Public display of deposited theses

DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE

• GONZÁLEZ GUTIÉRREZ, CÉSAR: Analyzing and Leveraging the Structure of Pre-trained Embeddings
  
  Author: GONZÁLEZ GUTIÉRREZ, CÉSAR
  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: 27/11/2025
  Deposit END date: 11/12/2025
  Thesis director: QUATTONI, ARIADNA JULIETA
  Thesis abstract: Developing models with limited annotation budgets (few-shot learning) is of great importance due to the high costs associated with data annotation.Recent advances in text classification have demonstrated that representations derived from pre-trained language models play a crucial role, especially in few-shot learning settings. These new advancements raise two natural questions:1) What properties of pre-trained representations can explain their effectiveness in few-shot learning?, and2) Can we leverage these properties to further enhance performance under limited annotation conditions? In the first part of this work, we address the first question and show that the effectiveness of pre-trained representations in few-shot scenarios can be explained by the degree of alignment between supervised task labels and the hierarchical structure of the pre-trained embedding space. In the second part, we propose a label propagation method designed to exploit this alignment, leading to improved performance in few-shot classification tasks.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• DEHGHANSOURAKI, DANIAL: Modeling Sediment Transport in Rivers and Reservoirs using an Accelerated Model
  
  Author: DEHGHANSOURAKI, DANIAL
  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: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 04/12/2025
  Deposit END date: 18/12/2025
  Thesis director: BLADE CASTELLET, ERNEST | LARESE DE TETTO, ANTONIA
  Thesis abstract: Reservoir sedimentation is a critical, ongoing issue in managing water resources sustainably. While conventional two-dimensional models are computationally efficient, they miss key three-dimensional processes, such as thermal stratification. Three-dimensional models provide a more accurate physical representation but require extensive computational resources, making them impractical for large-scale applications. This research creates a computational framework that combines High-Performance Computing, Artificial Intelligence, and advanced 3D multiphysics simulation to bridge this gap.A two-dimensional hydro-morphodynamic model (R-Iber) was rebuilt for Graphics Processing Units, resulting in computational speed-ups of one to two orders of magnitude. The accelerated model supported training a Deep Neural Network surrogate, enabling a 100,000-run Monte Carlo analysis for robust model calibration and uncertainty quantification. In parallel, a comprehensive three-dimensional multiphysics model was developed in the Kratos framework to simulate the 3D fluid-thermal problem.The integrated approach was used for the Riba-roja reservoir system. It measured how thermal stratification affects sediment trapping efficiency. Results show that combining HPC, AI, and multiphysics modeling leads to practical and actionable methods for sustainable reservoir management.
  

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

• ALCÓN DOGANOC, MIGUEL: Verification and Validation Solutions for the Safety Compliance of Autonomous Driving Frameworks Performance Aspects
  
