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Jordi Galí is a Professor at the Department of Economics and Business at Universitat Pompeu Fabra (UPF), a Senior Researcher at the Center for Research in International Economics (CREI), and a Research Professor at the Barcelona School of Economics (BSE). He holds a PhD from MIT and has played a central role in shaping modern macroeconomic theory, particularly the New Keynesian framework used by central banks worldwide. Education: PhD in Economics, Massachusetts Institute of Technology (MIT), 1989 Master in International Management, ESADE, 1985 Bachelor in Economics, Universitat Pompeu Fabra, 1994 His research focuses on macroeconomic theory, monetary economics, and macroeconometrics. He is best known for his work on the New Keynesian Phillips Curve, optimal monetary policy rules, and the role of technology and expectations in business cycles. His influential book, Monetary Policy, Inflation and the Business Cycle , is a standard reference in graduate programs globally. The most recent articles highlight a continued focus on critical issues in modern macroeconomics: the implications of a low natural rate of interest (r*), the effectiveness of monetary policy at the zero lower bound, the role of wage and price flexibility, and the interaction between fiscal and monetary policy. His work increasingly integrates heterogeneity, financial frictions, and experimental methods, reflecting the evolving frontiers of the field. Scientific Awards: BBVA Foundation Frontiers of Knowledge Award (2025) Yrjo Jahnsson Award (2005) Premi Rei Jaume I d'Economia (2004) Premio Nacional de Investigación “Pascual Madoz” (2022) Three ERC Advanced Grants Foreign Honorary Member, American Economic Association (2020) Galí has advised numerous central banks, including the ECB, Federal Reserve, and Banque de France. He has held leadership roles as President of the European Economic Association (2012), co-editor of the Journal of the European Economic Association , and co-director of the CEPR International Macroeconomics Programme. He is a Research Fellow at CEPR, a Research Associate at NBER, and a Fellow of the Econometric Society. He has also been actively involved in public policy debates in Spain and Europe, particularly on issues of productivity, labor market reform, and fiscal policy. His research program continues to explore the design of stabilization policies in open and currency union economies.

• Macroeconomic Theory
• Monetary Economics
• Macroeconometrics
• +7 more

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.

• Machine Learning
• Online Learning
• Multi-armed Bandit Problems
• +7 more

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.

• Macro-Labor Theory
• Labor Markets
• Urban Economics
• +3 more

Carlos Alvarez Martinez is a faculty member at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture at the Barcelona School of Informatics (FIB). He is a key member of the Programming Models (PM) research group and collaborates closely with the Barcelona Supercomputing Center (BSC). His research focuses on high-performance computing, FPGA acceleration, task-based programming models like OmpSs, and hardware-software co-design for heterogeneous systems. His research interests center on advancing parallel computing through innovative programming models and hardware acceleration. He investigates efficient task scheduling, resource management in multicore and FPGA-based systems, and runtime support for dataflow models. His work enables high-performance execution of complex applications in domains such as scientific computing and cyber-physical systems. He actively contributes to European initiatives like TEXTAROSSA and AXIOM, aiming to develop next-generation exascale supercomputing technologies. The trend in his recent publications shows a strong focus on leveraging FPGAs for HPC, optimizing SpMV operations, improving task scheduling with hardware support, and developing frameworks for multi-FPGA clusters. His work consistently bridges theoretical models with practical implementations, emphasizing performance, scalability, and energy efficiency in heterogeneous computing environments. Scientific Awards: Premi UPC al Compromís Social 2019 Premi Disseny per al Reciclatge 2013 Alvarez Martinez has advised or collaborated with several doctoral students, including Jaume Bosch, Xubin Tan, and Fahimeh Yazdanpanah. He has been involved in numerous competitive R&D projects, often related to high-performance computing and parallel programming models. His work includes significant contributions to educational innovation, particularly in active learning methodologies and formative assessment using interactive systems. He leads and participates in research labs and teams focused on programming models and computer architecture, notably the PM group at UPC/BSC. These teams develop runtime systems, compilers, and hardware accelerators to push the boundaries of parallel computing efficiency and programmability.

• High-Performance Computing
• Reconfigurable Computing
• FPGA Acceleration
• +7 more

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.

• Causality
• Statistical Machine Learning
• Probabilistic Modeling
• +6 more

Richard Hornbeck is the V. Duane Rath Professor of Economics at the University of Chicago Booth School of Business. He is an economic historian and applied-micro economist whose research focuses on the historical development of the American economy, examining why some places and people have become wealthier while others have remained poorer. Hornbeck is a research associate at the National Bureau of Economic Research, affiliated with programs on the Development of the American Economy, Development Economics, and Environmental and Energy Economics. Hornbeck's research spans multiple critical areas of economic history, with particular emphasis on slavery and emancipation economics, environmental history (especially the Dust Bowl migration), gender dynamics in 19th-century manufacturing, railroad development, and agricultural economics related to the Ogallala Aquifer. His work frequently utilizes newly digitized historical data to provide fresh insights into longstanding economic questions, connecting historical events to contemporary economic issues of wealth distribution and regional disparities. His publication record shows strong trends in American economic development research, with recent work focusing on the economic impacts of emancipation, historical manufacturing patterns by gender, and urban economic development. Many of his papers have been published as lead articles in top journals including the Journal of Political Economy, American Economic Review, and Review of Economics and Statistics. Hornbeck has received several prestigious honors including the Alfred P. Sloan Fellowship in 2014 and selection for the 2009 Review of Economic Studies Tour. His NBER affiliations demonstrate his standing in multiple subfields of economics research. Prior to joining Chicago Booth in 2015, Hornbeck was the Dunwalke Associate Professor of American History in the Economics Department at Harvard University. He received his PhD in economics from MIT in 2009 and a bachelor's degree in economics from the University of Chicago in 2004. His teaching includes courses on applied microeconomics in economic history and business in historical perspective, with course schedules extending through 2026.

