Francisco Jurado Melguizo is a Professor in the Department of Electrical Engineering at Universidad de Jaén. His research focuses on power systems, renewable energy integration, and optimization algorithms, with over 520 JCR-indexed publications and 260 conference papers. He has led projects funded by Spanish Ministries and the European Commission and authored 8 books. PhD: Universidad Nacional de Educación a Distancia (UNED), 1999 His work spans distributed generation, energy storage, smart grids, and techno-economic analysis, often incorporating AI and metaheuristic optimization techniques. Recent projects include hybrid renewable systems, EV charging infrastructure, and grid resilience under climate uncertainties. He has received recognition as one of the most influential researchers globally by Stanford University and contributes to research groups focused on electrical technology and energy systems.
Juan José Rué Perna is an Associate Professor in the Department of Mathematics at Universitat Politècnica de Catalunya (UPC), where he serves in the Faculty of Mathematics and Statistics. He also holds the position of Director of CFIS (Centro de Formación Interdisciplinaria Superior) and maintains strong affiliation with the Centre de Recerca Matemàtica (CRM). His academic career spans prestigious institutions across Europe, including Freie Universität Berlin, CSIC-ICMAT in Madrid, and École Polytechnique in Paris. Licenciado en Matemáticas (5-year degree) Engineering degree in Telecommunications (5-year program) PhD in Applied Mathematics (2009), supervised by Professor Marc Noy Rué's research focuses on combinatorics and discrete mathematics, with expertise in combinatorial structures, random graphs, and enumerative problems. His work bridges theoretical mathematics with applications in computer science, particularly in structural graph theory and probabilistic methods. He has made significant contributions to the understanding of planar graphs, random discrete structures, and additive combinatorics problems. His research combines analytic techniques with combinatorial reasoning to solve challenging enumeration and structural problems. His recent publications demonstrate a consistent trajectory in combinatorial mathematics, with emphasis on planar structures, random discrete objects, and additive problems. The works span theoretical investigations of graph structures, enumeration techniques, and probabilistic approaches to combinatorial problems. His research group GAPCOMB (Geometric, Algebraic and Probabilistic Combinatorics) at UPC continues to produce influential work in these areas. Premi Albert Dou de la SCM Rué has successfully supervised multiple PhD students to completion, including Clément Requilé, Christoph Spiegel, Vasiliki Velona, and Maximilian Wötzel. His research has been supported through numerous competitive grants, including ERC projects, ExploreMaps, and participation in the Berlin Mathematical School. He has organized significant academic events such as EUROCOMB 2021 and various workshops on combinatorics and discrete mathematics. As leader of the GAPCOMB research group at UPC, Rué fosters collaboration between geometric, algebraic, and probabilistic approaches to combinatorial problems. The group maintains strong connections with international research centers including ICMAT in Madrid and institutions across Europe, contributing to the vibrant combinatorial research community in Spain and internationally.
José Fernández Hernández is a Full Professor at the Department of Statistics and Operations Research, Faculty of Mathematics, University of Murcia (Spain). His academic career spans over two decades with significant contributions to location science, global optimization, and interval analysis. Ph.D. in Mathematics (1999), University of Murcia (Thesis: "Nuevas técnicas para el diseño y resolución de modelos de localización continua") Member of Operations Research Group (IOMUR), Spanish Society of Statistics and Operations Research (SEIO), and Euro Working Group on Locational Analysis (EWGLA) Research Interests: Specializing in Location Science where he develops models for optimal facility placement considering transportation costs, market share capture, and customer behavior. His work extends to Global Optimization techniques using interval analysis to solve nonlinear problems with multiple local optima, and Multiobjective Optimization frameworks for balancing conflicting objectives in spatial decision-making. Article Trends: His publications demonstrate a progression from geometric decomposition methods (2000s) to advanced competitive facility location models (2010s) parallel evolutionary algorithms (2010-2020) MINLP formulations for firm expansion (2015-2024) probabilistic consumer choice modeling attractiveness adjustment in existing facilities Stackelberg games in facility location Grants & Projects: Over 20 funded projects including national grants (Ministerio de Ciencia e Innovación) 1997-2024 regional projects (Fundación Séneca, Junta de Andalucía) 1998-2022 international cooperation with Hungary 2002-2006 Coordinating research networks on location analysis and computational methods. Collaboration: Regularly works with researchers from University of Almería University of Szeged (Hungary) International Federation of Operational Research Societies with over 50 co-authored publications.