  Author: ALCÓN DOGANOC, MIGUEL
  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: 01/12/2025
  Deposit END date: 15/12/2025
  Thesis director: ABELLA FERRER, JAIME | MEZZETTI, ENRICO
  Thesis abstract: Autonomous Driving (AD) has rapidly evolved from a research concept into an industrial reality. The increasing computational demands of autonomous vehicles have motivated the use of high-performance Multi-Processor Systems-on-Chip (MPSoCs), which offer both performance and energy efficiency. However, ensuring the safety compliance of such complex systems remains a major challenge. The software frameworks used to implement AD functionalities—typically integrating Artificial Intelligence (AI) algorithms—are not designed following a safety-driven development processes, and their non-deterministic behavior conflicts with the strict determinism required by safety standards. This thesis addresses these challenges by developing Verification and Validation (V&V) solutions that improve the safety compliance of AD frameworks, with a particular focus on performance-related aspects.The thesis begins by analyzing the main sources of non-determinism in AD systems across three layers: algorithmic, software architectural, and hardware platform. While variability exists in all layers, the software architecture layer is identified as a key contributor to the overall unpredictability. It not only introduces its own sources of variability but also amplifies those inherited from the other layers. This makes software architecture an effective focal point to improve system determinism and safety assurance.At the foundational level, the thesis addresses the challenge of unit testing within already-integrated AD frameworks, using the open-source Apollo AD framework as a case study. Due to tight coupling and data dependencies among its modules, Apollo does not easily support independent module validation. To enable proper verification of software units, the thesis proposes a systematic methodology to isolate, modify, and reconfigure Apollo modules into standalone, testable units, thus reintroducing unit-level testing capabilities into a complex, AI-based AD framework.The work advances toward system-level safety assurance through the development of dynamic and execution views of Apollo. Dynamic views describe the interactions among software components, linking safety requirements with their implementation and validation tests. However, these views alone fail to capture the concurrent behavior and execution parallelism of the system, which are crucial for verifying performance-related safety requirements. To fill this gap, the thesis introduces execution views, which complements dynamic views by integrating runtime information gathered from execution tracing on MPSoC platforms. Execution views enhance the observability of resource usage, timing behavior, and concurrency, allowing both improved testing and optimized hardware utilization—key aspects for reducing cost and ensuring safety.Finally, the thesis addresses the timing behavior and variability across software components. It identifies, formalizes, and applies a comprehensive set of timing-related metrics capable of capturing inter-module interactions and end-to-end latency properties in AD applications. Traditional timing metrics, such as worst-case execution and response times, fail to capture the interdependencies between components in systems like Apollo. By adopting complementary metrics such as maximum reaction time and maximum time displacement, the proposed approach provides deeper insights into timing dependencies, enabling early detection of timing anomalies and improving validation confidence.Overall, this thesis provides a set of methodologies and tools to improve the V&V of AD software from a safety-performance perspective. The proposed contributions bridge the gap between high-performance AI-based software and the stringent determinism required by safety standards. These advances support the systematic assurance of safety in AD frameworks, ultimately contributing to the reliable and certifiable deployment of autonomous vehicles on high-performance embedded platforms.
  
• GIESEN LEÓN, JEREMY JENS: Modeling and Optimization of Timing Interference for Time Critical Systems on Multicore COTS Platforms
  
  Author: GIESEN LEÓN, JEREMY JENS
  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: 27/11/2025
  Deposit END date: 11/12/2025
  Thesis director: MEZZETTI, ENRICO | CAZORLA ALMEIDA, FRANCISCO JAVIER
  Thesis abstract: Critical Real-Time Embedded Systems (CRTES) underpin automotive, aerospace, medical devices, among others. They must guarantee deterministic, certifiable behavior under worst-case conditions. As functionality grows (sensor fusion, AI, etc), uniprocessors fall short, prompting adoption of COTS multicores. Yet shared resources induce timing interference that threatens predictability and complicates certification, especially in heterogeneous SoCs with crossbars, bridges, and hierarchical memory.This Thesis advances timing predictability on complex multicores through three linked pillars: standardized hardware observability, contention modeling, and system-level optimization. Together they form a coherent, auditable path from low-level measurements to design decisions.First, we introduce unified observability frameworks combining core-local counters with system-level tracing. They correlate hardware events with task phases, reconstruct scheduling and contention across cores and interconnects, and standardize configuration and interpretation across heterogeneous devices. Measurements are attributed to tasks (excluding OS activity), incur bounded overhead, and yield ordered access sequences preserving temporal structure. Along with latency tables for memories and bridges, these artifacts make timing phenomena measurable and calibrate conservative models.Second, we develop contention models grounded in realistic traces. Traditional Access-Count Contention Techniques (ACCT) are overly conservative for parallel crossbars. Sequence-Aware Techniques (SACT) exploit request ordering to prune infeasible overlaps and tighten bounds. We propose ASCOM, a scalable framework balancing accuracy through compositional pairing against contender sequences and segmentation of long traces. We derive explicit upper/lower bounds to quantify margins and add bridge awareness to capture inter-cluster traversals and remote-memory asymmetries. Across single- and multi-crossbar SoCs, sequence-aware analysis yields tighter, trustworthy bounds while remaining tractable on industrial-scale traces.Third, we examine how modeling informs code and data placement across heterogeneous memories. Feasibility considers capacity and compatibility; locality and non-uniform latencies are captured through calibrated SACT. Exploration reveals pronounced sensitivity to placement: with identical workloads and schedules, changing only the mapping can shift contention by over 100% of reference execution time, due to bridge traversals, device asymmetries, and port effects. Architectural factors thus directly shape worst-case interference, elevating placement to a first-order design parameter.An end-to-end workflow operationalizes these ideas. System-level traces are captured on an industrial target hardware. Traces are filtered into ordered access sequences retaining temporal structure and feeding SACT analysis. Empirical campaigns build latency tables for memories and bridges. With these calibrated inputs, the bridge-aware SACT model estimates contention and total delay for alternative placements.Results show robust contention analysis on COTS multicores is feasible when: (i) the right signals are observed with standardized, low-intrusion instrumentation; (ii) models are sequence- and bridge-aware with explicit margins; and (iii) insights drive placement where locality and capacity are addressed coherently. Because ordered sequences, latency tables, and task-scoped metrics come from the deployed hardware, conclusions are auditable and fit safety cases. Combining hardware-aware instrumentation, realistic modeling, and contention-driven mapping, the Thesis provides a practical framework for timing predictability in CRTES and narrows the gap between certification expectations: traceability, explainability, repeatability and the behavior of parallel interconnects and heterogeneous memories in contemporary multicore SoCs.
  

