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.
Felix Gomez Marmol is an Associate Professor at the University of Murcia's Faculty of Informatics, Department of Information and Communication Engineering. His research focuses on cybersecurity, artificial intelligence, network security, and IoT security. He holds a PhD in Computer Science from the University of Murcia (2010), supervised by Dr. Gregorio Martínez Pérez. Key research interests include adaptive intrusion detection systems, dark web analysis, and AI-driven cybersecurity frameworks. He leads the Intelligent Systems and Telematics research group and previously contributed to the Sistemas Inteligentes group. His work emphasizes practical applications such as the SCORPION Cyber Range platform for cybersecurity training and gamification. Recent projects involve detecting hate networks on social media, optimizing malware defense using transfer learning, and developing SIEM systems for IoT environments. His contributions span technical papers on cybersecurity education, ethical hacking fundamentals, and blockchain-based security solutions. Prof. Gomez Marmol has collaborated on initiatives like the COBRA framework for simulating advanced persistent threats (APTs) and the COnVIDa dashboard for pandemic-related data analysis. His research bridges theoretical advancements with real-world cybersecurity challenges.
Paolo Rota is a tenure-track Assistant Professor at the University of Trento, affiliated with the Department of Information Engineering and Computer Science (DISI) and the Center for Mind/Brain Sciences (CIMeC). His research lies at the intersection of computer vision, machine learning, and multimodal AI, with a strong emphasis on vision-language models and activity recognition. His research interests include zero-shot action recognition, temporal action localization, open-world recognition, and person image synthesis. He explores how large multimodal models can be leveraged for practical applications in video analytics and industrial AI, often developing training-free or source-free adaptation methods that improve model generalization. Recent publications show a consistent trend in utilizing large vision-language models (e.g., CLIP, LMMs) for tasks such as image classification, domain adaptation, and action recognition, emphasizing simplicity, zero-shot capabilities, and real-world applicability. His work frequently appears in top venues including CVPR, NeurIPS, ICCV, and ICIAP. He actively mentors PhD students including Benedetta Liberatori, Jiaqi Liu, Yan Shu, Shiyao Xu, and Alessandro Conti, often co-advising with faculty such as Elisa Ricci and Nicu Sebe. He also contributes to teaching, including delivering lectures on machine learning for the MSc in Data Science program. He co-founded Mountain Maps, a startup using AI to enhance outdoor navigation and mountain exploration. His work bridges academic research and practical innovation, aiming to increase the real-world impact of AI systems.
Chelo Vargas Sierra is a Professor at the University of Alicante, affiliated with the Department of English Philology within the Faculty of Philosophy and Letters I (Philology). As a founding member and director since 2021 of the Interuniversity Institute of Applied Modern Languages (IULMA), she leads innovative research in terminology and translation technologies. Her academic background includes a PhD in Translation and Interpreting, a Master's in Audiovisual Translation (University of Cádiz), and a Master's in Terminology (Universitat Pompeu Fabra). PhD in Translation and Interpreting (University of Alicante) Máster en Traducción Audiovisual (University of Cádiz) Máster en Terminología (Institut Universitàri de Llingüística Aplicada) Her research focuses on terminology applied to translation, specialized languages (English-Spanish), corpus linguistics, and gender-sensitive terminology. She directs the DIGITENDER project (TED2021-130040B-C21) for digitizing multilingual terminological resources. She has participated in over 90 international conferences and chaired events like enTRetextos 2021 and AESLA 2016. Recent publications highlight trends in metaphor analysis in medical discourse, gender-sensitive terminology, and cross-linguistic sentiment studies in financial journalism. She chairs the Technical Standardisation Committee 191 for Terminology and has delivered 50+ international seminars for institutions like the European Union. Doctorate Extraordinary Award She serves on editorial boards of journals like Ibérica and Sendebar , contributes to translation technology training, and collaborates in international academic programs. Her work combines theoretical research with practical applications in translation technologies and terminological standardization.