Roberto Iglesias Rodríguez is an Associate Professor at the University of Santiago de Compostela, Spain, with a focus on robotics and machine learning. He holds a B.S. and Ph.D. in Physics from the same institution (1996, 2003). His work addresses lifelong robot learning, federated learning, and deployment of intelligent systems in heterogeneous environments. Current affiliation: University of Santiago de Compostela Academic rank: Associate Professor Education: B.S. and Ph.D. in Physics (1996, 2003) His research spans robotics, machine learning, and sensor fusion , emphasizing adaptive algorithms for non-IID data, concept drift, and real-time environmental interaction. Projects include service robots learning from humans, distributed control architectures, and federated learning strategies. Recent publications analyze continual learning , scene recognition , and human-robot collaboration . Key themes: robust navigation, multi-sensor systems, and explainable AI.
Hongjin Liang is an Associate Professor at the School of Computer Science , Nanjing University , where he researches programming languages and formal verification as part of the PLaX group. His office is located at Room 404, Building of Computer Science and Technology, Nanjing University (Xianlin Campus). His research spans concurrency , compiler verification , distributed systems , and theorem proving , with a focus on developing formal methods for verifying program correctness under complex execution models (e.g., randomized concurrency, CRDTs). His publications emphasize verification techniques for concurrent and distributed systems, program logics, and compiler optimizations. Recent work explores probabilistic program verification and algorithmic foundations of distributed computing. Awards: PLDI'19 Distinguished Paper Award He teaches courses including Formal Semantics of Programming Languages and Concurrency: Algorithms and Theories . He actively serves on program committees for PLDI, POPL, ESOP, and related conferences.
Ricardo Javier Principe Rubio is a Researcher at the Universitat Politècnica de Catalunya (UPC), affiliated with the Barcelona East School of Engineering (EEBE) and the Department of Fluid Mechanics. He is a key member of the ANiComp (Numerical Analysis and Scientific Computing) and (MC)² (Computational Mechanics in Continuous Media) research groups. His work bridges high-performance computing, fluid dynamics, and numerical methods, with applications in fusion technology, environmental engineering, and nanomaterials. His research focuses on advanced computational techniques, including finite element methods, uncertainty quantification, and parallel algorithms for large-scale simulations. Recent projects involve anisotropic mesh adaptation, multilevel Monte Carlo methods, and stabilized formulations for multiphase flows. Principe actively contributes to UPC's scientific software ecosystem, notably through the FEMPAR framework for parallel finite element modeling. Awards include the Premi Extraordinari de doctorat 2010 for outstanding doctoral research. He leads/participates in competitive R&D projects funded by Catalan and EU programs, such as EXAscale Quantification of Uncertainties for Technology and Science Simulation (EXAQUAT). Collaborative networks span Barcelona Supercomputing Center and international consortia.
