Xavier Serra is a Full Professor at the Department of Engineering at Universitat Pompeu Fabra (UPF), Barcelona. He is the founder and director of the Music Technology Group (MTG), and leads the UPF-BMAT Chair on AI and Music. He also coordinates the Master in Sound and Music Computing and serves as President of the Phonos Foundation. His research focuses on audio signal processing, sound and music computing, and computational musicology, emphasizing open science and open innovation. Education: BSc in Biology, University of Barcelona (1981) Master in Music, Florida State University (1983) PhD in Computer Music, Stanford University (1989) Research Interests: Audio Signal Processing Data-Driven and Knowledge-Driven Methodologies Music Information Retrieval Cultural Music Analysis (e.g., Carnatic/Turkish/Andalusian Music) Music Education Technology Notable Projects: CompMusic (ERC Advanced Grant, 2010-2017): Multicultural computational music analysis Open datasets: Freesound, Saraga, FSD50K Technologies: Reactable, Vocaloid, Essentia API Recent Trends in Articles: Focus on AI-driven audio processing (neural fingerprints, generative models), cross-cultural music analysis, and explainable music difficulty estimation. Awards: ERC Advanced Grant (2010) for CompMusic Project. Labs/Teams: Director of MTG, Phonos Foundation, and UPF-BMAT Chair. Active in open-source projects and international collaborations.
Sergio Bermudo Navarrete is a Professor at the Department of Economics, Quantitative Methods and Economic History, Universidad Pablo de Olavide. His research spans combinatorics, graph theory, and operator theory. Education: PhD in Mathematics (2003, University of Seville) with thesis on functional models of operators in Hilbert spaces. Research Interests: Focus on graph theory, domination problems, topological indices, and operator theory. Publication Trends: Recent work includes vertex-degree-based indices for oriented graphs, domination parameters in product graphs, and differential analysis of line graphs. Keywords span Computer Science , Mathematical Chemistry , and Operations Research . Collaborations: Frequent co-authors: José María Sigarreta Almira, José Manuel Rodríguez García, Juan Alberto Rodríguez-Velazquez. Contact: Email sbernav@upo.es .
Carme Torras Genís is a Research Professor at the Spanish National Research Council (CSIC), affiliated with the Institute of Robotics and Industrial Informatics (IRI) in Barcelona and the Technical University of Catalonia (UPC). Her career spans over three decades, focusing on robotics, neurocomputing, and artificial intelligence with applications in healthcare and deformable object manipulation. M.Sc. in Mathematics (University of Barcelona, 1978) M.Sc. in Computer Science (University of Massachusetts, 11981) Ph.D. in Computer Science (UPC, 1984) Research Interests : Robotic manipulation of deformable objects (especially textiles) Neurocomputing and machine learning for robotic control Human-robot interaction and assistive robotics Computational topology for cloth state representation Ethics in social robotics and AI Medical applications of robotics for neuromuscular disease assessment Scientific Leadership : ERC Advanced Grant recipient (2016) IEEE and EurAI Fellow Coordinator of Horizon Europe project SoftEnable and former ERC project CLOTHILDE Editorial leadership in IEEE Transactions on Robotics and multiple journals Active in ethics committees and AI policy advisory boards Advisory Committee of Ethics in AI (Catalan Government) Vice-President of CSIC Ethics Committee Member of Royal Academy of Engineering (Spain)
Prof. Jaume Sanz Subirana is a Tenure Full Professor of Mathematics at the Universitat Politècnica de Catalunya (UPC), BarcelonaTECH, and a Senior GNSS Scientific Researcher. He has been affiliated with the Department of Mathematics since 1983. His primary research focuses on GNSS data processing algorithms, ionospheric sounding, and high-accuracy navigation systems like WARTK and Fast-PPP. He co-founded the spin-off company gAGE-NAV S.L. in 2009 and served on the European Space Agency's GNSS Scientific Advisory Group (2018-2022). Prof. Sanz Subirana holds a Physics degree (1982) and a PhD in Galactic Dynamics (1987) from the Universitat de Barcelona. He has authored over 100 peer-reviewed papers (50+ in top JCR journals), 200 conference works, five books (including ESA-commissioned volumes), and holds four patents. His work has earned four best paper awards and UPC's Merit Recognition for teaching excellence. His research group, gAGE/UPC, specializes in GNSS navigation algorithms, ionospheric monitoring, and SBAS/GBAS systems. Key contributions include ionospheric gradient monitoring, real-time kinematic positioning, and mitigation of space weather effects on navigation signals.
