Sarah Dean is an Assistant Professor in the Computer Science Department at Cornell University, affiliated with the College of Engineering. Her research focuses on the interplay of machine learning, optimization, and dynamics in real-world systems, particularly in control theory, recommendation systems, and ethical AI. Education: PhD in EECS, University of California, Berkeley (2021) Postdoctoral Research, University of Washington (2021-2022) Research Interests: Data-driven control systems, reinforcement learning, recommendation systems, user dynamics, algorithmic fairness, and the societal impacts of AI. She emphasizes foundational understanding of how learning systems interact with human and social processes. Recent Work Trends: Her articles explore topics like bilinear system identification, user participation dynamics in recommendation platforms, and ethical considerations in AI development. Recent work includes harm mitigation strategies and mathematical modeling of AI-human feedback loops. Awards: AI2050 Early Career Fellow (2024) Best Paper at ICML 2018 (Delayed Impact of Fair Machine Learning) Best Student Paper in Imaging Systems (OSA Congress 2018) Advising & Labs: Advises over 15 graduate and undergraduate students. Leads research on interactive ML systems, with contributions to projects like the 'MSGD' repository for streaming data learning. Active in the GEESE group, promoting socially responsible computing.
Alp Atakan Overview Alp Atakan is a Professor and Head of School in the School of Economics and Finance at Queen Mary University of London. He holds a PhD from Columbia University and previously served as an Assistant Professor at Northwestern University and Associate Professor at Koç University. His research focuses on Microeconomic Theory, Game Theory, Auction Design, and Information Economics. Key contributions include studies on reputation dynamics, search markets, and information aggregation in auctions. Education PhD in Economics (with distinction), Columbia University, 2003 MA in Economics, Columbia University, 2000 MBA, Columbia University, 1997 BS in Economics, University of Pennsylvania, 1993 Research & Grants Recipient of an ERC Consolidator Grant (2016–2021) for 'Market Selection, Frictions, and the Information Content of Prices'. Notable research includes work on bargaining dynamics, price discovery mechanisms, and the role of information asymmetry in auctions. He has published in top journals like Econometrica , Journal of Economic Theory , and American Economic Review . Teaching spans MBA/EMBA courses on managerial economics and microeconomic theory, alongside advanced graduate courses in game theory and dynamic programming. Grants & Projects ERC Consolidator Grant: Market Selection & Price Information (€1,089,000) Tubitak Grants: Sequential Debate (2014–2015) and Auctions & Information (2012–2014) His work bridges theoretical economics with practical market design, emphasizing strategic interactions in decentralized systems.
Ming Hu is a Professor and University of Toronto Distinguished Professor of Business Operations and Analytics at Rotman School of Management, University of Toronto. He serves as Area Coordinator for the Operations Management & Statistics Area and holds editorial leadership roles including Editor-in-Chief of Naval Research Logistics and Associate Editor for multiple top journals. MS in Applied Mathematics, Brown University (2003) PhD in Operations Research, Columbia University (2009) His research focuses on sharing economy , social operations , and platform economics , examining how operational decisions can maximize societal benefit. Key areas include crowdfunding , two-sided markets , crowdsourcing , and group buying , with applications to DEI , sustainability , and AI-empowered operations . Recent work analyzes spatial operations in delivery systems, algorithmic fairness , and climate change adaptation in agricultural supply chains. His publications span top journals like Management Science and Operations Research , covering topics from blockchain traceability to quantum-inspired optimization . Scientific recognitions include: Wickham Skinner Early-Career Research Award (2016) Best Operations Management Paper in Management Science (2017) 2018 Poets & Quants Best 40 Under 40 MBA Professors As an Amazon Scholar (2022–) and Chair of Chain Analytics Institute (2023–), he bridges academic research with industry applications in AI-driven logistics and sustainable operations.
Rosa Ferrer is a Serra-Hunter Associate Professor at Universitat Pompeu Fabra and an Associate Research Professor at the Barcelona School of Economics. She also serves as a Research Affiliate at CEPR in London and as Co-Director of the Master in Competition, Regulation & Markets program. Her academic journey began with a PhD from Vanderbilt University, establishing a strong foundation for her research career in economics. Dr. Ferrer's research spans several key areas within economics, with a particular focus on Law and Economics, Industrial Organization, and the Digital Economy. She combines empirical and theoretical methods to explore consumer choice, demand estimation, gender economics, and law enforcement challenges. Her work is inspired by Gary Becker's view on economic incentives beyond monetary rewards, applying industrial organization and applied microeconomics to diverse applications. She has made significant contributions to understanding gender gaps in professional performance, particularly in the legal profession, as well as consumer behavior in product-harm crises and digital markets. Her publication record demonstrates consistent scholarly output across high-impact journals including Management Science, Journal of Political Economy, and Review of Economic Studies. Her recent work focuses on digital economy challenges, gender differences in media consumption, and career trajectories in professional settings. This research portfolio shows a clear progression from foundational work in law enforcement and decision theory to contemporary issues in digital markets and gender economics. As Co-Director of the Master in Competition, Regulation & Markets, Dr. Ferrer plays a significant role in shaping the next generation of economists and policy experts. Her leadership in this program reflects her commitment to bridging academic research with practical policy applications in competition and regulatory frameworks.
