Martial Hebert serves as the Dean of the School of Computer Science at Carnegie Mellon University, a position he assumed in August 2019. He is the sixth dean to lead the school since its inception in 1988 and holds the title of University Professor of Robotics. Professor Hebert is an active participant in global AI discussions, with an upcoming speaking engagement at the AI and Planet session on May 30, 2024, where he will address "Generative AI and regulation: From local implementations to global standards." Professor Hebert is a leading researcher in the fields of computer vision and robotics. His work has contributed significantly to advancing these disciplines, which are critical components of modern artificial intelligence and autonomous systems. His expertise spans theoretical foundations and practical applications of vision systems and robotic technologies, positioning him as a key figure at the intersection of academic research and real-world AI implementation. As Dean of one of the world's most renowned computer science schools, Hebert oversees a diverse academic community dedicated to innovation and excellence in computing education and research. Under his leadership, the School of Computer Science continues to maintain its position at the forefront of technological advancement and academic achievement in the computing field, while also engaging with critical issues around AI governance and regulation.
Flavio Vasconcellos Comim is a Full Professor at IQS School of Management in Barcelona, Spain, holding the Chair of Ethics and Christian Thought (intercenter). His research focuses on the intersections of Sustainability, Economics, and Ethics. Fields of Interest : Human Development, Capability Approach, Social Exclusion, Regional Development, AI Ethics, Poverty Stigma (Aporophobia), Sustainable Development, Social Welfare, Justice, and Happiness. Recent research includes publications on youth HDI in Spain (2025), AI bias against the poor (2024), and critiques of Sen's social choice theory (2024). He leads projects like Big data applied to the study of aporophobia and Population Medicine and Sustainable Development collaborations with China. His academic output spans journals like Regional Studies , AI and Society , and Cambridge Journal of Regions, Economy and Society , with keywords spanning Economics, Machine Learning, Human Development, and Social Justice. No formal students or awards are listed in available records.
Roberto Berjón Gallinas is a Professor at the School of Computer Science, Deusto University. His research focuses on semantic technologies, internet of things, and data integration, with a strong emphasis on mobile applications and open data. He leads two research groups: ICS (Innovación en Ciencias Sociales) MARATON (Mobile applications, internet of things, data processing, semantic technologies, open data) His recent work includes developing smart tracking frameworks for IoT workflows and digital twins, event-driven architectures for IoT systems, and semantic integration solutions for university research. His projects often bridge technical innovation with practical applications in collaborative e-learning and spatial analytics. Key trends in his publications highlight advancements in IoT frameworks , semantic technologies for data integration, and real-time systems using BLE and open data. These works frequently intersect with collaborative e-learning , university transparency , and adaptive mobile platforms .
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.
Daniel Sierra Ramos is an Adjunct Professor at IE University, Spain, and Co-Founder of Fitizens, a startup developing AI-driven wearables for physical activity quantification. He has over 6 years of experience as a Lead Data Scientist at Telefónica and Synergic Partners, specializing in AI applications for industries like banking, retail, and telecommunications. His expertise includes machine learning models for customer segmentation, predictive maintenance, and demand forecasting, alongside Big Data and cloud technologies (AWS/Azure). Education: Master in Telecommunication Engineering (Carlos III University, 2015) Master in Multimedia and Communications (Carlos III University, 2015) Bachelor in Telematic Engineering (Carlos III University, 2013) His research focuses on integrating AI into wearable devices and industry-driven data solutions. He trains professionals in AI from technical and business perspectives, emphasizing autonomy in data-centric environments. Active in corporate roles since 2015, he bridges technological innovation with practical business applications.