Bryon Aragam is an Associate Professor of Econometrics and Statistics and Robert H. Topel Faculty Scholar at the University of Chicago Booth School of Business. His research focuses on the intersection of causality, statistical machine learning, and probabilistic modeling, with particular emphasis on applications to artificial intelligence systems including large language models like ChatGPT and generative models like DALL-E. Dr. Aragam completed his PhD in Statistics and a Masters in Applied Mathematics at UCLA, where he was an NSF graduate research fellow. Prior to joining the University of Chicago, he was a project scientist and postdoctoral researcher in the Machine Learning Department at Carnegie Mellon University. Research Focus: Causal structure learning in probabilistic generative models Key Areas: Causal machine learning, deep generative models, latent variable models, statistical learning theory Applications: AI interpretability, ethics, and fairness in artificial intelligence systems Teaching: Business Statistics, Econometrics and Statistics Colloquium His recent publications demonstrate a strong theoretical foundation combined with practical applications, particularly in understanding and improving AI systems. His work spans causal discovery, graphical models, deep learning, and latent variable modeling, with particular attention to the theoretical properties of these methods and their applications to real-world AI challenges. The research shows a progression toward increasingly complex problems in causal representation learning and AI interpretability. Scientific Awards: Robert H. Topel Faculty Scholar NSF Graduate Research Fellow Dr. Aragam's work has been published in top statistics and machine learning venues including the Annals of Statistics, Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the Journal of Machine Learning Research (JMLR). His research group publishes broadly across both statistical and machine learning communities, demonstrating the interdisciplinary nature of his work at the intersection of statistics, machine learning, and causal inference. As a data science consultant for technology and marketing firms, Dr. Aragam has applied his expertise to problems in survey design, customer retention, logistics, and ranking, bridging the gap between theoretical research and practical applications.
Jacob D. Leshno is an Associate Professor of Economics and Robert H. Topel Faculty Scholar at the University of Chicago Booth School of Business. His research employs game theory, applied mathematics, and microeconomic theory to study allocation mechanisms and marketplace design, with applications spanning school choice systems, patient assignments to nursing homes, and decentralized cryptocurrency protocols. Professor Leshno's academic background includes: PhD in Economics from Harvard University, completed under Nobel laureate Alvin Roth M.Sc. in Pure Mathematics from Tel Aviv University B.Sc. in Pure Mathematics from Tel Aviv University His research program centers on market design theory with two primary strands. The first focuses on matching markets, where he developed tractable cutoff characterizations that clarify market structures for college admissions and medical residency matching (NRMP). His work demonstrates how price discovery mechanisms can streamline inefficient processes like college applications and subsidized housing allocation. The second strand examines cryptocurrencies and blockchain technology, investigating how open-source computer code functions as market rules in decentralized systems. This research explores both the economic security of permissionless consensus and fundamental limitations of proof-of-work protocols. Professor Leshno's publications reveal a cohesive research trajectory applying economic theory to increasingly complex market structures. His work consistently bridges theoretical rigor with practical implementation, evolving from traditional matching markets to the frontier of decentralized digital systems. Publications in top journals like American Economic Review and Journal of Political Economy demonstrate both analytical depth and real-world relevance across education, healthcare, and financial technology sectors. Professor Leshno has received significant recognition for his contributions: ACM SIGecom Test of Time Award for foundational work in matching markets INFORMS Frederick W. Lanchester Prize for outstanding contributions to operations research Prior to Chicago Booth, Professor Leshno served as Assistant Professor at Columbia Business School and completed a postdoctoral fellowship at Microsoft Research New England, following industry experience at Yahoo! and IBM. He teaches MBA courses in Competitive Strategy and Market Design, and developed a PhD seminar bridging computer science theory with economic principles for distributed systems. His research continues to influence both academic theory and practical implementations of market mechanisms across multiple sectors. Professor Leshno maintains active collaborations with leading researchers including Itai Ashlagi, Irene Lo, and Gur Huberman, advancing the theoretical foundations of market design while addressing contemporary challenges in digital marketplaces and allocation systems.