Eduardo Azevedo is the John M. Bendheim and Thomas L. Bendheim Professor of Business Economics and Public Policy at the Wharton School , University of Pennsylvania. He holds a courtesy appointment as Professor of Economics and was awarded the 2016 Sloan Foundation Fellowship. His research integrates economic theory with practical applications across science and business domains. His research interests include: Market design Selection markets Social science genetics Experimental economics Game theory Recent publication trends focus on: Economic theory applications to healthcare and digital markets Empirical Bayes methods in A/B testing Adverse selection in insurance markets Strategic behavior in two-sided matching Evolutionary behavioral economics He serves as an instructor for BEPP2500 - Managerial Economics , emphasizing real-world application of microeconomic theory to business problems. His work also involves software development for economic research, including MATLAB-based empirical Bayes tools for analyzing treatment effects in large-scale experiments. Scientific awards : Sloan Foundation Fellow (2016)
Dr. Kenneth Joseph is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo , part of the School of Engineering and Applied Sciences . He serves as Associate Director of the Institute for Artificial Intelligence and Data Science and leads the Computation and Equity Lab (cubelab) , focusing on social inequality through computational measures and models. Education: PhD, MS, and BS in Societal Computing from Carnegie Mellon University (2016, 2012, 2010) Research Interests: Computational Social Science, Network Science, Gender Studies, and AI for Social Good Notable Work: Gender disparities in academia, predictive modeling for foster care and urban policy, and social media rumor analysis Awards: UB Exceptional Scholar—Young Investigator Award (2021) Advising: Mentored students like Yuhao Du, Jason Yan, Arjunil Pathak, and Navid Madani on projects spanning Twitter bios, foster youth services, and algorithmic fairness.
Professor Masooda Bano serves as William Golding Senior Research Fellow at Brasenose College and Professor of Development Studies at the University of Oxford's Department of International Development. She leads the five-year ERC-funded Changing Structures of Islamic Authority (CSIA) project examining Islamic scholarly debates and their societal impacts. Her academic credentials include an MPhil in Development Studies from Cambridge and a DPhil from Oxford. These qualifications underpin her expertise in development theory and field research methodologies. Bano's research centers on the interplay between ideas, beliefs, and material incentives in development processes . She investigates how psycho-social factors shape individual choices and collective outcomes, with particular focus on Islamic authority structures, female education movements, and aid effectiveness. Her work combines large-scale comparative studies using ethnographic and survey data across Muslim-majority contexts. Recent publications reveal a concentrated focus on education policy in developing nations , especially Pakistan, Nigeria, and Indonesia. Key themes include decentralized education planning, low-fee private tuition markets, community participation models, and Islamic education systems. The research consistently examines religion-development intersections and institutional responses to social change. Her scientific recognition includes: Two competitive ESRC Fellowships A 1.4 million euro ERC Starting Grant for the CSIA project ESRC Best Social Science Impact award for Nigeria education interventions Bano supervises MPhil/DPhil theses at Oxford and has advised major development agencies, notably designing DfID's education reforms in northern Nigeria. Her CSIA project coordinates a multinational team conducting textual analysis, surveys, and ethnographic fieldwork to map evolving Islamic authority structures.
Dr. Hongtu Zhu is the Kenan Distinguished Professor of Biostatistics, Statistics, Radiology, Computer Science, and Genetics at the University of North Carolina at Chapel Hill (UNC). He holds affiliations with the Gillings School of Global Public Health and leads the Biostatistics and Imaging Genomics Analysis Lab. His expertise spans statistical learning, medical imaging, AI, and big data integration, with a focus on precision medicine and biomedicine. Dr. Zhu earned his PhD in Statistics from The Chinese University of Hong Kong (2000) and has held prior roles including DiDi Fellow/Chief Scientist (2018-2020) and Bao-Shan Jing Endowed Professor at MD Anderson Cancer Center (2016-2018). He has published over 345 peer-reviewed articles in top-tier journals like Nature, Science, and JASA, and actively contributes to editorial roles including Coordinating Editor of JASA. His research interests include neuroimaging analysis, knowledge graphs, and AI applications in healthcare. Notable awards include the COPSS Snedecor Award (2025), IEEE Fellowship (2025), and IMS Medallion (2027). He has mentored over 80 PhD students/postdoctoral fellows and serves on NIH grant review panels and professional organizations like the ASA's Section on Statistics in Imaging. Key Contributions: Imaging genomics, brain connectivity studies, ridesharing market optimization, medical AI frameworks Lab Innovations: Brain Imaging Genetics Knowledge Portal, Biomedical Knowledge Graph Interface Teaching: Advanced biostatistics courses (Generalized Linear Models, Deep Learning in Biomedicine) Recent work explores causal inference in healthcare, X chromosome's role in neurobiology, and AI ethics in medical vision-language models. His interdisciplinary projects bridge statistics, computer science, and clinical practice to address complex biomedical challenges.
