Jan Eeckhout is an ICREA Research Professor at Pompeu Fabra University (UPF) in Barcelona, specializing in macroeconomic theory, labor markets, and urban economics. His work focuses on market power dynamics, wage inequality, and technological impacts on labor and urban systems. He holds a PhD from the London School of Economics (LSE). Eeckhout has received a prestigious ERC Advanced Grant (€2.45M) for research on 'Macro Market Power and Distribution.' He authored the influential book The Profit Paradox (2021), exploring how dominant firms reshape labor markets and economies, translated into multiple languages. His research frequently appears in top journals like the Quarterly Journal of Economics and Review of Economic Studies. Research Interests: Macro-Labor Theory, Labor Markets, Urban Economics, Market Power, and Economic Inequality. Recent work examines technological origins of labor market stagnation, IT-driven urban polarization, and wealth effects on worker productivity. Advising and Grants: Supervises PhD students (e.g., Milena Djourelova, David Puig) and collaborates with institutions globally (CEMFI, EUI, Sciences Po). His team includes co-authors like Jan De Loecker and Philipp Kircher. Active in policy discussions via think tanks and media outlets like VoxEU and the NYT. Labs/Teams: Leads a diverse research group at UPF, with projects on market power, urban economics, and labor dynamics.
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.
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.
Seth Blumsack is a Professor at the Pennsylvania State University in the Department of Energy and Mineral Engineering and serves as Director of the Center for Energy Law and Policy . He holds an Adjunct Research Professor position at the Carnegie Mellon Electricity Industry Center and is affiliated with the Santa Fe Institute as an External Faculty member. His research spans energy economics , power grid reliability , and complex infrastructure networks . Key projects include: Interdependent natural gas and electricity systems analysis Governance of regional transmission organizations Smart grid consumer behavior studies Power grid reliability tools development He has secured funding from the U.S. National Science Foundation , Department of Energy , Environmental Protection Agency , and private industry. His Best paper award at Hawai’i International Conference on System Sciences (2011) and John T. Ryan, Jr. Fellowship (2011-17) highlight his scientific recognition. Publications emphasize electricity market deregulation , energy infrastructure resilience , and consumer response to smart grid technologies . His work has been cited in major media outlets like The New York Times and The Los Angeles Times , and he has consulted for National Renewable Energy Laboratory , U.S. Department of Energy , and other industry stakeholders.
Baris Ata is the Sigmund E. Edelstone Distinguished Service Professor of Operations Management at the University of Chicago Booth School of Business. His work bridges theoretical operations management with practical applications, focusing on dynamic decision-making under uncertainty. Research Interests Ata’s research spans stochastic networks, manufacturing/service operations, healthcare delivery, and social sector innovation. Recent projects address high-dimensional stochastic control, xenotransplantation candidate selection, criminal justice logistics, and last-mile delivery challenges in Africa. Scientific Awards Best Paper in Service Science Award, INFORMS (2009) William Pierskalla Best Paper Award, INFORMS (2015) Wickham Skinner Best Paper Award, POMS (2019) Manufacturing and Service Operations Management Young Scholar Prize, INFORMS (2015) Emory Williams MBA Teaching Award (2021) Recent Publications Ata’s recent work includes topics in dynamic pricing, stochastic control, and healthcare logistics. His papers examine congestion-based pricing strategies, equilibrium analysis in queues, and policy design for organ transplantation. Broad disciplines include operations management, stochastic modeling, and healthcare analytics.
Jordi Claramonte Arrufat is a Spanish philosopher and university professor at the National University of Distance Education (UNED) in the Department of Philosophy and Moral and Political Philosophy. His work centers on Modal Aesthetics , a theoretical system analyzing the relationships between necessity, contingency, possibility, and impossibility in art and sensitivity. He has authored six major essay works, including the foundational Estética Modal: Libro Primero (2016) and Libro Segundo (2021). PhD in Philosophy from UNED (2006) Visiting professor at MIT, Yale University, and Chicago Arts Institute His research bridges aesthetics with political and social self-organization processes, focusing on contextual art practices and the breakdown of artistic representation in favor of direct action. Collaborations include groups like Fiambrera Obrera and Sabotaje Contra el Capital Pasándole Pipa (SCCPP). In 2022, he delivered the talk Art to the Limit at Valencia's 1st Biennial of Thought, addressing creativity in times of social crisis. Publications include analyses of censorship, relational aesthetics, and applications of modal theory to cinema, architecture, and sculpture. Claramonte's work has inspired academic research across disciplines, including studies on: Modal applications in audiovisual media and cinema Architectural modal analysis Scultptural modal strata Tradition in modern aesthetics He has supervised 17 doctoral theses and contributed to critical dialogues on autonomy, precariousness, and the political dimensions of sensitivity.
