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 .
Antonio González is a full Professor at the Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC), where he is affiliated with the Department of Computer Architecture. He leads the Microarchitecture and Compilers (ARCO) research group, focusing on robust and energy-efficient computing systems, including general-purpose processors, GPUs, and cognitive computing architectures. His research spans computer architecture, microarchitecture, compilers, GPU design, and deep learning acceleration, with a strong emphasis on energy efficiency and memory optimization. His work integrates hardware and compiler techniques to enhance performance in modern computing systems. The recent publications highlight a strong trend in energy-efficient DNN acceleration, GPU microarchitecture, memory systems, and near-data processing. His team explores novel quantization methods, adaptive caching, and architectural extensions for vision and AI workloads, published in top-tier venues such as MICRO, ISCA, and IEEE/ACM journals. ACM Fellow (2020) ICREA Academia Award (2014, 2019, 2024) UPC Duran Farell Award (2008) HiPEAC 2024 Paper Award (twice) González has supervised several PhD students and leads competitive R&D+i projects, including those funded by ICREA and the European Research Council. His research group collaborates extensively within UPC and with international institutions. He is actively involved in advancing computer architecture through innovation in simulation, hardware design, and AI acceleration. He is a member of IEEE and ACM, and his work continues to influence both academic and industrial developments in high-performance and energy-efficient computing.
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)
Nicolò Cesa-Bianchi is a Professor of Computer Science at the University of Milan, where he serves as head of the Computer Science programs. He is also associated with the Department of Electronics, Information and Bioengineering (DEIB) at Politecnico di Milano. Cesa-Bianchi holds significant leadership roles including Board member, Fellow and co-director of the Milan unit of the European Laboratory for Learning and Intelligent Systems (ELLIS), and membership in the prestigious Accademia Nazionale dei Lincei. He is also involved with The European Lighthouse on Secure and Safe AI (ELSA), The European Lighthouse of AI for Sustainability (ELIAS), and The FAIR foundation. Professor Cesa-Bianchi's research focuses on the theoretical foundations of machine learning, with special emphasis on sequential decision making and online learning algorithms. His work spans multiple areas including multi-armed bandit problems, regret analysis, prediction with expert advice, and learning on graphs. He has made significant contributions to understanding the theoretical limits of learning algorithms and developing efficient methods for various learning scenarios. His research has important applications in online markets, social networks, and bioinformatics. His monographs 'Prediction, Learning, and Games' and 'Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems' are considered seminal works in the field. His recent publications demonstrate continued leadership in advancing the theoretical understanding of machine learning, with 2024-2025 papers covering cooperative online learning, multitask learning, fair trade mechanisms, and refined analyses of bandit algorithms. The research shows increasing focus on practical economic applications while maintaining strong theoretical foundations. Google Research Award Xerox Foundation UAC Award Member of the Accademia Nazionale dei Lincei ELLIS Fellow Cesa-Bianchi has been deeply involved in academic service, having served as action editor for the Machine Learning Journal, IEEE Transactions on Information Theory, and the Journal of Machine Learning Research. He currently serves as associate editor for the Journal of Information and Inference and TheoretiCS. He has held leadership positions including President of the Association for Computational Learning and member of the steering committee for the EC-funded Network of Excellence PASCAL2. He was program chair of the 13th Annual Conference on Computational Learning Theory and the 13th International Conference on Algorithmic Learning Theory. He leads the Laboratory for AI and Learning Algorithms (ALGA) at the University of Milan, which focuses on theoretical and applied research in machine learning. His international collaborations are extensive, with visiting positions at UC Santa Cruz, Graz Technical University, Ecole Normale Supérieure in Paris, Google, and Microsoft Research. As an educator, he teaches advanced courses including Reinforcement Learning and Statistical Methods for Machine Learning, and has supervised numerous students through the years.