Institute for Bioengineering of Catalonia (IBEC)Spain
Prof. Raimon Jané Campos is a leading figure in biomedical signal processing at the Universitat Politècnica de Catalunya (UPC) and Universitat de Barcelona (UB). As co-director of UPC's Biomedical Signal and System Group (CREB) and coordinator of the Biomedical Engineering PhD Programme, he bridges engineering and clinical applications. His work focuses on respiratory and sleep disorder diagnostics, with significant contributions to COPD and sleep apnea monitoring through wearable devices and machine learning. PhD in Biomedical Engineering (UPC, 1989) Visiting researcher at Université de Nice-Sophia Antipolis Vice-president of Spanish Society of Biomedical Engineering Research spans respiratory mechanics , sleep-disordered breathing , acoustic biomarkers , bioimpedance , and machine learning in biomedical contexts . His 2025 work on microcalorimetric pathogen classification and 2024 spiking neural networks for apnea detection demonstrate cutting-edge integration of computational methods with physiological monitoring. Articles from 2017-2024 reveal consistent focus on non-invasive diagnostics , cardiorespiratory synchronization , and smartphone-based health solutions . Awarded the Barcelona City Technology Research Award (2005) and serving on the International Advisory Board for Physiological Measurement since 2010, his career combines academic leadership with real-world clinical translation through IBEC's technology transfer initiatives.
Albert Atserias is a Professor in the Department of Computer Science at the Universitat Politècnica de Catalunya (UPC), affiliated with the Faculty of Informatics of Barcelona (FIB) and the ALBCOM research group (Algorithms, Bioinformatics, Complexity, and Formal Methods). He is also associated with the Institut de Matemàtiques de la UPC-BarcelonaTech. His research is central to theoretical computer science, with a strong emphasis on logic and complexity. Atserias's research interests span Computational Complexity, Logic in Computer Science, Finite Model Theory, Proof Complexity, and Constraint Satisfaction Problems . His work explores the fundamental limits of computation, the expressive power of logical languages over finite structures, and the complexity of proving mathematical statements. He investigates the algebraic and combinatorial properties of proof systems, the limits of efficient algorithms for constraint solving, and the theoretical foundations of databases. His research often bridges logic, algebra, and combinatorics to provide deep insights into computational phenomena. The trends in his recent publications show a sustained focus on the logical and algebraic underpinnings of computational problems. Key themes include the consistency and complexity of database queries , the power and limitations of proof systems (like resolution and sum-of-squares), and the expressive power of homomorphism counts in graph theory. His work on the hardness of automating resolution and the development of circular proof systems are particularly significant contributions to proof complexity. The 2024 PODS Best Paper Award for work on relational consistency underscores the impact and timeliness of his research. Among his notable scientific awards are the prestigious ICREA Acadèmia , the PODS 2024 Best Paper Award , the Premi Extraordinari de Doctorat (Extraordinary Doctoral Prize), and the Kleene Award for Best Student Paper . These accolades reflect both the excellence of his early work and his continued leadership in the field. Atserias has been a principal investigator on numerous competitive research projects, including funding from the European Research Council (ERC) and the Spanish Ministry of Science. He has advised doctoral students, such as Toni Hakoniemi, whose thesis on proof complexity he supervised. His extensive collaborative network includes leading researchers like Phokion Kolaitis, Anuj Dawar, and Victor Dalmau. He has also served on the scientific committees of major conferences, contributing to the academic community. He is a core member of the ALBCOM research group , a leading team at UPC focused on theoretical aspects of computer science, which provides a vibrant environment for research in algorithms, complexity, and formal methods. His work is also connected to the broader Institut de Matemàtiques de la UPC, fostering interdisciplinary collaboration between computer science and mathematics.
