Dr. Rajesh Bera is a Research Fellow at ICFO's Functional Optoelectronic Nanomaterials group specializing in quantum-confined nanostructures. His research examines ultrafast carrier dynamics, excitonic properties, and optoelectronic applications of nanomaterials including quantum dots, nanoplatelets, and hybrid nanostructures. Current investigations focus on intraband transitions in doped nanocrystals, orientation-dependent excitonic behavior in 2D materials, and charge transfer mechanisms in heterostructure devices. Work bridges fundamental photophysics with applications in photodetection, sensing, and energy conversion. Recent publications demonstrate expertise in time-resolved spectroscopy of quantum materials, nanomaterial synthesis via colloidal chemistry, and rational design of optoelectronic devices. Continually develops novel characterization methods to probe ultrafast processes at nanoscale interfaces.
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.
Bryon Aragam is an Associate Professor of Econometrics and Statistics and Robert H. Topel Faculty Scholar at the University of Chicago Booth School of Business. His research focuses on the intersection of causality, statistical machine learning, and probabilistic modeling, with particular emphasis on applications to artificial intelligence systems including large language models like ChatGPT and generative models like DALL-E. Dr. Aragam completed his PhD in Statistics and a Masters in Applied Mathematics at UCLA, where he was an NSF graduate research fellow. Prior to joining the University of Chicago, he was a project scientist and postdoctoral researcher in the Machine Learning Department at Carnegie Mellon University. Research Focus: Causal structure learning in probabilistic generative models Key Areas: Causal machine learning, deep generative models, latent variable models, statistical learning theory Applications: AI interpretability, ethics, and fairness in artificial intelligence systems Teaching: Business Statistics, Econometrics and Statistics Colloquium His recent publications demonstrate a strong theoretical foundation combined with practical applications, particularly in understanding and improving AI systems. His work spans causal discovery, graphical models, deep learning, and latent variable modeling, with particular attention to the theoretical properties of these methods and their applications to real-world AI challenges. The research shows a progression toward increasingly complex problems in causal representation learning and AI interpretability. Scientific Awards: Robert H. Topel Faculty Scholar NSF Graduate Research Fellow Dr. Aragam's work has been published in top statistics and machine learning venues including the Annals of Statistics, Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the Journal of Machine Learning Research (JMLR). His research group publishes broadly across both statistical and machine learning communities, demonstrating the interdisciplinary nature of his work at the intersection of statistics, machine learning, and causal inference. As a data science consultant for technology and marketing firms, Dr. Aragam has applied his expertise to problems in survey design, customer retention, logistics, and ranking, bridging the gap between theoretical research and practical applications.
Jacob D. Leshno is an Associate Professor of Economics and Robert H. Topel Faculty Scholar at the University of Chicago Booth School of Business. His research employs game theory, applied mathematics, and microeconomic theory to study allocation mechanisms and marketplace design, with applications spanning school choice systems, patient assignments to nursing homes, and decentralized cryptocurrency protocols. Professor Leshno's academic background includes: PhD in Economics from Harvard University, completed under Nobel laureate Alvin Roth M.Sc. in Pure Mathematics from Tel Aviv University B.Sc. in Pure Mathematics from Tel Aviv University His research program centers on market design theory with two primary strands. The first focuses on matching markets, where he developed tractable cutoff characterizations that clarify market structures for college admissions and medical residency matching (NRMP). His work demonstrates how price discovery mechanisms can streamline inefficient processes like college applications and subsidized housing allocation. The second strand examines cryptocurrencies and blockchain technology, investigating how open-source computer code functions as market rules in decentralized systems. This research explores both the economic security of permissionless consensus and fundamental limitations of proof-of-work protocols. Professor Leshno's publications reveal a cohesive research trajectory applying economic theory to increasingly complex market structures. His work consistently bridges theoretical rigor with practical implementation, evolving from traditional matching markets to the frontier of decentralized digital systems. Publications in top journals like American Economic Review and Journal of Political Economy demonstrate both analytical depth and real-world relevance across education, healthcare, and financial technology sectors. Professor Leshno has received significant recognition for his contributions: ACM SIGecom Test of Time Award for foundational work in matching markets INFORMS Frederick W. Lanchester Prize for outstanding contributions to operations research Prior to Chicago Booth, Professor Leshno served as Assistant Professor at Columbia Business School and completed a postdoctoral fellowship at Microsoft Research New England, following industry experience at Yahoo! and IBM. He teaches MBA courses in Competitive Strategy and Market Design, and developed a PhD seminar bridging computer science theory with economic principles for distributed systems. His research continues to influence both academic theory and practical implementations of market mechanisms across multiple sectors. Professor Leshno maintains active collaborations with leading researchers including Itai Ashlagi, Irene Lo, and Gur Huberman, advancing the theoretical foundations of market design while addressing contemporary challenges in digital marketplaces and allocation systems.