• Economic History
• Applied Microeconomics
• American Economic Development
• +7 more

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.

• Market Design
• Game Theory
• Microeconomic Theory
• +3 more

Amir Sufi is the Bruce Lindsay Distinguished Service Professor of Economics and Public Policy at the University of Chicago Booth School of Business, where he has been a faculty member since 2005. He serves as a Research Associate at the National Bureau of Economic Research and co-director of its Corporate Finance Program. Bachelor’s Degree, Walsh School of Foreign Service, Georgetown University (1999) PhD in Economics, Massachusetts Institute of Technology (2005) His research focuses on finance , macroeconomics , and corporate finance . Key areas include household debt dynamics , credit market structure , income inequality , and interest rate impacts on productivity growth . Recent work examines customer capital investment and low-interest rate effects on market concentration . Selected scientific awards include the 2017 Fischer Black Prize, Econometric Society Fellow (2022), and American Academy of Arts and Sciences Fellow (2024). His peer-reviewed publications and working papers span topics from syndicated loans to global household debt cycles , with notable contributions to understanding credit-driven business cycles and government-led consumer credit programs . He teaches courses in leveraged finance , private credit , and corporate restructuring .

• Finance
• Macroeconomics
• Corporate Finance
• +9 more

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.

• Electricity and Natural Gas Industries
• Energy Infrastructure Resilience
• Network Science
• +4 more

Danfeng Zhang is a faculty member at Duke University whose research sits at the intersection of programming languages and security. Active across the premier PL conferences since 2015, Zhang has served on more than two-dozen program committees and currently co-chairs the POPL Student Research Competition. Education & Affiliation: Home page: users.cs.duke.edu/~dz132 Affiliation: Duke University, United States Research Interests: Zhang’s work spans programming-language design, static and dynamic analysis, formal verification, and security. A recurring theme is developing language-based techniques that guarantee strong security and privacy properties—ranging from side-channel resistance and constant-time execution to differential-privacy proofs—while preserving performance and usability. His recent projects combine type systems, program logics, and automated reasoning to build practical verification tools for concurrent, speculative, and approximate software. Publication Trends: Across nine representative papers (2015-2024) Zhang has advanced static detection of cache side channels, automated proofs of differential privacy, and relaxed concurrency models. The trajectory shows deepening integration of security concerns into language infrastructure, with tool-building (CtChecker, SpecSafe, LightDP) that bridge formal guarantees and real-world systems. Service & Leadership: 2024 POPL Student Research Competition Co-Chair 2025 POPL Program Committee member Repeated reviewer/PC member: PLDI, SPLASH/OOPSLA, ISSTA, ECOOP, APLAS, PriSC, PASS Zhang regularly mentors student researchers through SRC sessions and workshop panels, fostering diversity and early-career participation in the programming-languages community.

• Programming Languages
• Security
• Differential Privacy
• +5 more

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.

• Operations Management
• Applied AI
• Dynamic Decision Making Under Uncertainty
• +4 more

Raquel Moreno Sánchez is a Professor in the Department of Health at UCJC since 2011, specializing in emergency nursing and disaster response. She holds a Bachelor's in Nursing (1997), a PhD from the University of Alcalá de Henares, and advanced degrees including a Master's in Child Psychology and a Master's in Emergencies, Disasters, and International Cooperation (UCJC, 2013). Previously, she served as an Honorary Professor at the Autonomous University of Madrid (UAM) from 1998–2011. Her research focuses on emergency care protocols, pharmacology of antipsychotic drugs, and disaster management strategies. Notable contributions include bibliometric analyses of global antipsychotic drug studies and co-authorship of clinical guidelines for the SUMMA-112 emergency service. She coordinates training programs for healthcare professionals in out-of-hospital emergencies and advanced life support. Her work spans helicopter medical transport, palliative care, and interdisciplinary crisis management. Teaching roles include leading courses in emergency nursing, pediatric psychology, and mountain emergencies at UCJC. Professional experience includes 27 years in emergency and outpatient nursing, with prior roles in hospital critical care units and primary care. She is an Advanced Life Support instructor certified by SEMICYUC and actively participates in academic committees for healthcare education and policy.

• Emergency Nursing
• Disaster Management
• Critical Care
• +3 more

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.

• Tax Law
• Financial Law
• Public Finance
• +5 more

Danel Ahman is an Associate Professor at the Institute of Computer Science , University of Tartu , Estonia, specializing in programming language theory . His research focuses on dependent/refinement types , computational effects , and verified software . Education PhD in Theoretical Computer Science (University of Edinburgh, 2017) MPhil in Advanced Computer Science (University of Cambridge, 2012) BSc in Informatics (Tallinn University of Technology, 2010) Research Interests : Danel investigates programming languages with algebraic effects and effect handlers for verified software, exploring denotational/operational semantics and fibrational approaches to effects. His work bridges theoretical computer science with practical formal verification. Scientific Awards : Estonian Research Council grant (2025) Marie Skłodowska-Curie Fellowship (2019) PhD dissertation prize (2018) Google/Citrix dissertation awards (2012) Teaching & Supervision : He teaches courses like Logic in Computer Science and Functional Programming at the University of Tartu, and supervised BSc/MSc theses on topics including asynchronous effects and formal verification. Danel also organizes research seminars and guest lectures on F*.

• Programming Language Theory
• Dependent and Refinement Types
• Computational Effects
• +6 more

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.

• Modal Aesthetics
• Art Theory
• Political Philosophy
• +5 more