Doctoral School

Reading date: 29/10/2025

• MEHABA, WAFA: The effect of promotions on consumer purchasing behavior
  
  Author: MEHABA, WAFA
  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: 02/10/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: GIL ROIG, JOSE MARIA
  Thesis abstract: The retail industry has long had to contend with a more competitive and complicated environment. Changes in consumer behaviour, market structures, and public health concerns have drastically altered this environment over the last 20 years. Furthermore, the importance of promotional differentiation increased as a result of economic crises, inflation, dwindling consumer purchasing power. Retail sales promotions present significant opportunities to reshape and influence the consumer behaviour. Considering their direct impact on expenditures patterns, it is crucial to understand the multifaceted promotional effects.In this context, the overall objective of this dissertation is studying the effect of sales promotions on consumer purchasing behaviour across different contexts. Three consumer studies were conducted, examining promotional effects on budget allocation, crisis driven behavioural changes and health related policy implications using Homescan data from Kantar Worldpanel. First, the effect of retail sales promotions on the allocation of the household food budget among the items of the shopping basket was investigated in Catalonia, Northeast region in Spain. Using Homescan data from purchases of a supermarket, own and cross-promotion elasticities were calculated using the Exact Affine Stone Index (EASI). Results reveal positive effects of sales promotions on households’ expenditure and mostly a negative asymmetric cross-effect, implying a small but significant budget reallocation.Second, purchasing behaviour changes during crisis periods were analysed using COVID-19 pandemic as a case study. Price sensitivity and promotional responsiveness were examined across different crisis phases and expenditure levels using both fixed effects regression and quantile regression models. Homescan data covering the period the first year of COVID-19 and the year before are used. The results indicate that households exhibit a decreased price sensitivity and reduced promotion responsiveness during the first lockdown followed by increased sensitivity during the new normality period. Additionally, during first lockdown, low expenditure households are more sensitive to prices and promotions than high expenditure households. Third, a cross-country comparative analysis is conducted. The relationship between retail sales promotions and Body Mass Index (BMI) is examined using the EASI demand system, comparing northern (Scotland) and southern (Spain) regions. The analysis focuses on foods High in fat, Sugar and Sodium (HFSS) across different BMI profiles. Findings indicate that consumers with unhealthy BMI exhibit higher sensitivity to price and expenditure changes compared to those with healthy BMIs. Moreover, Scottish households show greater sensitivity to expenditure changes and promotions compared to their Spanish counterparts.The research conducted in this dissertation provides valuable insights to retailers, policymakers, and other stakeholders involved in the food retail sector. The outcomes of this dissertation can guide promotional strategy design, pricing decisions, and policy interventions to meet consumer needs while addressing broader societal concerns including crisis management and public health objectives.
  

Reading date: 30/10/2025

• MHATRE, SUVIDHA SUDHAKAR: AI-Enabled Network Slicing and Resource Management for Open and Programmable Next-Generation (6G) Networks
  
  Author: MHATRE, SUVIDHA SUDHAKAR
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 01/10/2025
  Reading date: 30/10/2025
  Reading time: 10:00
  Reading place: FIB, Sala de Juntes, B6 - planta 1
  Thesis director: VERIKOUKIS, CHRISTOS | RAMANTAS, KONSTANTINOS
  Thesis abstract: This thesis addresses the emerging challenges in resource management for 6G networks by proposing intelligent, scalable, and explainable solutions using Deep Reinforcement Learning (DRL) and related AI techniques. With the evolution from 5G to 6G, the increasing heterogeneity of applications and services introduces complex requirements in terms of latency, bandwidth, computational efficiency, and end-to-end quality of service (QoS). The research presents a suite of AI-driven solutions for dynamic and adaptive resource allocation tailored to network slicing scenarios in Open and Programmable architectures.The work begins by developing a DRL-based, QoS-aware slice resource allocation framework, integrating user association parameterization for beyond-5G O-RAN environments. A hierarchical DRL model is introduced to manage global-local resource trade-offs efficiently. This is extended by proposing a multi-time scale resource management framework under an AI-as-a-Service (AIaaS) paradigm to serve heterogeneous 6G services.To improve interpretability and trust in automated network operations, the thesis incorporates Explainable Reinforcement Learning (XRL) techniques into RAN slicing and management strategies. Finally, the use of transfer learning in DRL is explored to enhance policy adaptation in intra- and inter-slice domains, accelerating learning and improving performance in diverse and dynamic network conditions.The thesis includes extensive simulations and experimental validation to demonstrate the superiority of the proposed methods in terms of scalability, efficiency, and generalization over state-of-the-art (SOTA) baselines. The overall contributions provide a technically innovative and practically applicable roadmap for intelligent, trustworthy, and adaptive resource management in future 6G wireless systems.
  

Reading date: 31/10/2025

• BILBAO VILLA, AINARA: Palabras de luz: Herramientas léxicas y gráficas para la definición de los principales términos empleados en la descripción de la distribución lumínica en el espacio arquitectónico.
  