Horacio Saggion is the Chair in Computer Science and Artificial Intelligence at the Department of Information and Communication Technologies, Universitat Pompeu Fabra. He leads the TALN Group and the Large Scale Text Understanding Systems Lab. His research focuses on Computational Linguistics, with specialties in Text Summarization, Information Extraction, and Semantic Analysis. He coordinates the Horizon Europe iDEM project on inclusive democratic spaces and previously led the SignON project for Sign Language Translation. Key technologies include the SUMMA Summarization system and the Dr Inventor Text Mining Library. Education: PhD, MSc, and Licenciatura in Computer Science. Research Interests: Text simplification for accessibility, sign language translation, misinformation detection, and ethical AI applications. His work bridges natural language processing with societal needs such as clear communication in public administration. Grants & Projects: Coordinator of iDEM (Horizon Europe), PI of SignON, Simplext, and Able to Include. Involved in BEA shared tasks and CLEF labs. Active in organizing workshops like TSAR at EMNLP. Labs & Teams: Head of TALN Group and Text Understanding Lab. Collaborations include Universitat Pompeu Fabra's interdisciplinary initiatives and industry partnerships for technology commercialization.
Silvia Jiménez Fernández is an Associate Professor in the Department of Signal Theory and Communications at Universidad Autónoma de Madrid. Her research focuses on optimization algorithms, smart grids, renewable energy systems, telemedicine, and machine learning applications. She holds a Ph.D. from Universidad Politécnica de Madrid (2009), supervised by Dr. Francisco del Pozo Guerrero and Dr. Paula de Toledo Heras. Her work integrates interdisciplinary approaches, such as combining evolutionary algorithms with engineering challenges in energy systems and healthcare. Key contributions include advancements in coral reefs optimization algorithms for energy management, machine learning for battery health estimation, and telemedicine systems for chronic disease monitoring. Recent research trends emphasize hybrid learning models in education, multi-objective optimization in renewable energy systems, and risk analysis in smart grids with electric vehicles. She is affiliated with the GHEODE Research Group (Modern Heuristics and Network Design).
Dr. Silvia Martínez Martínez is a Researcher in the Department of Philology and Translation at the University of Granada, specializing in German Philology with a PhD completed in 2015. Her academic work centers on accessibility in audiovisual translation, particularly subtitling for the deaf and hard of hearing (SpS), and audio description across multilingual contexts. Her research interests include: Audiovisual Translation Accessibility for Deaf and Hard of Hearing Subtitling for the Deaf Translation Technology German-Spanish Translation Audio Description Terminology Analysis of her 15 most recent publications (2022-2025) reveals dominant trends in AI-driven accessibility solutions, cross-linguistic corpus studies (German/Spanish/English), and innovative pedagogical applications. Key thematic clusters include sound translation in streaming/VOD platforms, gamification in STEM education, vitivinicultural terminology, and cultural adaptation in music translation, demonstrating her interdisciplinary approach spanning translation technology, medical accessibility, and sociological studies. She has received the Premio Francisco Ayala (2012) for her contributions to translation studies, recognizing her work on accessibility frameworks and specialized translation methodologies. Dr. Martínez Martínez actively contributes to educational innovation through projects like DESAM (accessible museum resources) and OPERA (cultural accessibility), while her supervision of PhD candidates and development of didactic tools for audio description training underscore her commitment to advancing inclusive translation practices in academic and professional settings.
Julian Fierrez is a Full Professor at the School of Engineering, Universidad Autonoma de Madrid. With an h-index of 74 and over 20,000 citations, his work spans biometrics, signal/image processing, artificial intelligence, and human-computer interaction. Key research areas include: Biometric anti-spoofing and DeepFakes detection Mobile and behavioral biometrics Bias/fairness in AI systems Biometric applications in e-health and education Security in multimodal biometric systems His recent publications show strong focus on deep learning applications for biometric security, with specific subfields including fake detection, keystroke authentication, facial analysis for Parkinson detection, and privacy-preserving AI. He serves as Associate Editor for multiple IEEE and Elsevier journals. Scientific distinctions include: IAPR Young Biometrics Investigator Award (2017) Miguel Catalan Award to Best Researcher under 40 (2017) EURASIP Best PhD Award (2012) EBF European Biometric Industry Award (2006) Prof. Fierrez leads the BiDA Lab and supervises students like Ruben Tolosana and Aythami Morales. Current projects include BBforTAI (Biometrics and Behavior for Unbiased & Trustworthy AI) and PRIMA (Privacy Matters). He also contributes to standardization efforts in biometric evaluation.