Eugene F. Fama, 2013 Nobel Laureate in Economic Sciences, is the Robert R. McCormick Distinguished Service Professor of Finance at the University of Chicago Booth School of Business. Widely regarded as the "father of modern finance," his work on the efficient markets hypothesis and risk-return relationships has profoundly influenced both academic and investment communities. Bachelor's, Tufts University (1960) MBA and PhD, University of Chicago Graduate School of Business (1964) Fama's research centers on theoretical and empirical finance, focusing on asset pricing models, market efficiency, and portfolio management. His recent publications emphasize factor investing, including the development of five-factor models and the analysis of international market anomalies. Key trends in his scholarship include empirical validation of the Capital Asset Pricing Model (CAPM), international factor analysis, and the distinction between luck and skill in mutual fund performance. His work remains foundational for quantitative finance and investment strategies. Scientific Awards and Fellowships Nobel Prize in Economic Sciences (2013) Deutsche Bank Prize in Financial Economics (2005) Morgan Stanley American Finance Association Award for Excellence in Finance (2007) Onassis Prize in Finance (2009) Chaire Francqui (1982) Nicholas Molodovsky Award from CFA Institute (2006) Fred Arditti Innovation Award (2007) Fellow of the American Finance Association (2001) Fellow of the Econometric Society Fellow of the American Academy of Arts and Sciences Fama serves as Advisory Editor for the Journal of Financial Economics and has mentored numerous PhD students through his academic career. His research continues to shape financial theory and practice, with ongoing analysis of market efficiency and factor-based investing.
Carles Padro Laimon is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Mathematics and the School of Telecommunications Engineering. He is a leading researcher in cryptography and information security, focusing on secret sharing schemes, combinatorial structures, and cryptographic protocols. His work integrates discrete mathematics, coding theory, and algorithmic design to address security challenges in digital systems. Padro leads the MAK Research Group (Mathematics Applied to Cryptography) and the ISG-MAK Information Security Group. He has been involved in numerous competitive research projects, including initiatives on post-quantum cryptography and secure multi-user systems. His contributions span over 211 documented activities, including articles, theses, and conference participations. His research interests include the theoretical foundations of cryptography, with a focus on optimizing secret sharing schemes, analyzing matroid-based structures, and developing secure communication protocols. He has collaborated extensively with institutions like the UPC and European research networks, contributing to both academic and practical advancements in cybersecurity. Padro holds a PhD in Mathematics from UPC and has supervised doctoral theses and mentored researchers in his field. His work frequently appears in top journals like IEEE Transactions on Information Theory, Designs, Codes and Cryptography, and SIAM Journal on Discrete Mathematics.
Francisco Javier Murillo Torrecilla is a Professor of Research Methods and Evaluation in Education at the Autonomous University of Madrid (UAM). He serves as Director of multiple educational journals ( REICE , Revista Iberoamericana de Evaluación Educativa , Revista Internacional de Educación para la Justicia Social ) and leads research groups like 'Educational Change for Social Justice' (GICE) and the Ibero-American Research Network on School Change and Effectiveness (RINACE). His work focuses on Education for Social Justice , School Segregation , and Educational Leadership . He holds degrees in Mathematics and Education Sciences, and a PhD in Education Sciences from Universidad Complutense de Madrid. With 5 research sexenios and over 200 publications, his citations exceed 25,000 (h-index: 84) in Google Scholar. He has led 25 competitive research projects, including the 'Network of Excellence' RILME (EDU2017-90606-REDT). Coordinated UNESCO's Latin American Laboratory for Educational Quality Evaluation (LLECE) Former Director of Spain's Centre for Educational Research and Documentation (CIDE) Director of UAM's UNESCO Chair in Education for Social Justice and Institute DEMOSPAZ His research projects on social justice in education include five consecutive Spanish State Program grants (2010-2021) and books like La investigación sobre eficacia escolar (2005). He has consulted for UNESCO, OECD, and governments in Latin America.
Danel Ahman is an Associate Professor at the Institute of Computer Science , University of Tartu , Estonia, specializing in programming language theory . His research focuses on dependent/refinement types , computational effects , and verified software . Education PhD in Theoretical Computer Science (University of Edinburgh, 2017) MPhil in Advanced Computer Science (University of Cambridge, 2012) BSc in Informatics (Tallinn University of Technology, 2010) Research Interests : Danel investigates programming languages with algebraic effects and effect handlers for verified software, exploring denotational/operational semantics and fibrational approaches to effects. His work bridges theoretical computer science with practical formal verification. Scientific Awards : Estonian Research Council grant (2025) Marie Skłodowska-Curie Fellowship (2019) PhD dissertation prize (2018) Google/Citrix dissertation awards (2012) Teaching & Supervision : He teaches courses like Logic in Computer Science and Functional Programming at the University of Tartu, and supervised BSc/MSc theses on topics including asynchronous effects and formal verification. Danel also organizes research seminars and guest lectures on F*.