Angel Saz Carranza is a Professor and Associate Professor at the Department of Strategy and General Management in the Esade Business School, Ramon Llull University. His research focuses on global governance, intergovernmental organizations, regulatory networks, and public-private partnerships. He contributes to the UN Sustainable Development Goals through his work on institutional frameworks and policy design. He leads research projects funded by the EU and Spanish Ministry of Science, including 'EU-VALUES' (2023-2026) and 'LegitGov' (2022-2025). His work explores accountability mechanisms in EU regulatory networks and governance structures of intergovernmental organizations under the UN system. Key research outputs analyze board design in intergovernmental organizations, network tasks in regulatory frameworks, and determinants of public-private partnership policies. His projects often involve semantic big data analysis and configurational approaches. He is part of the Grup de Recerca en Lideratge i Innovación en la Gestión Pública (GLIGP), a research group focusing on public management innovation. Current and past projects address global governance legitimacy, strategic foresight for Spain's foreign policy, and regulatory network governance.
Institute for Bioengineering of Catalonia (IBEC)Spain
Prof. Raimon Jané Campos is a leading figure in biomedical signal processing at the Universitat Politècnica de Catalunya (UPC) and Universitat de Barcelona (UB). As co-director of UPC's Biomedical Signal and System Group (CREB) and coordinator of the Biomedical Engineering PhD Programme, he bridges engineering and clinical applications. His work focuses on respiratory and sleep disorder diagnostics, with significant contributions to COPD and sleep apnea monitoring through wearable devices and machine learning. PhD in Biomedical Engineering (UPC, 1989) Visiting researcher at Université de Nice-Sophia Antipolis Vice-president of Spanish Society of Biomedical Engineering Research spans respiratory mechanics , sleep-disordered breathing , acoustic biomarkers , bioimpedance , and machine learning in biomedical contexts . His 2025 work on microcalorimetric pathogen classification and 2024 spiking neural networks for apnea detection demonstrate cutting-edge integration of computational methods with physiological monitoring. Articles from 2017-2024 reveal consistent focus on non-invasive diagnostics , cardiorespiratory synchronization , and smartphone-based health solutions . Awarded the Barcelona City Technology Research Award (2005) and serving on the International Advisory Board for Physiological Measurement since 2010, his career combines academic leadership with real-world clinical translation through IBEC's technology transfer initiatives.
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.
John Kilner is a Senior Research Investigator at Imperial College London, formerly holding the BCH Steele Professorship of Energy Materials and serving as Head of the Department of Materials and Dean of the Royal School of Mines. His research focuses on ionic and mixed-conducting ceramics, particularly for applications in fuel cells, oxygen separators, and sensors. He pioneered isotopic exchange SIMS techniques to study oxygen exchange and diffusion in oxide ceramics, with recent work centered on intermediate-temperature fuel cells and interfacial phenomena in solid electrolytes. Prof. Kilner's academic background includes over 30 years of research in materials science, leading to over 250 publications and multiple patents in fuel cell and gas separation technologies. He co-founded CeresPower Ltd, a successful spinout company. His work bridges fundamental materials science with applied energy technologies, emphasizing solid-state ionics and ceramic electrolyte development. Publications span advancements in garnet solid electrolytes, lithium-ion conductivity enhancement strategies, and in-operando microscopy analysis of battery materials. His contributions to the Journal of Solid State Ionics as European Editor highlight his role in shaping the field's academic discourse. Notably, Kilner advises doctoral research such as William Manalastas Wang’s thesis on ceramic lithium-ion electrolytes. His research team actively explores next-generation battery materials with a focus on improving energy density and stability through advanced ceramic engineering and surface analysis techniques.
Antonia Agulló Agüero is a distinguished Professor at Pompeu Fabra University specializing in Financial and Tax Law. With a scholarly career spanning over four decades from 1980 to 2025, she has established herself as a leading authority in Spanish tax law with growing expertise in EU tax frameworks and public finance systems. Her academic contributions include 26 journal articles, 27 collaborative works, 15 books, and direction of 20 doctoral theses. Her research interests focus on Tax Law , Financial Law , and Public Finance , with particular expertise in EU Taxation, Local Government Finance, Constitutional Tax Law, and International Taxation. Her scholarly work demonstrates a clear evolution from foundational tax principles to complex contemporary issues including healthcare financing, cross-border taxation, and fiscal policy responses to economic crises. Analysis of her most recent publications (2016-2020) reveals increasing attention to healthcare financing mechanisms, EU tax harmonization challenges, and the constitutional dimensions of public spending. Her work bridges theoretical legal scholarship with practical policy applications, particularly in regional tax autonomy and fiscal federalism within Spain's autonomous communities framework. As a dedicated academic mentor, she has supervised 20 doctoral students whose research spans diverse tax law topics including international double taxation, public debt concepts, soft law in international taxation, and environmental taxation. Her students have gone on to contribute significantly to academic and professional tax discourse in Spain. Her scholarly infrastructure includes leadership in academic publications, participation in professional tax councils (notably the Barcelona Tax Council), and contributions to major tax law reforms including Spain's General Tax Law and Personal Income Tax legislation. Her work continues to influence tax policy development in Spain and EU member states.