  Author: BILBAO VILLA, AINARA
  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: Normal
  Deposit date: 01/10/2025
  Reading date: 31/10/2025
  Reading time: 11:30
  Reading place: ETSAB (Escuela Técnica Superior de Arquitectura de Barcelona) - Planta Baja - Aula Beta Av. Diagonal, 649-651 - 08028 - Barcelona
  Thesis director: MUROS ALCOJOR, ADRIAN
  Thesis abstract: The introduction of electric lighting in Architecture marked a profound transformation in its design conception, establishing artificial light as a fundamental element in the configuration of space. Unlike other artistic and architectural disciplines, artificial architectural lighting lacks a formalised Art History. Existing specialist literature remains largely focused on technical and quantitative aspects, frequently relegating the qualitative dimensions of light in space to a secondary status. Consequently, there is a notable absence of a specific vocabulary capable of accurately describing the qualitative effects of lighting in architecture. This lexical gap hampers the effective communication of lighting-related spatial concepts, ultimately to the detriment of architectural practice. In light of these challenges, and with the aim of improving both design and pedagogical methodologies, this research advocates for the establishment of a dedicated vocabulary for qualitative architectural lighting. It is predicated on the hypothesis that it is feasible to construct a consensual glossary that enables the precise articulation of the formal and spatial attributes of lighting effects within architectural environments. To substantiate this hypothesis, the research sets out two principal objectives: first, to identify the parameters that define the qualitative aspects of lighting and to compile the associated terminological corpus; second, to develop a lexical and visual dictionary in which each term is clearly defined and illustrated, thereby facilitating its comprehension and application in both academic and professional contexts, and contributing to the standardisation of a specific and practical language.The study adopts a qualitative methodological framework, centred on the linguistic analysis of texts describing architectural lighting projects, which have been published in specialised Spanish-language media. A rigorous, systematic, and replicable terminology methodology has been employed, drawing upon established principles from the field of Terminology studies and related research on lighting perception. The process integrates automated term extraction methods, enabling efficient handling of large data sets, and applies linguistic techniques adapted to the visual domain. The research identifies the principal parameters defining the formal qualities of architectural lighting as direction, colour, and distribution, followed by quantity, luminance, sources, informational content, perceptual effects, and others. Among these, the distribution parameter emerges as the most frequently cited and, thus, the most critical for both configuring and describing architectural lighting. Accordingly, the dictionary focuses on the most recurrent terms related to distribution, listed alphabetically as follows: accent lighting, ambient lighting, composed lighting, diffuse lighting, direct lighting, directed lighting, dispersed lighting, focalized lighting, general lighting, grazing lighting, homogeneous lighting, horizontal lighting, indirect lighting, integrated lighting, precise lighting, projected lighting, reflected lighting, uniform lighting, and vertical lighting. It has been demonstrated that each of these terms can be defined in a manner that supports clear, precise, and intelligible communication within architectural lighting discourse. Furthermore, it is feasible to identify corresponding visual representations that exemplify each definition, reinforcing their pedagogical and practical applicability. In conclusion, this research affirms the viability of developing a consensual glossary of terms to imporve the communication of the formal and spatial characteristics of lighting effects within architectural practice, which constitutes a foundational step toward the recognition and standardisation of qualitative lighting vocabulary in the discipline.
  

• EIXIMENO FRANCH, BENET: High performance computing and artificial intelligence algorithms for dimensionality reduction of turbulent flows
  