Belen Masia is a tenured Associate Professor in the Computer Science Department at Universidad de Zaragoza , Spain. She is affiliated with the Graphics & Imaging Lab (part of the I3A Institute ) and the Vision, Image and Neurodevelopment Group (within the IIS Aragon Institute ). Her research bridges computational imaging , applied perception , and virtual reality , focusing on modeling human visual behavior and improving graphics/vision algorithms through perceptual insights. Education : Ph.D. in Computer Science (Eurographics PhD Award 2015), postdoctoral work at Max Planck Institute for Informatics . Research Highlights : Virtual Reality : Studying user behavior, saliency prediction, multimodal perception, and cinematography in VR. Appearance Modeling : Developing intuitive material representations and metrics for editing. Applied Perception : Leveraging human vision insights to diagnose defects in non-verbal patients. Computational Displays : Exploring HDR imaging and display optimization. Scientific Awards : Eurographics Young Researcher Award 2017 Eurographics PhD Award 2015 MIT Technology Review Top Ten Innovators Below 35 in Spain 2014 NVIDIA Graduate Fellowship 2012 Leonardo Fellowship from BBVA Foundation 2020 Leadership & Editorial Roles : Co-chair of Full Papers track at Eurographics 2026 Associate Editor for ACM Transactions on Graphics, Computers and Graphics, and ACM Transactions on Applied Perception Co-founder of DIVE Medical , a startup for automated visual function diagnosis PhD Students : Dario Lanza (2025, Modeling, Perception and Editing of Volumetric Materials ) Daniel Martin (2024, Computational Models of Visual Attention in VR , Best PhD Thesis Award EGSE) Julia Guerrero-Viu (2023, WiGRAPH Rising Star) Sandra Malpica (2023, VR Gaze Behavior ) Manuel Lagunas (2021, BBVA/SCIE Young Researcher Award) Ana Serrano (2019, Eurographics PhD Award & Unizar Outstanding Thesis) Collaborations & Grants : Involved in the EU-funded PRIME Innovative Training Network (predictive rendering and appearance reproduction) and leading projects on deep learning for pediatric visual diagnosis.
Cecilio Angulo Bahón is a full Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Barcelona School of Industrial Engineering (ETSEIB) and the Department of Systems, Automatics and Industrial Informatics Engineering . He leads research in Artificial Intelligence and Robotics , with significant contributions to healthcare data analytics, digital twins, and human-robot collaboration. His research spans machine learning for medical data harmonization, generative adversarial networks in health informatics, and evolutionary algorithms for control systems. Recent publications focus on synthetic healthcare data generation, climate-resilient agriculture , and UMAP-based data analysis . His work bridges AI theory with practical applications in industrial and healthcare domains. Scientific awards include the Sant Jordi 2023 Digital Polytechnic Initiative Award . He has supervised doctoral candidates like Carlos Flores-Vázquez and N. Raya, with key collaborations at the IDEAI-UPC Intelligent Data Science and AI Research Group and the Institute of Robotics and Industrial Informatics (CSIC-UPC).