Dae-Jin Lee is an Assistant Professor at IE University’s School of Science and Technology, specializing in statistical modeling and data science. Previously, he served as a Research Line Leader at the Basque Centre for Applied Mathematics (BCAM) and coordinated the Knowledge Transfer Unit in Data Science/AI. His academic background includes a Ph.D. in Mathematical Engineering (2010) from Universidad Carlos III de Madrid and postdoctoral research at CSIRO (Australia). His research focuses on statistical methods for complex data, including penalized splines, tensor product smooths, and applications in biomedicine, epidemiology, environmental science, and sports analytics. He has led multidisciplinary projects funded by public and industry grants, collaborating globally with experts across fields like engineering, medicine, and biology. Key research themes include predictive modeling for health outcomes (e.g., SARS-CoV-2 pneumonia severity), sports injury prevention, and AI in healthcare. His work integrates machine learning with traditional statistical techniques, addressing real-world challenges like pedestrian dynamics simulations and automated medical diagnostics. He is actively involved in scientific organizations, including the Spanish Biostatistics Society and the Statistical Modelling Society. His recent publications highlight innovations in growth curve modeling, AI ethics, and spatiotemporal data analysis, reflecting his commitment to advancing both theoretical and applied statistics.
Francisco Jose Garcia Garcia is a Professor at the Universidad Pablo de Olavide, affiliated with the Department of Physical, Chemical and Natural Systems. His research focuses on Zoology, Marine Biology, and Benthic Ecology, with a specialization in Mollusks (particularly Opisthobranchia) and Antarctic Biodiversity. He leads the ORGSIS Organisms and Systems research group and contributes to the Doctoral Programs in Biodiversity and Conservation Biology. PhD in Zoology (1987) from the University of Seville His research spans marine taxonomy, ecological impacts of human activity, and biogeographical patterns of mollusks and arthropods in coastal environments. Recent studies examine invasive species effects (e.g., Amathia verticillata) and wrack dynamics in Atlantic and Mediterranean ecosystems. His publications from 1984–2024 reflect long-term contributions to Antarctic benthos studies (BENTART projects) and nudibranch systematics. Articles highlight expertise in Invasive Species Ecology, Benthic Ecology, and Environmental Impact Assessment, with a focus on mollusk physiology, taxonomy, and habitat interactions. Notable collaborations include Antarctic research campaigns and cross-regional studies comparing Brazil and Spain. As part of the ORGSIS group, he investigates coastal ecosystem functioning, emphasizing sandy beach macrofauna and supralittoral arthropods. His work integrates field experiments (e.g., wrack removal, trampling effects) and laboratory assays on reproductive biology.
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.
Agustín Zaballos Diego is an Assistant Professor in the Department of Computer Engineering at University Ramon Llull (URL), Barcelona, Spain, since 1999. He serves as Research Coordinator in the Department of Engineering at La Salle Campus Barcelona and leads the R&D Networking and Security Area since 2002. His academic background includes a PhD in Data Networks and Internet Technologies (2012), an International MBA (2014), and an M.S. in Electronic Engineering (2000). University: University Ramon Llull (URL) Department: Department of Computer Engineering Research Group: GRITS Research Focus: Real-time QoS-aware routing protocols in Smart Grids, Ubiquitous Sensor Networks, and IoT communications. His work bridges telecommunications, computer science, and energy systems through projects like OPERA (FP6), INTEGRIS (FP7), and FINESCE (FP7). Publication Trends: Recent articles highlight advancements in HF communications for Antarctic research, hybrid genetic algorithms for traffic engineering, IPv6 testing, and Industry 4.0-related networking solutions. Keywords span Smart Grids, IoT, Sensor Networks, and QoS optimization. Collaborative Projects: Key initiatives include the Antarctica Project , ATHIKA (ICT in healthcare), ENVISERA (environmental sensor networks), HOTSUP (online teaching innovation), PLANET4 (AI/ML in industry), and XIoT (IoT scalability challenges).
Alan Briones Delgado is a researcher at the La Salle School of Engineering , Universitat Ramon Llull , with a focus on Internet of Things , Cybersecurity , and Transport Protocols . His work spans projects funded by the European Commission and national grants, including EXCEL4HOUSING4.0 , WeB-Nimbus , and NG-SOC , addressing challenges in cloud computing education, ecological monitoring, and security operations. His research integrates Artificial Intelligence and Wireless Sensor Networks for sustainable solutions. Key research areas include Quality of Service in heterogeneous networks, Environmental Conservation via IoT, and Teaching and Learning strategies for Big Data. Projects like EcoSentinel and BTL-COP highlight his commitment to Environmental Monitoring and Community Policing applications. His collaborations extend to institutions in the UK , Albania , and Western Balkans . Contact: alan.briones@salle.url.edu
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.