DOCTORAL DEGREE IN COMPUTING

• NJOKU, UCHECHUKWU FORTUNE: Towards Effective and Interpretable Many-Objective Feature Selection in Machine Learning
  
  Author: NJOKU, UCHECHUKWU FORTUNE
  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 COMPUTING
  Department: Department of Computer Science (CS)
  Mode: Change of supervisor
  Deposit date: 04/12/2025
  Deposit END date: 18/12/2025
  Thesis director: ABELLO GAMAZO, ALBERTO | BILALLI, BESIM | BONTEMPI, GIANLUCA
  Thesis abstract: Effective Machine Learning (ML) requires more than just accurate models; it also demands consideration of factors such as model complexity, fairness, and other task-specific requirements. Fulfilling these requirements begins at the data level by selecting features that con-tribute to addressing these concerns. This can benefit from a many-objective optimization approach to Feature Selection (FS).This thesis, therefore, studies Many-Objective Feature Selection (MOFS) and contributes to the development of efficient and responsible ML solutions. However, due to the large number of MOFS solutions, it comes with an interpretability challenge. Therefore, we also aim to propose a methodology for tackling this limitation of MOFS.Although FS has been long researched, previous work (on both filter and wrapper methods) has failed to address this gap by focusing only on one or at most two objectives. Also for the interpretability of FS results, no methodological approach has been proposed and rather a basic tabular representation has been used.We propose a framework that uses non-dominated sorting genetic algorithms to balance important and often conflicting objectives for FS. In particular, more than four to fifteen objectives could be considered with this method. For interpretability, our proposed methodology consists of six steps that consider three viewpoints: objectives, solutions, and variables (i.e., features).To achieve the research goal, we follow a structured approach: first, an extensive literature review that establishes the state-of-the-art and identifies open challenges. Next, empirical analyses of single-objective filter and wrapper methods, as well as multi-objective wrapper methods, are conducted to assess their strengths and limitations. Our MOFS framework is then proposed and evaluated through multiple experiments, including its application to fairness in ML. Finally, the interpretability methodology is instantiated as an interactive dashboard, which is validated through an experimental study involving 50 participants, with statistical analysis to assess its effectiveness.The findings highlight that no single FS method is universally optimal; instead, the best approach depends on dataset characteristics, task requirements, and objectives. While filter methods are computationally efficient and wrapper methods enhance model performance in single-objective settings, the proposed MOFS framework successfully balances multiple conflicting indicators related to performance, complexity, and fairness. Moreover, the interpretability methodology proved essential in helping data scientists to better understand MOFS results, enabling informed decision-making in FS.
  

DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING

• ROYANO GARCIA, VERÓNICA: A Function-Oriented Assessment Methodology (FOAM) for life-cycle monitoring of building functional condition
  