Diego Gutierrez is a Full Professor at the Computer Science Department of the Universidad de Zaragoza, Spain. He leads the Graphics & Imaging Lab at the I3A Institute and is part of the Vision, Image and Neurodevelopment Group at the IIS Aragon Institute. His research focuses on light transport simulation, computational imaging (including non-line-of-sight imaging), virtual reality, material perception, and applied perception for medical applications (via his startup DIVE Medical). He has received the 2022 Eurographics Outstanding Technical Contributions Award and an ERC Consolidator Grant (2016). Education & Affiliations: No explicit education details provided, but he has been a visiting researcher at MIT, Stanford, Yale, UCSD, and other institutions. Research Themes: Physically-based light transport simulation (transient rendering, global illumination) Computational imaging (NLOS imaging, diffractive wave propagation) Virtual reality (user behavior modeling, multimodal perception) Material appearance representation (perceptual metrics, intuitive editing) Medical imaging (visual function assessment) Professional Contributions: Editor in Chief of ACM TAP Associate Editor for ACM TOG and Computer Graphics Forum Program Chair for international conferences Publications & Impact: Over 100 influential papers, including a breakthrough Nature paper on NLOS imaging using diffractive wave propagation. His work on transient rendering, phasor fields, and perceptual material editing has driven field advancements. Grants & Recognition: ERC Consolidator Grant (2016) for intuitive material editing research Named among the 100 most influential researchers of the decade Recipient of the 2022 Eurographics award for technical contributions Labs & Teams: Leads the Graphics & Imaging Lab (I3A Institute) and co-founded DIVE Medical for clinical visual diagnostics. His team's work bridges computer graphics with perceptual science and clinical applications.
Sebastia Martin Mollevi is a researcher at the Department of Mathematics , Universitat Politècnica de Catalunya , affiliated with the Information Security Group - Mathematics Applied to Cryptography (ISG-MAK) . His work focuses on cryptographic protocols, secret sharing, and elliptic curve applications. Education : PhD in Mathematics (2000) from UPC, thesis on Elliptic Curves over ZN and Cryptographic Applications . Research Interests : Cryptography, secret sharing schemes, broadcast encryption, elliptic curve cryptography, combinatorial code design, and information theory applications. Publications : 108 activities including 16 indexed journal articles, 58 conference presentations, and 17 technical documents. Projects : Lead researcher in projects like Cátedra CARISMATICA and Criptografía para retos digitales emergentes , focusing on digital society security and post-quantum cryptography. His work includes algorithmic improvements in broadcast encryption trade-offs, linear threshold secret sharing, and secure public-key cryptosystems. Notable contributions involve proving security equivalences in elliptic curve systems and developing practical encryption mechanisms.
Dr. Simón Rodríguez Santana is an Assistant Professor at the Higher Technical School of Engineering (ICAI) of Comillas Pontifical University, where he teaches in the Mathematical Engineering and Artificial Intelligence program. He holds a Physics degree from the Autonomous University of Madrid, a Master's in Theoretical Physics, and a PhD in Mathematical Engineering from Complutense University of Madrid. His research focuses on developing probabilistic machine learning and statistical techniques, particularly Bayesian methods applied to drug discovery, adversarial risk analysis, and time series forecasting. Professional experience includes a postdoctoral position at the Institute of Mathematical Sciences (ICMAT-CSIC) and visiting scholar roles at Aalto University (Finland). He has led two industrial research projects and contributed to national/international initiatives. Technical skills include Python (TensorFlow/PyTorch), R, LaTeX, and Slurm. Key research areas span probabilistic ML, Bayesian statistics, approximate inference, and operations research. Recent work emphasizes applications in personalized pricing strategies and AI-driven drug design. He has reviewed for top conferences (ICML, NeurIPS) and presented invited seminars on probabilistic ML applications. Awarded PAD accreditation from ANECA, he actively engages in academic dissemination through media appearances like 'Casting the Future' podcast and external training programs such as Generative AI for Education. His current teaching includes tenure-track positions and thesis supervision at undergraduate and master's levels.