Karina Gibert is a Full Professor at Universitat Politècnica de Catalunya (UPC), specifically at the Faculty of Computer Science of Barcelona (FIB) in the Department of Statistics and Operations Research. With a permanent teaching position since 1990, she contributes to research and education with a focus on Data Science, Artificial Intelligence, Explainable AI, and Ethics in AI. Full Professor, UPC (since 1990) PhD in Informatics Engineering Postgraduate in Higher Education Teaching Director and co-founder of IDEAI research center Dean of the Official Professional College on Informatics Engineering of Catalonia Active in bridging the gender gap in STEAM through multiple initiatives Her research focuses on extracting strategic knowledge from data and intelligent systems with ethical and explainable perspectives. She has led various projects including Diet4You for personalized diets, INSESS-COVID19 for social vulnerability analysis, Top Rosies Talent for female AI development, and ciutadanIA for AI culture promotion. Her work spans health, environment, sustainability, tourism, and social technology applications. As an editor of Environmental Modeling and Software journal and active academic, she contributes to international conferences, working groups, and research collaborations. Her service includes membership on various ethics and AI strategy committees and advisory boards. Women Tech Award 2023 National Informatics Engineering Award in Digital Dissemination 2022 Ada Byron Award 2022 Honorific Mention of Creu Casas award 2021 donaTIC 2018 Award Finalist at AMETIC Awards 2021 Finalist of European Social Services Awards 2021
Javier Fernandez Blanco is an Associate Professor and Chair of the Department of Economics and Economic History at the University Autonomous of Barcelona (UAB), affiliated with the Barcelona School of Economics (BSE). He holds a PhD in Economics from the University of Minnesota (2008) and degrees in Economics and Mathematics from the Universitat de Barcelona. His research focuses on labor markets, public insurance design, and macroeconomic policy, with a particular interest in unemployment dynamics, household insurance mechanisms, and aging populations. He has held visiting positions at the University of Toronto (2018-19 as Visiting Associate Professor), UNSW Sydney (2012), and Carlos III University of Madrid (2008-12). His work has been published in top journals like the International Economic Review, Journal of Economic Theory, and European Economic Review. He has secured research grants, including two BSE Seed grants as Principal Investigator, and contributed to national research initiatives. He currently co-directs research projects on labor markets and education, and has advised numerous PhD and master’s students. His awards include fellowships from the Generalitat, Ramon Areces Foundation, and University of Minnesota. He actively participates in academic service, including organizing conferences, serving on editorial boards, and holding leadership roles in academic governance at UAB and BSE.
Yolanda Vidal Segui is an Associate Professor in the Department of Mathematics at the Universitat Politècnica de Catalunya (UPC), affiliated with the Escola d'Enginyeria de Barcelona Est (EEBE). Her research focuses on wind energy systems, predictive maintenance, and structural health monitoring of wind turbines. She leads projects in the CoDAlab and WinTurCoM research groups, specializing in data-driven models, condition monitoring, and failure prognosis. Her work integrates machine learning, mathematical modeling, and sensor technology to enhance turbine reliability and energy efficiency. Dr. Vidal holds a PhD in Applied Mathematics and has authored over 350 publications. Her contributions include advancements in SCADA data analysis, vibration-based diagnostics, and AI-driven condition monitoring systems. She has received several accolades, including the WindEurope Technology Workshop recognition and the IFIT Distinction in Mechanism and Machine Science. Her research bridges academia and industry, addressing challenges in offshore wind turbine integrity and maintenance strategies. Active in professional service, she serves on conference committees and editorial boards (e.g., Mechanical Systems and Signal Processing, Wind Energy). Her work emphasizes sustainable energy solutions and has been applied in real-world scenarios like the Alpha Ventus wind farm. She also contributes to educational initiatives, developing innovative teaching materials for engineering students.