  Author: EIXIMENO FRANCH, BENET
  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 COMPUTATIONAL AND APPLIED PHYSICS
  Department: Department of Physics (FIS)
  Mode: Article-based thesis
  Deposit date: 29/09/2025
  Reading date: 31/10/2025
  Reading time: 12:00
  Reading place: Sala d'actes Manuel Martí Recober - Planta 0 - Edifici B6 - Campus Nord UPC
  Thesis director: RODRIGUEZ PEREZ, IVETTE MARIA | LEHMKUHL BARBA, ORIOL
  Thesis abstract: This thesis presents a suite of methodologies for the dimensionality reduction of turbulent flow data, with a focus on high-fidelity simulations of external aerodynamics in industrial contexts, such as flow around simplified road vehicles. These simulations, typically performed on unstructured meshes with hundreds of millions of degrees of freedom, require scalable tools for analysis and modeling. All developments are implemented in pyLOM, an open-source Python library designed for terabyte-scale reduced-order modeling.The work progresses in four main steps, all of them published and detailed in their corresponding peer-reviewed article. First, classical reduction techniques based on the singular value decomposition (SVD), such as proper orthogonal decomposition (POD), dynamic mode decomposition (DMD), and spectral POD (SPOD), are adapted for high-performance computing by exploiting parallel QR factorization. Strong and weak scalability tests demonstrate high efficiency, with communication during QR factorization identified as the main bottleneck. Such performance gains together with the parallel input/output capabilities of pyLOM helped to apply these algorithms to datasets which occupy several terabytes of data as the direct numerical simulation of the flow in the Stanford diffuser in 80 seconds.Second, a convolutional neural network (CNN) variational autoencoder ($VAE) is developed for nonlinear dimensionality reduction, successfully capturing the temporal dynamics of the Windsor body back pressure with only two latent variables. The model effectively compresses snapshots of back pressure taken at yaw angles of 2.5º, 5º, and 10º. The projection of the mean pressure coefficient to the latent space yields an increasing linear evolution of the two latent variables with the yaw angle. The mean pressure coefficient distribution at yaw angle 7.5º is predicted with a mean error of 3.13% when compared to the results obtained by means of wall-modeled large eddy simulations (WMLES) after computing the values of the latent space with linear interpolation.Both methodologies have been merged to create a novel method named Geometry-Agnostic Variational-autoencoder Integration (GAVI), replacing the SVD step with a VAE operating on QR-factorized data. GAVI provides compact latent spaces without requiring structured grids, achieving high energy recovery across diverse test cases: circular cylinder, Windsor body, and urban flows, with latent spaces of 3–6 variables recovering over 90% of flow energy. The only step involving high performance computing (HPC) in GAVI is the computation of the QR factorization. This operation is done in parallel using pyLOM and its economic cost for all cases tested is lower than 10€. The fit of the VAE to the R matrix can be done with a GPU that fits in a workstation or laptop.Finally, a transformer-based closure strategy is proposed to compensate for energy loss in reduced models. By learning the spatial distribution of unresolved fluctuations, it improves reconstruction accuracy for complex unstructured domains, outperforming approaches based on super resolution generative adversarial networks (SRGAN) in both vehicle wakes and urban wind scenarios. The transformer model learns the probability density function of the missing fluctuations conditioned to the fluctuations already recovered by the model. Adding these fluctuations closes the energy gap between the original and the reconstructed data and improves the accuracy on both the instantaneous fields and the root mean square value of the fluctuations.
  

• JIN, ANYI: Polyhydroxyalkanoates (PHAs): Processing, Property Modulation, and Biomedical Applications
  
  Author: JIN, ANYI
  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: 02/10/2025
  Reading date: 31/10/2025
  Reading time: 11:00
  Reading place: Sala Polivante A03 - Edici A EEBE - Campus Diagonal Besós https://eebe.upc.edu/ca/lescola/com-arribar
  Thesis director:
  Thesis abstract: This doctoral thesis presents a comprehensive study on the structure-property relationships, processing behavior, and functional performance of polyhydroxyalkanoates (PHAs), with the aim of enhancing their applicability as sustainable alternatives to conventional plastics. The work focuses on various PHA-based materials and explores their modification through blending strategies and the incorporation of functional additives. A wide range of processing techniques were employed, including melt compounding, injection molding, ultrasonic molding, solvent casting, and electrospinning. These methods enabled the fabrication of various PHA-based formulations tailored for specific applications. Physicochemical characterization was carried out using nuclear magnetic resonance (NMR), Fourier-transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), X-ray diffraction (XRD), scanning electron microscopy (SEM), polarized optical microscopy (POM), tensile testing, and synchrotron-based FTIR microspectroscopy (SR-FTIR). These techniques enabled the investigation of molecular structure, crystallization kinetics, morphology, thermal stability, and mechanical properties.The results demonstrate that copolymer composition plays a critical role in defining the crystallinity, thermal behavior, and mechanical performance of PHAs. The incorporation of comonomers such as 3-hydroxyvalerate (3HV), 3-hydroxyhexanoate (3HHx), and 4-hydroxybutyrate (4HB) effectively tuned the material properties. The addition of nucleating agents, such as boron nitride (BN) and poly(3-hydroxybutyrate) (PHB), were found to significantly accelerate the crystallization rate of P3HBHHx without adversely affecting its molecular or thermal stability. Blending P3HBHHx with other biopolymers, such as poly(latic acid) (PLA), poly(butylene adipate-co-terephthalate) (PBAT), poly(butylene succinate) (PBS), and poly(3-hydroxybutyrate-co-4-hydroxybutyrate) (P34HB), further modulated its performance, although compatibility remained a challenge in certain formulations. Biomedical applications were also explored using electrospinning and ultrasonic molding. Drug-loaded poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) nanofibers exhibited tunable release kinetics and antibacterial activity, while P34HB demonstrated excellent processability and thermal resistance under ultrasonic molding conditions. Finally, SR-FTIR microspectroscopy revealed spatial orientation patterns within PHBV spherulites, offering new insights into the molecular organization of PHAs. Overall, this thesis establishes a comprehensive framework for tailoring PHA materials through formulation and processing innovations. It contributes to the scientific understanding and technological advancement of PHAs as viable sustainable material across various sectors.