Marta Casanellas is a full professor in the Department of Mathematics at the Polytechnic University of Catalonia (UPC) and a researcher at the Centre de Recerca Matemàtica. She teaches at the Faculty of Mathematics and Statistics, ETSEIB, and FIB. She earned her PhD in mathematics from the University of Barcelona under RM Miró-Roig, focusing on algebraic geometry and liaison theory. After completing a postdoc at UC Berkeley with a Fulbright Scholarship, she shifted her research to applications of algebraic geometry in computational biology, particularly phylogenetics. Her educational background includes a PhD from the University of Barcelona (2002), followed by a postdoctoral fellowship at UC Berkeley (2002-2003) supported by a Fulbright Scholarship. She obtained a prestigious Ramón y Cajal contract at UPC in 2003, which marked her transition to interdisciplinary research at the intersection of mathematics and biology. Casanellas' research focuses on applying algebraic and geometric techniques to phylogenetics, with particular emphasis on evolutionary models, phylogenetic invariants, and computational methods for genomic data analysis. Her work bridges pure mathematics (particularly algebraic geometry) with biological applications, developing mathematical frameworks to reconstruct evolutionary histories and understand genomic relationships. She has published extensively in both mathematics journals like Advances in Mathematics and biology journals like Molecular Biology and Evolution. Her recent publications demonstrate a consistent focus on developing algebraic methods for phylogenetic analysis, with increasing attention to heterogeneous evolutionary processes across lineages, time-reversible models, and computational implementations of theoretical results. The trend shows progression from theoretical foundations in algebraic geometry toward increasingly sophisticated and applicable computational methods for biological data. Fulbright Scholarship for postdoctoral research at UC Berkeley Ramón y Cajal contract (2003) Casanellas has supervised PhD students including A. Kedzierska (co-supervised with R. Guigó of the CRG). She has served as principal investigator for three competitive Spanish government projects involving fifteen researchers each. She has held significant academic leadership roles including Deputy Director of Research of the Department of Mathematics at UPC (2015-2018), head of studies for the Degree in Data Science and Engineering at UPC (2018-2022), and currently coordinates UPC's PhD in Bioinformatics program and Bachelor's Degree in Bioinformatics. She leads the BIO-GEOMAP research group focused on applying mathematical techniques to biological problems.
Wouter Lueks is a faculty member at the CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. His research focuses on designing secure, practical, and privacy-friendly systems using applied cryptography, anonymous communication, and systems engineering. He leads a lab and actively mentors PhD and PostDoc researchers. Education: PhD in Computer Science (Radboud University, Netherlands), advised by Jaap-Henk Hoepman and Bart Jacobs. Postdoctoral Researcher at EPFL, Switzerland (SPRING Lab). Research Interests: Privacy-preserving systems for humanitarian aid and public health. Cryptography in decentralized networks and anonymous communication. Secure protocols for identity management and voting systems. Key Publications: Recent work includes privacy-preserving digital wallets for aid distribution (IEEE S&P 2025), biometric deduplication systems (IEEE S&P 2024), and decentralized proximity tracing protocols (Commun. ACM 2022). His research emphasizes practical applications of zero-knowledge proofs and attribute-based credentials. Awards: Distinguished Paper Award at IEEE S&P 2023. Runner-up Casper Bowden PET Award 2021 and CNIL-Inria Privacy Award 2021. Advising & Grants: Supervises PhD/PostDoc researchers and collaborates on projects funded by EU and industry grants. Active in open-source contributions, including the zksk library and Lightnion anonymous communication tool. Labs/Teams: Principal investigator at CISPA, collaborates with the SPRING Lab (EPFL) and leads interdisciplinary teams in privacy-enhancing technologies.
Florina Almenares Mendoza is an Associate Professor at the Telematics Engineering Department of Carlos III University of Madrid , where she also serves as the Director of the University Master's Degree in Cybersecurity. Her research focuses on addressing security challenges in emerging technologies such as IoT, post-quantum cryptography, and privacy-preserving systems. Email: florina.almenares@uc3m.es Contact: 916246234 Location: 4.0.F06 - Quevedo Towers (Leganés) Research Interests Florina's work spans cybersecurity , Internet of Things (IoT) , and post-quantum cryptography , with a focus on scalable authentication, quantum-resistant protocols, and privacy. She explores machine learning applications for security, federated identity management , and smart grid security frameworks. Recent Publications Her recent research includes papers on DNSSEC soft delegation, hybrid quantum security for TLS/IPsec, PUF-based authentication in IoT, and blockchain-enabled auditability. These studies emphasize IoT security , quantum-resistant algorithms , and privacy-enhancing technologies .
