenetrating network of a conducting polymer, poly[3,4-ethylenedioxythiophene-2-yl methanol] (PEDOT-MeOH), obtained by chemical oxidative polymerization of EDOT-MeOH monomers infiltrated into the clickHA matrix, endows the system with electro-responsive properties without compromising its structural integrity or biocompatibility. The influence of the infiltrated monomer concentration is systematically analyzed, demonstrating a progressive increase in electroactivity and the onset of electronic percolation at an EDOT-MeOH concentration of 0.05 M, above which effective conductive connectivity and reproducible electrochemical responses are achieved.Molecular dynamics simulations provide a mechanistic understanding of the internal organization of the system, revealing that EDOT-MeOH monomers aggregate into domains stabilized by π–π interactions that act as nucleation sites for polymerization, resulting in a homogeneous distribution of the conducting polymer within the HA matrix without altering its global structure. Finally, the electrochemical stability of the system and its application as an electrochemical sensor for the detection of NADH, a relevant biomarker of bacterial infection, are evaluated. ClickHA/PEDOT-MeOH hydrogels exhibit stable and selective electrochemical responses in the presence of interferents, both in model solutions and in bacterial culture media, enabling the early detection of infections. Overall, this thesis validates the clickHA/PEDOT-MeOH system as a robust multifunctional platform that integrates skin regeneration and electrochemical diagnostics, with high potential for translation into advanced smart wound dressings.
  

DOCTORAL DEGREE IN SUSTAINABILITY

• RAMIREZ RODRIGUEZ, MARIA SARAY: Fisheries Sustainability: Environmental, Economic, and Social Vulnerabilities, Addressing the Problem Through Food Waste
  
  Author: RAMIREZ RODRIGUEZ, MARIA SARAY
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SUSTAINABILITY
  Department: University Research Institute for Sustainability Science and Technology (IS.UPC)
  Mode: Normal
  Deposit date: 11/02/2026
  Deposit END date: 24/02/2026
  Thesis director: REIG PUIG, MARIA LOURDES | FERNÁNDEZ GUERRERO, DAVID
  Thesis abstract: Food security and a resilient food system are aims to ensure the future of humanity in a scenario of several threats, such as climate change, the decreasing trend in available resources, the emergence of virulent diseases, global conflicts affecting supply chains, etc. Providing solutions to these issues is so vital that within the Sustainable Development Goals (SDG), sustainable production and consumption is a stated goal (nº 12), and the reduction of Food Losses and Waste (FLW) has become one of the tools for achieving this goal (nº12.3). . This study aims to contribute in FLW reduction for the fish sector, decreasing its negative impacts and increasing the sustainability of the fish sector activity. Moreover, the goal of the thesis is also to reduce fish sector vulnerability, by identifying weak points and possible areas of improvements with a focus on economic and social sustainability, but without forgetting an environmental approach.The methodology combines qualitative and quantitative methods. Public databases were used but also own data was generated by including fish sector stakeholders in the study’s development by surveys, interviews and participatory dynamics. Spain was chosen for the geographical scope due to several factors, such as its high volume of catches, consumption and international trade in fishery and aquaculture products, both in the European and global contextThe thesis is structured in the following way. Chapter 1 was developed as a diagnosis of FLW in the fisheries sector. FLW were quantified and causes, and prevention measures were detected through the use of a standardized methodology. Furthermore, two species were selected to represent Spanish fish sector based on consumption and catches. Anchovy (Engraulis encrasicolus) was chosen to represent oily fish and Hake (Merluccius merluccius) for representing lean fish. As a result, we provided FLW estimations using standardized methodologies, which allows for comparison with future research. Furthermore, our contribution enables the formulation of mitigation and prevention actions. After the diagnosis stage, interventions were designed and tested, trying to approach the problems identified in the diagnosis stage.Chapter 2 tries to improve the resilience of the fisheries sector in Catalonia by developing a market intervention for the expansion of target species. Priority was given to local species, favored by climate change, and which are currently being wasted both nutritionally and economically, due to their low commercial interest. The selected species was Sardinella aurita, which was also validated by local fishermen as a good candidate for the market intervention. The market intervention contributes to increase the economic value of catches by offering alternative products made from low-value species. Moreover, it approached consumers toward local species by adding value to proximity and offering more convenient consumption methods for unskilled consumers. On the other hand, in Chapter 3 another mitigation action was proposed in order to reduce FLW and the economic devaluation of products due to consumer concerns about food safety and aesthetic reasons. As was detected during the diagnostic stage, Anisakis negatively affects the fish sector. It is necessary to inform consumers correctly by developing communication tools that focus on risk avoidance and the social and health benefits of consuming fish. This chapter proposed and tested communications to decrease the perception of food risk towards Anisakis and increase fish consumption.Finally, recommendations have been formulated for each stage of the fish FSC to reduce FLW and increase economic profit, as well as to propose strategies to promote sector’s resilience. These recommendations include strong collaboration and better communication between stages and withpolicymakers, as well as promoting fish culture to increase consumption and reduce food safety concerns.
  

DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE

• DE SANTIAGO GARCIA, JAVIER NICOLAS: La imagen poética en los procesos de producción, proyectuales y habitar de la vivienda de autoproducción en Lomas del Centinela.
  
  Author: DE SANTIAGO GARCIA, JAVIER 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 THEORY AND HISTORY OF ARCHITECTURE
  Department: Department of History and Theory of Architecture and Communication Techniques (THATC)
  Mode: Normal
  Deposit date: 09/02/2026
  Deposit END date: 20/02/2026
  Thesis director: USANDIZAGA CALPARSORO, MIGUEL M. | SERRA PERMANYER, MARTA
  Thesis abstract: This thesis addresses the search for the poetic image in self-built housing in the Lomas del Centinela neighborhood, in Zapopan, Jalisco, Mexico. This search focuses on some of the processes identified with self-built housing, particularly in the production processes, design processes, and the dwelling process.The concept of poetic image is constructed through the discourses of authors such as Gaston Bachelard, Carlos González y Lobo, Steven Holl, Manuel Martín Hernández, Juhanni Pallasmaa, and Alberto Pérez-Gómez. It can be defined as the element that results from having imagined something with a specific purpose in mind. It is referred to as an element because it can manifest as a thought, a written text, a goal, a conceptual drawing, a method to achieve an end, a way of experiencing a place, of appropriating it, and of recognizing oneself in that journey.This study examines women from Lomas del Centinela who have self-built their homes, approaching their history and the forms of production they engaged in during the years they, along with their families, pursued the dream of building their own homes.During this research, they were interviewed, seeking in their discourses elements that could be considered poetic images, with the aim of exploring their self-building processes through the lens of the poetic image. Through this search, not only is the importance of imagination emphasized, but also the fact that self-building processes are not spontaneous. Rather, in much of their conception, construction, and inhabitation, they respond—beyond the management of minimal resources—to a strong imaginative component. This entails a profound reflection on the potential of self-built housing in terms of creative achievement.