Francisco Javier Oliver Bernal is a Lecturer at the University of Deusto in Bilbao, Spain, within the Faculty of Education and Sport and the Department of Physical Activity and Sports Sciences. He teaches across Computer Engineering, Physical Activity and Sports Sciences, and Primary Education bachelor's programs, as well as the Master's in Secondary Education. He earned his Doctor of Medicine and Surgery from the University of the Basque Country. His research spans Human-Computer Interaction, Educational Technology, and Science Education, with a strong emphasis on accessibility for visually impaired users. He has developed tools for e-learning, digital resource centers, and innovative teaching methodologies in computer science and natural sciences, aiming to enhance educational experiences through technology. His scholarly output, spanning from the 1990s to 2023, demonstrates a consistent focus on technology-enhanced learning, evolving from early work in 3D interfaces and computer graphics to recent applications in health, music, and interdisciplinary educational contexts. Key trends include the integration of accessibility features, the development of domain-specific educational tools (e.g., for biology and astronomy), and responses to contemporary challenges like the COVID-19 pandemic. He has supervised multiple theses on digital accessibility and cooperative systems, though student names were not listed. Details on research grants were not provided in the available text. As a member of the eVida research group (officially recognized by the Basque Government), he contributes to projects advancing accessible educational technologies, including the ACCE project for audiovisual accessibility and READIS digital resource centers for visually impaired users.
Bernardino Casas Fernández is an Adjunct Professor at the Departament de Llenguatges i Sistemes Informàtics (LSI) of Universitat Politècnica de Catalunya (UPC). He holds offices at both the Vilanova i la Geltrú campus (EPSEVG-VG1, Room 120) and the Barcelona campus (Campus Nord-Edifici Omega, Room 224). His research focuses on quantitative linguistics, natural language processing, polysemy analysis, and computational linguistics. He has contributed to open-source tools like FreeLing and projects such as CARPANTA for email summarization. Recent work explores semanticity in Catalan using large language models and ethical implications of generative AI in education. He maintains active involvement in computational linguistics and child language development studies. Education details are not explicitly listed, but his academic career spans from 2003 (earliest article) to 2024. He collaborates with initiatives like LAPPS (Language Acquisition and Processing Systems) and has participated in projects involving churn prediction systems and entropy estimation techniques.
Gustavo Deco is a Research Professor at the Institució Catalana de Recerca i Estudis Avançats (ICREA) and holds a Professorship (Catedrático) at Pompeu Fabra University (UPF). He leads the Computational Neuroscience Group and directs the Center of Brain and Cognition at UPF. His research focuses on computational models of brain dynamics, integrating biophysics, neuroimaging, and complex systems principles. Deco’s academic journey includes a PhD in Physics (1987, thesis on Relativistic Atomic Collisions), postdoctoral work at the University of Bordeaux (France) and University of Giessen (Germany), and a Habilitation in Computer Science (1997, Technical University of Munich). He has led computational neuroscience research at Siemens Corporate Research Center (1990–2003) and pioneered whole-brain modeling frameworks like The Virtual Brain (TVB). His research interests span critical brain dynamics, non-equilibrium thermodynamics in neural systems, psychedelics’ effects on brain hierarchy, and clinical applications of computational models in disorders such as Alzheimer’s and depression. Recent work emphasizes turbulence-like dynamics in healthy and diseased brains, and biomarker discovery using AI-driven simulations. Deco’s articles (2024–2025) explore topics like entropy production in brain networks, psychedelics-induced flattening of functional hierarchies, sleep-like dynamics post-stroke, and the role of long-range connections in global brain communication. His work bridges theoretical models with clinical insights, aiming to advance personalized neurology and digital brain research.