Julian Pfeifle is an Associate Professor in the Department of Mathematics at the Polytechnic University of Catalonia (UPC), affiliated with the Terrassa School of Industrial, Aerospace, and Audiovisual Engineering. He is part of the UPC's research group GAPCOMB (Geometric, Algebraic, and Probabilistic Combinatorics). His research focuses on combinatorics, discrete geometry, and algebraic structures, with particular emphasis on polytopes, graph theory, and geometric algorithms. Affiliations: Department of Mathematics, UPC; GAPCOMB Research Group. Education: Doctorate in Mathematics from UPC (thesis directed by G. M. Ziegler). His research interests span polytope theory, combinatorial geometry, algebraic combinatorics, and discrete optimization. Recent work includes studies on non-realizability certificates for polytopes, polynomial roots via Gale duality, and geometric constructions using the Cayley trick. He has contributed to projects funded by national and international grants, including the European Science Foundation's 'SDModels' initiative. Pfeifle has published extensively in top journals like Journal of Combinatorial Theory , Discrete & Computational Geometry , and Experimental Mathematics . His articles often explore polytopal structures, graph algorithms, and combinatorial topology. A notable award is the Richard Rado Preis (Ehrenvolle Anerkennung) for his doctoral thesis. He has advised doctoral students and contributed to research projects such as 'Geometric, Algebraic and Probabilistic Combinatorics' (AGRUPS-2023) and 'Combinatorics and Complexity of Discrete Geometric Structures' (MTM-funded). His work frequently intersects with computational geometry and combinatorial algorithms, with applications in optimization and discrete mathematics.
Vicenç Gómez is an Associate Professor in the Department of Engineering at Universitat Pompeu Fabra (UPF), where he leads research in artificial intelligence and machine learning. He serves as Coordinator of the Erasmus Mundus Joint Master in Artificial Intelligence and the MSc program in Intelligent and Interactive Systems, and teaches in the BSc in Mathematical Engineering in Data Science. His research interests include machine learning, approximate inference, optimal control, and complex networks , with applications in social networks, robotics, brain-computer interfaces, and urban systems. He applies advanced AI techniques to model human behavior, network dynamics, and decision-making processes. The recent publications highlight a strong focus on graph-based learning, reinforcement learning, social network analysis, and health informatics . His work integrates theoretical advances in probabilistic modeling with real-world applications in digital platforms, environmental monitoring, and mental health. There is a consistent theme of modeling complex systems through structured AI and interpretable models. Scientific Awards and Recognition: Coordinator of the prestigious Erasmus Mundus Joint Master in Artificial Intelligence Local Chair of UAI 2024, a top-tier conference in AI Program Committee member for ICAPS 2024 Organizer of the EMAI Summer School in collaboration with UCL Advising and Grants: Vicenç Gómez actively supervises PhD and Master's students, including Nur Alvarez-Gonzalez, Roger Garriga, Emily Theophilou, and Sergio Calo. His advising spans topics in emotion detection, mental health modeling, air quality prediction, and representation learning. He has been involved in organizing major academic events and leading international educational programs, indicating significant leadership and collaborative grant activity. Labs and Research Groups: He is a key member of the Artificial Intelligence and Machine Learning group at UPF’s Department of Engineering, based at the Roc Boronat building in Barcelona. His team engages in interdisciplinary research combining AI theory with applications in social, health, and urban domains.
Vicent Girbés Juan is an Associate Professor in the Department of Electronic Engineering at the School of Engineering, Universitat de València. His research is centered in the HRI Human-Robot Interaction Group, where he contributes to advanced robotics, intelligent vehicles, and human-centered automation systems. He earned his PhD from Universitat Politècnica de València in 2016 with a thesis on clothoid-based planning and control in autonomous and manual-assisted driving systems, supervised by Dr. Josep Tornero Montserrat and Dr. Leopoldo Armesto Ángel. His research interests span robotics, control systems, path planning for UAVs, visible light communication, haptic feedback in teleoperation, and educational innovation in engineering. He has published extensively on smooth trajectory generation, dual-arm robot control, sensor fusion, and V2V communications. His recent work shows a growing emphasis on integrating pedagogical innovation with engineering education, including flipped evaluation, peer assessment, and hackathon-based programming learning. His publications from 2021 to 2024 reveal a dual focus: advancing industrial robotics and intelligent transportation systems, while simultaneously innovating in teaching methodologies and student engagement in higher education. Key technical areas include clothoid-based 3D path planning, cautious Bayesian optimization, VLC positioning, and haptic-assisted teleoperation. He actively collaborates on interdisciplinary projects involving human-robot cooperation, industrial automation, and educational technology, reflecting a commitment to both technological advancement and pedagogical excellence. His email is vicent.girbes@uv.es .