Javier Fernandez Blanco is an Associate Professor and Chair of the Department of Economics and Economic History at the University Autonomous of Barcelona (UAB), affiliated with the Barcelona School of Economics (BSE). He holds a PhD in Economics from the University of Minnesota (2008) and degrees in Economics and Mathematics from the Universitat de Barcelona. His research focuses on labor markets, public insurance design, and macroeconomic policy, with a particular interest in unemployment dynamics, household insurance mechanisms, and aging populations. He has held visiting positions at the University of Toronto (2018-19 as Visiting Associate Professor), UNSW Sydney (2012), and Carlos III University of Madrid (2008-12). His work has been published in top journals like the International Economic Review, Journal of Economic Theory, and European Economic Review. He has secured research grants, including two BSE Seed grants as Principal Investigator, and contributed to national research initiatives. He currently co-directs research projects on labor markets and education, and has advised numerous PhD and master’s students. His awards include fellowships from the Generalitat, Ramon Areces Foundation, and University of Minnesota. He actively participates in academic service, including organizing conferences, serving on editorial boards, and holding leadership roles in academic governance at UAB and BSE.
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.
Paolo Mastropietro is a Research Professor at the Institute for Research in Technology (IIT) of Comillas Pontifical University in Madrid. He holds a Master's degree from the University of Rome Tor Vergata (2009) and a PhD from Comillas University (2016), focusing on capacity remuneration mechanisms. His career includes private sector work in Italy and Spain, a UNV Project Officer role in Ethiopia (2011), and joining IIT in 2012 under the SETS Erasmus Mundus PhD program. Affiliations: IIT, School of Engineering (ICAI), Comillas Pontifical University Research Interests: Power sector regulation, security of supply, capacity remuneration mechanisms, regional markets, tariff design, and energy sustainability His research emphasizes regulatory frameworks for energy transition and decarbonization, with contributions on hydrogen markets, electricity storage, and demand response integration. Recent work includes analysis of EU market reforms, pandemic-related energy poverty measures, and capacity mechanisms in Latin America. Key projects include the EU-funded ONESYSTEM (2023–2028) and DEFINER (2022–2025) initiatives, focusing on energy system integration and demand flexibility. He advises on regulatory modernization in Peru, Colombia, and Panama, and has authored over 40 journal articles, books, and technical reports. Awards: 2015 ICER Distinguished Scholar Award, Iberdrola Scholarship (2020) Grants: Projects funded by MICIU, World Bank, European Commission, and others He supervises doctoral research, including P. Brito Pereira’s work on future-proof capacity mechanisms. His expertise spans international energy policy, with engagements at ACER and MIT, and contributions to energy transition strategies globally.
Eduardo Alonso Pérez de Agreda is a faculty member at the Universitat Politècnica de Catalunya in the Departament d'Enginyeria del Terreny, Cartogràfica i Geofísica . He leads research in geotechnical engineering and rock mechanics, particularly focusing on landslides, tunneling in expansive rocks, and multiphase soil interactions. Research Highlights Analyzing soil saturation dynamics using digital imaging Modeling tunnel lining in anhydritic claystones Studying mineral precipitation impacts on infrastructure Recent Article Trends Over 15 articles (2021–2025) on landslides, tunneling, soil liquefaction, and multiphase interactions Keywords span geotechnical engineering, computational methods, rock mechanics, and material science Subfields include stress-dilatancy, material heterogeneity, swelling rocks, and landslide triggering mechanisms Awards Baker Medal (2017) Telford Gold Medal (2019) Advising Advised PhD students: G. Di Carluccio (2020), C. Alvarado (2017), M. Alvarado (2021) Co-advised: L. Tapias, Y. Salami, R. Fuentes Labs & Collaborations Active in the MSR - Mecànica del Sòls i de les Roques and GGMM - Grup de Geotècnia i Mecànica de Materials research groups Collaborated with institutions in Spain, Italy, and China