Ruben Tolosana is a researcher at the Biometrics and Data Pattern Analytics Lab (BiDA Lab) in the School of Engineering at Universidad Autónoma de Madrid. His work centers on biometrics, with emphasis on behavioral and mobile authentication, face recognition, privacy-enhancing technologies, and deep learning applications in human-computer interaction. He actively contributes to major research initiatives such as the FRCSyn-onGoing challenge and the ChildCI framework. PhD in Computer Science or related field (inferred from publication volume and role) Advanced training in machine learning, computer vision, and biometrics His research interests include behavioral biometrics, mobile device security, synthetic data for AI training, privacy in biometric systems, and the application of Transformer models to user authentication. Tolosana's work often involves the development of novel datasets and benchmarking platforms to advance the field. He has co-authored influential surveys on privacy vulnerabilities in mobile sensors and privacy-preserving techniques in biometric recognition. The most recent articles highlight trends in using synthetic data for face recognition, applying Transformers to behavioral biometrics (keystroke, touchscreen, gait), and developing frameworks for child age detection via interaction patterns. His work consistently addresses real-world challenges such as privacy, bias, and system generalization. Publications in journals like Information Fusion , Pattern Recognition , and ACM Computing Surveys reflect the high impact and interdisciplinary nature of his research. Second FRCSyn-onGoing: Winning solutions and post-challenge analysis to improve face recognition with synthetic data (2025) ChildCI framework: Analysis of motor and cognitive development in children-computer interaction for age detection (2024) FRCSyn-onGoing: Benchmarking and comprehensive evaluation of real and synthetic data to improve face recognition systems (2024) SwipeFormer: Transformers for mobile touchscreen biometrics (2024) An Overview of Privacy-Enhancing Technologies in Biometric Recognition (2024) Ruben Tolosana collaborates extensively with researchers in the BiDA Lab, including Rubén Vera-Rodríguez, Aythami Morales, Julian Fierrez, and others. He has contributed to the development of public databases such as mEBAL and ChildCIdb, supporting open science. His work is supported by ongoing research grants (inferred from project scope and publications), and he plays a key role in organizing workshops such as WAMWB to advance the mobile and wearable biometrics community. He is a core member of the Biometrics and Data Pattern Analytics Lab (BiDA Lab), a leading research group in biometric technologies, where he contributes to multiple projects involving mobile authentication, face recognition, and privacy-preserving AI systems.
Eneko Agirre is a Full Professor at the Faculty of Computer Science of the University of the Basque Country UPV/EHU, where he serves as the director of the HiTZ Centre on Language Technology. He is an active member of the Ixa Research Group and has established himself as a leading figure in Natural Language Processing, particularly in multilingual and low-resource language settings. His work bridges theoretical advances with practical applications for language technology. Agirre received his PhD from the University of the Basque Country in 1999 with a thesis on conceptual relationships and ontologies, supervised by Dr. Kepa Sarasola Gabiola and Dr. Arantza Díaz de Ilarraza Sánchez. His academic journey has been marked by significant contributions to computational linguistics and language technology. His research primarily focuses on Natural Language Processing challenges, with special emphasis on Word Sense Disambiguation, cross-lingual transfer learning, dialogue systems, and Large Language Models for low-resource languages. He has pioneered work on Basque language technology and has consistently addressed the challenges of multilingual AI systems, particularly examining how language models perform across different linguistic contexts and cultural settings. Analysis of his recent publications reveals a strong trajectory toward advancing Large Language Models for low-resource languages, with particular attention to Basque. His work spans vision-language models, information extraction techniques, and rigorous evaluation methodologies for NLP systems. A recurring theme is the exploration of how language models handle low-resource languages compared to high-resource ones, with groundbreaking findings about cultural knowledge transfer between languages. Fellow of the ACL (2021), one of only 74 research leaders worldwide National Research Prize on Informatics (2021) Best resource paper award at ACL 2024 Honourable mention paper award (top 1%) at EMNLP (2020) Outstanding Paper award (top 2%) at COLING (2020) Recipient of three Google Faculty Research Awards (2017, 2018, 2019) Agirre has supervised over 25 PhD students, many of whom have received prestigious awards including the EurAI Artificial Intelligence PhD Dissertation Award. His research has been supported by numerous European projects including LIHLITH (2018-2020) on lifelong learning for dialogue systems, and he has served as principal investigator for multiple CHIST-ERA and FP7 projects. His work with Google includes collaborative projects on entity dictionaries and conversational question answering systems. As director of the HiTZ Centre on Language Technology and member of the Ixa Research Group, Agirre leads a vibrant team focused on advancing language technology for Basque and other under-resourced languages. The center has developed significant resources including Latxa, an open language model for Basque, and has established itself as a hub for multilingual NLP research. His group actively collaborates with international institutions including Stanford, NYU, and various European universities, fostering a global network for language technology research.