  Author: ROYANO GARCIA, VERÓNICA
  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: 27/11/2025
  Deposit END date: 11/12/2025
  Thesis director: SERRAT PIE, CARLES | RAPINSKI, JACEK TOMASZ
  Thesis abstract: The effective management of the aging building stock is currently hindered by two critical gaps: the lack of a standardized common language for data exchange and the limitations of existing assessment paradigms. Current methodologies prove insufficient: defect-based approaches prioritize physical integrity over the direct evaluation of functional condition, while serviceability models rely on variable, context-dependent user requirements. These limitations render current approaches unsuitable for objective, longitudinal analysis of functional performance. To address these challenges, this doctoral thesis presents the development and validation of the Function-Oriented Assessment Methodology (FOAM), a comprehensive framework designed for the objective, life-cycle monitoring of the functional condition of construction elements.The methodology is established upon four fundamental contributions: (i) adopting the international ISO/IEC 81346 standard to ensure rigorous and interoperable element classification; (ii) conceptualizing the Element-Function (E-F) network, a hierarchical structure that links construction elements to their functions and defines the aggregation weights; (iii) operationalizing data collection through the Functional Condition Assessment Questionnaire (FCAQ), enabling the transformation of subjective inspections into standardized discrete data; and (iv) developing a mathematical engine that translates these data into a continuous, time-dependent Functional Condition Index (FCI).The statistical behavior of the proposed estimator, (FCI) ̂(t), has been rigorously validated through a comprehensive in silico simulation study comprising 2,187 scenarios modeled using a Generalized Estimating Equations (GEE) approach. The results demonstrate that the estimator is statistically sound, confirming its unbiased nature and √n-consistency. A critical finding of the sensitivity analysis is that the methodology is highly robust to random inspector variability but extremely sensitive to systematic inspector bias. This establishes that unbiased inspection protocols are a non-negotiable prerequisite for reliable estimation. Furthermore, the analysis identifies the functional degradation pattern and the evaluation time as the dominant factors influencing the predictive capacity of the model.Beyond theoretical validation, the practical applicability of the framework has been demonstrated through the development of the FastFoam web platform, achieving a Technology Readiness Level (TRL) 7. This thesis concludes that FOAM resolves the assessment paradigm, overcoming subjective, defect-based approaches towards an objective, function-based methodology, providing a robust tool to support well-informed decision-making in asset management and the long-term preservation of the built environment.
  

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

• RODRÍGUEZ ROMERO, CARLOS EDUARDO: Analysis of coupled hydro-mechanical processes in double-structure geomaterials for nuclear waste storage
  
  Author: RODRÍGUEZ ROMERO, CARLOS EDUARDO
  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: 04/12/2025
  Deposit END date: 18/12/2025
  Thesis director: VAUNAT, JEAN | GENS SOLE, ANTONIO
  Thesis abstract: The safe long-term isolation of high-level radioactive waste requires engineered barriers capable of maintaining low permeability and mechanical stability under complex thermo-hydro-mechanical (THM) conditions. Among candidate materials, compacted bentonite exhibits a distinctive double-structure behaviour, governed by the coexistence of micro- and macro-porous domains. This thesis focuses on the analysis of coupled hydro-mechanical processes in double-structure geomaterials, with particular attention to bentonite mixtures of blocks and pellets, as used in buffer systems for deep geological repositories. The research first reviews the geomechanical basis of double-structure soils and identifies the experimental evidence supporting their dual-porosity nature. A constitutive THM framework is then developed, extending the existing double-structure formulation to incorporate: (i) the parameter ακ to control microstructural deformation; (ii) a fabric-dependent structuration law to represent the memory and degradation of compression; and (iii) frictional resistance at block–pellet and block–wall interfaces.The model was implemented and calibrated using laboratory and mock-up experiments from the BEACON project, including the MGR22, MGR23, and MGR27 experiments, the EPFL path-dependent tests and the POSIVA test. Numerical simulations successfully reproduced the evolution of swelling pressure, void ratio, dry density, water content and water intake observed experimentally. The results confirmed that friction plays a decisive role in the redistribution of stresses between pellets and blocks, while microstructural evolution governs the long-term homogenisation process. The enhanced formulation captured partial density homogenisation and the persistence of microstructural porosity, in agreement with laboratory observations.Overall, the thesis provides an improved understanding of the coupled hydro-mechanical behaviour of double-structure bentonites and proposes a robust constitutive framework capable of reproducing their key features under repository-relevant conditions. The work highlights the necessity of considering both microstructural evolution and frictional effects in predictive models for bentonite barriers, thus contributing to the reliability of long-term safety assessments of deep geological repositories.
  

DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING

• LU, YONGGANG: Research on Transient Flow Characteristics and Dynamic Behaviour of hydraulic Pumps in Support of Energy transition
  
  Author: LU, YONGGANG
  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: Article-based thesis
  Deposit date: 26/11/2025
  Deposit END date: 10/12/2025
  Thesis director: PRESAS BATLLÓ, ALEXANDRE
  Thesis abstract: Amid the global shift to low-carbon energy, multi-energy complementary power systems are key to achieving carbon neutrality. Nuclear energy, pumped storage hydropower, and industrial waste energy recovery enhance energy system flexibility but increase demands on energy transfer and fluid transport. Hydraulic pumps, vital for energy conversion, face challenges: RCPs in Generation IV lead-cooled reactors suffer from corrosion and vibration; pumped storage units face stability issues; and industrial waste pressure recovery is inefficient under variable conditions. This study focuses on three core devices—RCPs, pump-turbines, and PATs—using analysis, simulation, and experiments to investigate their dynamics and propose optimizations.First, the transient fluid-structure interaction of lead-bismuth eutectic RCPs during startup was studied. A mathematical model for flow rate and rotational speed under various startup modes was developed. Bidirectional fluid-structure interaction analysis showed maximum stress at the impeller blade root and maximum deformation at the blade-hub/shroud junction. Higher startup torque increased acceleration and torsional shock, with peak stress linked to instantaneous rotational speed. These findings inform safer RCP startup design.Second, the dynamic characteristics of reversible pump-turbines under load rejection were studied using 3D transient simulations and entropy production theory to analyze energy loss. The study found the unit crosses the S-shaped region during load rejection, with complex flow under reverse pump conditions. When speed exceeded 110%, significant fluctuations in axial hydraulic thrust and torque were observed, and blade pressure loads became asymmetric. These findings improve understanding of pump-turbine transient behavior.Finally, a two-stage PAT system for high-pressure energy recovery in petrochemicals was studied, focusing on vortex evolution and pressure pulsations. Pulsations in the diffuser stemmed from rotor-stator interaction near the tongue, with strong inter-stage interference at the inlet impeller. Low-frequency pulsations from vortex shedding were detected at high flow rates, threatening system stability. Combined experiments and simulations clarified pulsation propagation, aiding inter-stage matching and efficiency improvements.The innovative results of this study have been published in leading fluid mechanics and energy journals. They advance the theoretical understanding of hydraulic pump dynamics and provide practical solutions for nuclear safety, grid flexibility, and industrial energy conservation. The main body of the dissertation details each research component, with three supporting JCR Q1 articles appended.
  

DOCTORAL DEGREE IN PHOTONICS

• ARRÉS CHILLÓN, JAVIER: Application to Sensing, Imaging, and Cooling of Ultra-Thin Metal Films and Derived Nanostructured Glass Surfaces
  
  Author: ARRÉS CHILLÓN, JAVIER
  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: 04/12/2025
  Deposit END date: 18/12/2025
  Thesis director: PRUNERI, VALERIO
  Thesis abstract: The continuous evolution of optoelectronic systems responds to the demand for higher efficiency, speed, and sensitivity. A key strategy is to modify material dimensions at the nanoscale, which alters their optical, electrical, and thermal properties and enables new functionalities.A prominent example is ultra-thin metal films (UTMFs), with thicknesses below 10 nm, which exhibit properties different from thicker metal layers. This thesis explores the use of gold (Au) UTMFs deposited on copper oxide (CuO) seed layers, fabricated with industrial techniques such as physical vapor deposition (PVD). These ultra-thin films enable continuous and ultrasmooth surfaces, as well as tunable properties through optical or electrical processes.The potential of these UTMFs in electrochemical sensors based on self-assembled monolayers (SAMs) is demonstrated. The results show that thinner films respond more rapidly to SAM formation, and that biotin functionalization enables the detection of streptavidin through measurable resistance changes.The optical interaction between UTMFs and fluorophores is also investigated, focusing on fluorescence quenching caused by non-radiative energy transfer. Experiments reveal the dependence on film thickness and fluorophore–metal separation, confirming that these films can enhance the signal-to-noise ratio in fluorescence imaging of stained bacteria.Finally, glass surfaces are nanostructured with nanopillars (NPs) generated via thermally dewetted UTMF masks and subsequent etching. These surfaces exhibit unique optical properties: anti-reflective coatings in the visible range and enhanced infrared emissivity. Moreover, they are combined with thin polymer coatings to preserve visible transparency while improving the efficiency of passive radiative cooling (PRC). Results confirm that nanostructured glass surfaces dissipate more heat than flat ones, opening opportunities in solar panels, displays, and windows.This thesis therefore demonstrates the potential of Au UTMFs and nanostructured glass surfaces for the development of chemical sensors, advanced optical microscopy techniques, and radiative cooling applications.
  