Miguel Ángel Bernal Merino serves as a Part-Time Lecturer in the Department of Modern Philology, Translation and Interpretation at the University of Las Palmas de Gran Canaria. Concurrently, he acts as convener of the MA in Translation at the University of Roehampton in London, managing its Specialised Translation, Audiovisual Translation, and Intercultural Communication pathways since 2005. His academic profile bridges theoretical research and industry application in localization disciplines. PhD in The Localisation of Video Games, Imperial College London MSc in The Localisation of Multimedia Interactive Entertainment Software, Imperial College London Certificate in Software Localisation, University of Limerick CELTA, University of Cambridge MPhil in Lip-Synched Dubbing, Universidad de Alicante MA in Hispanic Literature, University of Rhode Island BA in English & Spanish Linguistics, Universidad de Alicante Bernal Merino's research pioneers the expansion of Translation Studies into interactive media domains. His work on video game localization examines interactivity, cultural adaptation, glocalisation, and playability, while his audiovisual translation research investigates creativity in lip-synched dubbing, subtitling, and audiodescription. He extends these frameworks into gaming-based language learning through haptic environments and multisensory reinforcement, exploring physiological aspects of multilingual cognition and polysemiotic neural networks. This multidisciplinary approach fundamentally challenges traditional boundaries in translation theory. His publication trajectory reveals evolving industry-academia integration, shifting from foundational game localization frameworks (2008-2015) toward user-centered research and educational applications (2018-2024). Recent work emphasizes measurable business impacts through quality localization, regional market adaptations, and crowd-sourced methodologies, demonstrating consistent influence on professional standards across gaming and translation sectors. Fellow of the Higher Education Academy Bernal Merino supervises doctoral research on mobile game localization, transmedia fan experiences, and historical game content translation while developing industry-academia pipelines through projects like AHRC's Media Across Borders. His funded initiatives—including Maximising ROI through Quality Game Localisation and Video Games for Language Learning—bridge theoretical innovation with commercial implementation, focusing on glocalisation strategies, interactivity metrics, and playability optimization. These collaborations connect European universities, gaming studios, and localization service providers. As chair of the IGDA Localization SIG and member of GIR Discourse, Communication and Society, he directs international forums for game localization discourse. His work with Routes into Languages promotes audiovisual media in language education, while REF-readiness collaborations enhance research excellence across European institutions through his professional network spanning industry conferences like GDC Summit and Game Global.
Michalis Vazirgiannis is a Professor at LIX, École Polytechnique (France) leading the Data Science and Mining (DaSciM) group. With academic backgrounds in Physics (Athens University), AI (Heriot-Watt University), and Informatics (Athens University), he has conducted research at Fraunhofer, Max Planck MPI, and INRIA/FUTURS while teaching at institutions across Greece, France, China, and Spain. His research spans Machine/Deep Learning for Graphs (GNNs, graph kernels, embeddings) Text Mining & NLP (Graph-of-Words, biomedical text analysis) Combinatorial Optimization for pandemic forecasting and energy systems Event/Anomaly Detection in time series and sensory data Industrial collaborations with Airbus, Google, Tencent, and BNP . He has supervised 29 completed PhD theses, published over 250 papers, and received prestigious awards including Marie Curie and Tencent Rhino-Bird Fellowships. His team leads the ANR-HELAS Chair (2020-2025) focusing on heterogeneous data deep learning.
Jordi Perelló Muntan is an Associate Professor in the Department of Computer Architecture at the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, where he is also affiliated with the Escola Tècnica Superior d'Enginyeria de Telecomunicació de Barcelona (ETSETB). He is a member of the Broadband Communications Systems and Architectures (CBA) and IDEAI-UPC research groups, focusing on advanced optical and future internet networking technologies. Research Interests: His research spans telecommunications networks, optical fiber and optical networking, resource optimization, network architectures, and the Future Internet. He investigates performance optimization in 5G transport networks, Spatial Division Multiplexing (SDM), Recursive Inter-Network Architecture (RINA), elastic optical networks, and cognitive networking. His work integrates SDN, network virtualization, and green networking principles for scalable and efficient infrastructures. Publication Trends: His recent publications focus on probabilistic constellation shaping in multicore fiber networks, cognitive strategies for optical margin reduction, RINA-based QoS assurance, and migration planning toward spectrally-spatially flexible optical networks. These reflect a strong trend toward intelligent, adaptive, and energy-efficient network design for future communication systems. Scientific Awards: Co-recipient of the 2020 Fabio Neri Best Paper Award Runner-up (Elsevier Journal of Optical Switching and Networking) Co-recipient of the ONDM 2021 Best Paper Award Co-recipient of the 2019 IEEE Communications Society Charles Kao Award Co-recipient of the ONDM 2012 Best Student Paper Award Advising and Grants: He has advised multiple PhD students on topics including RINA, optical network planning, and virtual provisioning. He has led or participated in major European (H2020, FP7) and national (PID, TEC) research projects such as SLICENET, PRISTINE, TRAINER, and ALLIANCE, focusing on 5G, RINA, and sustainable network infrastructures. Labs and Teams: He is an active member of the CBA research group at UPC, contributing to experimental and theoretical advancements in optical and programmable networks. His team collaborates internationally on testbed development and standardization efforts in next-generation networking.