Pablo Diaz Cachinero is a Visiting Professor at Carlos III University of Madrid, affiliated with the Department of Statistics and the Energy Analytics research group. His work bridges Industrial Engineering and Renewable Energy domains. Research Interests: His research focuses on integrating Electric Vehicles (EVs) into energy systems, optimizing microgrid operations with renewable resources, and analyzing transitional energy technologies. He applies advanced statistical and optimization methods to address demand uncertainty and improve grid efficiency. Publications Trends: Recent work emphasizes Virtual Power Plants (VPPs), EV operational planning, and battery degradation cost modeling. These studies appear in journals like IEEE Access, Applied Energy, and Renewable Energy. Projects: Currently leading SOLAROPIA-CM-UC3M (2024-2026): AI for solar plant integration in Spain UNIVERSIDAD CARLOS III DE MADRID (2024-2025): Uncertainty-based EV optimization Academic Mobility: Completed a predoctoral stay at Aalto University (2021) under Professor Matti Lehtonen. Maintains active co-authorship networks and is visible on platforms like Google Scholar.
Lorenzo Castilla Mora serves as Associate Professor in the Department of Integrated Didactics within the Faculty of Education, Psychology and Sports Sciences at the University of Huelva. His academic profile centers on mathematics and statistics education, with specialized expertise in developing probabilistic reasoning frameworks for educators and designing innovative teaching methodologies for uncertainty concepts. His doctoral research at the University of Huelva (2017) examined Spanish financial sector perceptions post-crisis using fuzzy cognitive mapping, supervised by Dr. David Castilla Espino and Dr. Juan José García del Hoyo. This work reflects his interdisciplinary approach bridging quantitative methods with social science applications. Castilla Mora's research trajectory reveals three interconnected strands: (1) teacher knowledge development in probability and statistics, evidenced by cross-cultural studies with Slovakian educators; (2) digital pedagogy innovation through platforms like Moodle, eTwinning, and Scientix for STEAM integration; and (3) curriculum adaptation to European educational frameworks. His publications consistently address practical classroom implementation challenges while advancing theoretical foundations in mathematics didactics. His scholarly output demonstrates evolving focus from financial cognition and migration studies (2006-2010) toward concentrated expertise in statistical pedagogy since 2011, with recent work emphasizing teacher training for probabilistic reasoning (2021-2023). This progression highlights increasing specialization in mathematics education while maintaining methodological rigor from his quantitative social science background. He actively contributes to research groups HUM168 (Teacher Development) and SEJ329 (MEMPES-AEA), focusing on collaborative projects that translate theoretical frameworks into practical educational tools. His current work integrates digital solutions with cognitive theory to address persistent challenges in statistics education.
Eva María Arias de Reyna Domínguez serves as a Full Professor in the Department of Signal Theory and Communications at the University of Seville. Her research is centered within the Signal Processing and Communications research group (TIC-155), where she has led numerous national and international projects focused on advanced signal processing techniques for wireless communications and localization systems. Her research interests span Signal Processing , Wireless Communications , and Ultra-Wideband Localization , with particular expertise in Expectation Propagation algorithms, UWB signal processing, and crowd-based learning for IoT applications. Her work bridges theoretical signal processing with practical implementations in digital communications and indoor positioning systems. Analysis of her 15 most recent publications reveals a consistent focus on Expectation Propagation techniques for digital communications (constituting 40% of recent work), UWB localization algorithms (30%), and channel equalization methods (20%). Her research demonstrates a progression from fundamental signal processing algorithms toward IoT-integrated spatial field estimation and machine learning applications. She has advised doctoral student Irene Santos Velazquez (2018 thesis on Expectation Propagation for digital communications) and participated in significant research projects including ATENEA (Artificial Intelligence for Art Fabric Analysis), Finite-Length Iterative Decoding, and multiple national grants under Spain's TEC and CSD programs. Her laboratory work centers on the Signal Processing and Communications research group, which has received continuous consolidation funding from 2005-2017.