• TYULNEV, IGOR: Investigation and Control of Phase Transitions by Ultrafast Strong-field Techniques
  
  Author: TYULNEV, IGOR
  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: 10/12/2025
  Deposit END date: 24/12/2025
  Thesis director: BIEGERT, JENS
  Thesis abstract: This work presents the experiments and results on the application of mid-infrared laser sources towards condensed matter systems for the study and control of manybody interactions within material phases and at phase boundaries. Utilizing the decades in know-how and development of intense, few-cycle waveforms at high repetition rates, the here demonstrated applications leverage the mid-infrared wavelengths to study and control strong-field phenomena at ultrafast time-scales and across phase transitions. To this end non-linear techniques are employed to extend the source capabilities towards a variety of driving and probing wavelengths, meanwhile tailoring spin-angular momentum multi-color beams as driving fields with unique patterns. With strong-field driven dynamics happening at sub-cycle time scales, techniques such as high harmonic generation (HHG) are applied to a variety of materials which undergo electronic and structural transitions. For bulk transition metal dichalcogenides, as the investigated MoS2, the induced spatial and temporal symmetry breaking from a tailored trefoil-shaped strong-field allowed the detection of valley polarization, i.e. a carrier population imbalance between neighboring bandgap extrema. The specific control of the energy bands at these sites, first, allows the realization of a valley switch to be used for optical computing, and second, realizes a hybrid system of light and matter with band topology akin to the Haldane model, which paves the way towards field-induced and controlled topological phase transitions in two-dimensional materials. Furthermore, the field-induced currents and the emerging harmonics are used to probe the potential landscape of the lattice and therefore, simultaneously detect signatures of the crystal and band structure encoded in a static spectrum. Interference within the spectra further reveal the underlying electron-hole dynamics and timings. In high-temperature superconducting ceramics like YBCO, the temperature induced changes in electronic properties are also sensitively detected via HHG, even for more elusive material phases. Meanwhile higher order transitions like the correlated charge density wave (CDW) phase shows a mixture of electronic and structural changes in the HHG crystallography as investigated in TiSe2. The macroscopic and nonlinear approach yields major changes in the harmonic spectra even from small changes in e.g. atom displacement and identifies phase anisotropies which eluded conventional or microscopic techniques.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• GIL DÍAZ, CRISTINA: Characterization of cirrus clouds and dust aerosols with remote sensing: application of radiative transfer models for the study of their radiative effects
  
  Author: GIL DÍAZ, CRISTINA
  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: Article-based thesis
  Deposit date: 09/12/2025
  Deposit END date: 22/12/2025
  Thesis director: SICARD, MICHAEL
  Thesis abstract: Clouds and aerosols are key modulators of the Earth’s radiative balance, yet their interactions remain among the largest sources of uncertainty in climate projections. This Ph.D. thesis investigates aerosol–cloud–radiation processes at mid-latitudes, with emphasis on cirrus clouds and mineral dust, by combining long-term ground-based lidar measurements, radiative transfer modelling, and regional climate simulations.First, a multi-year dataset of MPLNET lidar measurements in Barcelona was analyzed to characterize the geometrical and optical properties of cirrus clouds and to quantify their direct radiative effect. Cirrus occurrence was high, with marked seasonal variability. Distinct radiative behaviours were identified: at nighttime, cirrus clouds warm both top-of-the–atmosphere and bottom-of-the–atmosphere, while during at daytime they consistently warm top-of-the-atmosphere and predominantly cool bottom-of-the-atmosphere.Second, the semi-direct radiative effects of Saharan dust during a coupled dust and heatwave event were assessed with a regional climate model over the Iberian Peninsula. Results highlighted the importance of spectral nudging for an accurate simulation and showed that dust absorption modifies thermodynamic profiles, cloudiness, and the surface energy balance, thereby partially mitigating heatwave impacts. These responses were spatially heterogeneous, reflecting the strong dependence of dust–radiation interactions on dust distribution and meteorological conditions.Third, the role of the dust giant mode and the dust conversion factors for calculating cloud condensation nuclei and ice-nucleating particle concentrations were examined. Incorporating a synthetic giant mode significantly improved the agreement with reference datasets for the dust direct radiative effect, despite inherent uncertainties and idealized assumptions. In addition, dust conversion factors were derived from AERONET and MPLNET lidar measurements, demonstrating the potential of lidar to provide vertically resolved proxies for aerosol indirect effects.