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.
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.
Gil Serrancoli Masferrer is an Associate Professor in the Department of Mechanical Engineering at the School of Engineering of East Barcelona (EEBE), part of the Polytechnic University of Catalonia (UPC). He is affiliated with the InSup - Research Group in Surface Interaction in Bioengineering and Materials Science and the LAM - Multimedia Applications and ICT Laboratory. His work focuses on biomechanics, computational modeling, and telerehabilitation systems development for clinical applications. Dr. Serrancoli's research spans multisolid dynamics, dynamic optimization, movement simulation, and telerehabilitation systems. His expertise lies in applying computational techniques to solve complex problems in orthopedics, gait analysis, and rehabilitation engineering. His work bridges mechanical engineering with biomedical applications, particularly in musculoskeletal modeling and simulation of orthopedic procedures. He has developed novel computational frameworks for estimating internal musculoskeletal loading and muscle adaptation in various conditions, including hypogravity environments. His recent publications demonstrate a strong focus on in-silico modeling of orthopedic procedures, particularly knee osteotomies (proximal fibular osteotomy versus high tibial osteotomy), with detailed analysis of joint pressure redistribution. He has also pioneered the application of machine learning techniques, particularly recurrent neural networks, to biomechanical problems including cycling biomechanics and running dynamics prediction. His work consistently integrates computational efficiency with clinical relevance. Technical Award - OpenSim+ Advanced Workshop March 2024 Accésit del XLV Congreso de la Sociedad Ibérica de Biomecánica y Biomateriales European Society of Biomechanics Travel Award OpenSim Virtual Workshop - Technical Award OpenSim Visiting Scholar 2017 Enginyers BCN 2018 Dr. Serrancoli leads several competitive R&D projects including 'Muvity: a novel physical telerehabilitation system' for vulnerable populations and 'Simulaciones predictivas in silico para cirugías ortopédicas' (Predictive in-silico simulations for orthopedic surgeries). He collaborates extensively with researchers across Europe, particularly with Jordi Torner, Josep Maria Font Llagunes, and Joan Carles Monllau, and has secured funding from national and regional programs including Plan Estatal de Investigación Científica y Técnica y de Innovación. He is actively involved in the BIOMEC - Biomechanical Engineering Lab and the TecSalut - Research Group in Health Technologies, where he contributes to the development of innovative solutions for healthcare challenges, particularly in the areas of telerehabilitation and computational biomechanics for orthopedic applications.