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)
Alicia Orea Giner is a Professor at the Faculty of Economics and Business Sciences of Rey Juan Carlos University, specializing in sustainable tourism and social justice. Her research focuses on Generation Z's sustainable consumption practices in food tourism, AI integration in hospitality, and ethical dimensions of tourism. She co-authored the award-winning article The way we live, the way we travel: generation Z and sustainable consumption in food tourism experiences , recognized with the 2024 Emerald Literati Outstanding Paper Award. Her work bridges sustainability, technology, and cultural studies. Key themes include feminist methodologies in tourism research, transformative travel through ecofeminism, and post-pandemic food tourism trends. She explores AI applications in service robots, wellness tourism's mental health connections, and marginalized communities' roles in culinary tourism. Recent studies address LGBTQ+ tourism challenges, stakeholder participation in World Heritage sites, and ghost tours' cultural narratives. Awards highlight her contributions to sustainability and social justice in tourism. Awards: 2024 Emerald Literati Outstanding Paper Award Research Foci: Food Tourism, AI Ethics, Feminist Tourism Studies, Cultural Heritage Management Labs/Teams: No specific lab mentioned; collaborates across interdisciplinary tourism research networks.
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.
Bernhard Schölkopf is a Director at the Max Planck Institute for Intelligent Systems and holds a Professorship at ETH Zurich. He is one of Europe's leading researchers in Artificial Intelligence and serves as co-founder and president of ELLIS (European Laboratory for Learning and Intelligent Systems). His scientific interests focus on machine learning and causal inference, with applications spanning biomedical problems, computational photography, and astronomy. Schölkopf has conducted research at prestigious institutions including AT&T Bell Labs, GMD FIRST in Berlin, and Microsoft Research Cambridge before joining the Max Planck Society in 2001. Schölkopf's recent work examines the tangible risks of AI systems rather than speculative existential threats, highlighting important challenges including algorithmic bias, lack of transparency, privacy violations, worker exploitation, carbon footprint of AI systems, and job displacement across multiple publications in different languages. His scientific achievements have been recognized with numerous prestigious awards: Academy Prize of the Berlin-Brandenburg Academy of Sciences and Humanities Royal Society Milner Award Leibniz Award Koerber European Science Prize BBVA Foundation Frontiers of Knowledge Award Allen Newell Award Fellow of the ACM Fellow of the CIFAR Program "Learning in Machines and Brains" Schölkopf is a member of the German Academy of Sciences (Leopoldina) and co-founded the series of Machine Learning Summer Schools. His work bridges theoretical advances in machine learning with practical applications across diverse domains, while advocating for responsible AI development that addresses real-world challenges rather than speculative existential threats.
Francesc Miralles Torner is an Associate Professor affiliated with the Department of Enterprise and Technology, specializing in digital innovation, artificial intelligence, and entrepreneurial ecosystems. He leads the BOCETO: Boosting Comfort in Educational Environments project and participates in initiatives like Digital Innovation and AI as an agent for Digital Transformation . His work focuses on sustainability frameworks, innovation intermediaries, and technology's role in addressing global challenges. Academic Rank: Associate Professor Department: Enterprise and Technology Key Research Areas: Digital Innovation, Entrepreneurial Ecosystems, Sustainability, AI Recent research explores configurational approaches to startup innovativeness, orchestration of innovation networks, and digital transformation through global and sustainable lenses. His collaborations span institutions like AGAUR and international researchers.
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.
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.
Leland Bybee is an Assistant Professor of Finance at the University of Chicago Booth School of Business . He leverages machine learning and natural language processing to address economic and financial questions, particularly focusing on belief measurement with applications to asset pricing and behavioral economics. Ph.D. in Financial Economics, Yale School of Management (2024) M.S. in Statistics, University of Michigan (2017) B.A. in Economics, University of Chicago (2013) His research integrates computational methods with economic theory to analyze: Textual analysis of business news for macroeconomic tracking Narrative-driven asset pricing models Memory-based belief formation using kernel methods Macroeconomic determinants of currency returns He has received multiple awards including: Dimension Fund Advisors Distinguished Paper Award BlackRock Applied Research Award HEC Top Finance Graduate Award The Brattle Group PhD Candidates Award EFA Engelbert Dockner Memorial Prize Bybee teaches Machine Learning in Finance and participates in finance seminars, contributing computational tools like regIPCA (Python) and changepointsHD (R) to the research community.
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