Andrea Ianiro is a Full Professor in the Aerospace Engineering Department at Universidad Carlos III de Madrid (UC3M), where he leads research in fluid dynamics, turbulence, and heat transfer. His work bridges experimental techniques and machine learning applications for flow analysis and control. He serves as Associate Editor of the International Journal of Heat and Mass Transfer (2025-2028) and directs the EFM Lab (Experimental Fluid Mechanics Laboratory) at UC3M. Professor Ianiro's research focuses on turbulence characterization, boundary layer flows, and the application of machine learning to fluid mechanics problems. His work spans experimental techniques including Particle Image Velocimetry (PIV), infrared thermography, and advanced data processing methods. Recent research emphasizes data-driven approaches for flow field reconstruction, turbulence control, and heat transfer optimization in wall-bounded flows. His projects often combine theoretical, experimental, and computational approaches to address complex fluid mechanics challenges. The analysis of his recent publications reveals a strong trend toward integrating machine learning with traditional fluid mechanics. His work increasingly focuses on using deep learning techniques (particularly CNNs and GANs) for flow field prediction from limited measurements, developing meshless computational methods for flow analysis, and applying optimization techniques (including genetic algorithms) to heat transfer enhancement. His research maintains a strong experimental foundation while embracing data-driven approaches to tackle turbulence modeling challenges. Associate Editor of the International Journal of Heat and Mass Transfer (2025-2028) Professor Ianiro leads multiple significant research projects including SPANDRELS (SParse AND paRsimonious Event-based fLow Sensing, 2025-2030), HumanIC (Human-Centric Indoor Climate for Healthcare Facilities, 2024-2027), and EXCALIBUR (Extraction of machine learning strategies for turbulent flow control, 2023-2026). His work has attracted funding from the European Commission, Spanish National Research Agency, and industry partners including Airbus. He has supervised numerous theses on topics including AI-based sensing of turbulent flows, convective heat transfer control, and turbulent boundary layers. At UC3M, Professor Ianiro directs the Experimental Fluid Mechanics Laboratory (EFM Lab), which focuses on advanced measurement techniques for fluid flow and heat transfer characterization. The lab specializes in PIV/PTV techniques, infrared thermography, and the development of novel experimental approaches for turbulence research. Current research directions include machine learning applications for flow field reconstruction, plasma-based flow control, and heat transfer optimization in complex flow configurations.
Yuan Zhong is an Associate Professor of Operations Management at the University of Chicago Booth School of Business . He previously held positions as an Assistant Professor at Columbia University’s Department of Industrial Engineering and Operations Research and was a Postdoctoral Scholar at UC Berkeley’s Computer Science Department. Education: PhD in Operations Research, MIT (2012) MA in Mathematics, Caltech (2008) BA in Mathematics, University of Cambridge (2006) His research focuses on applied probability and stochastic system design , with applications in cloud computing , supply chain management , and e-commerce logistics . Recent work explores multi-period production systems and dynamic resource allocation in data centers and healthcare operations . Recent publications analyze cloud value chains , sparse graph design for delivery networks, and process flexibility in manufacturing. He has contributed to journals like Operations Research , Annals of Applied Probability , and Stochastic Systems . Scientific Awards: 2012 Kenneth C. Sevcik Outstanding Student Paper Award Best Student Paper Award at ACM Sigmetrics (2012) He teaches courses in business process fundamentals and queueing theory , with a future schedule including Operations Management: Business Process Fundamentals (2025–2026). No explicit student advising list was provided.
Jordi Guitart Fernández is a Professor at the Department of Computer Architecture, Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC). He is also affiliated with the Barcelona Supercomputing Center (BSC-CNS), a leading national supercomputing facility. He leads the CROMAI research group, focusing on Computing Resources Orchestration and Management for AI. His work bridges high-performance computing, cloud systems, and artificial intelligence. Research Interests: Cloud Computing and Edge Computing Green and Energy-Efficient Computing Containerization and Virtualization for HPC Resource Orchestration and Management Autonomic and Self-Adaptive Systems Machine Learning Workflow Management AI-Driven System Optimization His recent publications reveal a strong focus on intelligent management of computing resources across cloud, edge, and HPC environments using machine learning and agent-based frameworks. He investigates performance, efficiency, and reliability in containerized AI and HPC workloads, particularly within Kubernetes and distributed infrastructures. His work increasingly integrates human-in-the-loop and trustworthiness aspects into AI systems. Scientific Awards: CLOUD Conference 2025 Best Paper Award VISIGRAPP 2025 Best Student Paper Award Premi Extraordinari de Doctorat 2025 - Àmbit d'Enginyeria de les TIC Test of Time Award Honorable Mention (e-Energy) Reconeixement als Mèrits Docents d'Especial Qualitat Top reviewers for Polytechnic University of Catalonia (Computer Science) - September 2017 Advising and Grants: He has advised doctoral students, including Peini Liu. He leads and participates in numerous competitive R+D+i projects, such as CROMAI and DALEST, funded by national and European programs like HORIZON 2020 and the Spanish State Research Plans. His work is supported by grants focused on knowledge generation and industrial leadership in computing technologies. Labs and Teams: He is the leader of the CROMAI - Computing Resources Orchestration and Management for AI research group at UPC. He also collaborates closely with the Barcelona Supercomputing Center (BSC-CNS), contributing to large-scale computing initiatives and strategic research agendas in Europe.