Warut Suksompong is an Assistant Professor in the School of Computing at the National University of Singapore (NUS), where he holds the NUS Presidential Young Professorship. Previously, he was a postdoctoral researcher at the University of Oxford, hosted by Edith Elkind, and completed his PhD at Stanford University under Tim Roughgarden. He holds bachelor's and master's degrees from MIT. His research focuses on algorithmic game theory, computational social choice, mechanism design, and interdisciplinary problems at the intersection of computer science, economics, mathematics, and operations research. He is particularly known for contributions to fair division, including envy-freeness, proportionality, and maximin fairness in both divisible and indivisible resource allocation contexts. Key awards include the IJCAI 2021 Distinguished Paper Award for work on dividing land with geometric constraints and the WINE 2021 Best Student Paper Award for research on funding public projects via the Nash product rule. His work bridges theoretical foundations with practical applications, addressing challenges such as connectivity constraints, budget allocation, and social choice mechanisms. He has authored over 100 publications in top conferences and journals, including SIAM Journal on Discrete Mathematics, Artificial Intelligence, and Games and Economic Behavior. His research has been supported by grants from NUS and international collaborations.
Hanna Halaburda is an Associate Professor of Technology, Operations, and Statistics at the Leonard N. Stern School of Business, New York University, where she joined in 2019. Her research lies at the intersection of economics, technology, and digital platforms, with a strong focus on blockchain, cryptocurrencies, and platform competition. She has published extensively in top academic journals and co-authored the seminal book Beyond Bitcoin: The Economics of Digital Currencies . PhD in Economics, Northwestern University MA in Economics, Warsaw School of Economics MA in Philosophy, Warsaw University Her research interests center on the economic implications of digital transformation. She investigates how blockchain technology reshapes trust, governance, and competition in digital markets. Her work explores token design, consensus mechanisms, smart contracts, and the strategic use of decentralization in platforms. She also studies platform competition under network effects, consumer choice, and omnichannel marketing. A recurring theme is how digital technologies alter traditional economic forces and business models. The most recent articles show a strong trend toward analyzing the governance, security, and economic design of blockchain systems. Her work combines rigorous theoretical modeling with empirical insights, often applying game theory and industrial organization frameworks. Topics include permissioned vs. permissionless blockchains, the role of cryptographic tokens in coordination, and the macroeconomic implications of digital currencies. She also contributes to debates on Web3, AI, and the future of digital platforms. Scientific awards and recognitions include: ISR Best Paper Published in 2022 Runner-Up Lead article in RAND Journal of Economics Best Paper Award at Tokenomics 2023 Best Paper Award at WISE 2023 Best Paper Finalist at WISE 2022 and WISE 2021 Hanna Halaburda has advised and collaborated with numerous researchers and institutions. Her co-authors include leading scholars from Harvard, NYU, and international universities. She has received research recognition through best paper awards and invitations to contribute to high-impact journals and policy discussions. Her work has been supported by academic and policy institutions, including the Bank of Canada, where she previously served as a senior economist. She frequently publishes in both academic and practitioner outlets, including Harvard Business Review and Nature Human Behavior , indicating strong translational impact. She is actively involved in research teams focused on digital assets, blockchain governance, and platform economics. While no formal lab is mentioned, her extensive list of working papers and collaborations suggests leadership in a dynamic research group at NYU Stern. Her recent work on DAOs, public crypto mining firms, and CBDCs indicates ongoing, forward-looking research programs with real-world policy and business implications.
Peihan Miao is an Assistant Professor in the Department of Computer Science at Brown University, where she is a member of the Theory Group. Her academic journey began with a BS from the ACM Honors Class at Shanghai Jiao Tong University, followed by a PhD from UC Berkeley in 2019 under the supervision of Sanjam Garg. BS: ACM Honors Class at Shanghai Jiao Tong University PhD: University of California, Berkeley (2019) Dr. Miao's research focuses on cryptography and security, with particular emphasis on bridging the gap between theoretical cryptography and practical applications, especially in the realm of secure multi-party computation. Her work spans both foundational theoretical aspects and applied systems, demonstrating a strong commitment to developing cryptographic techniques that can be implemented in real-world scenarios. She has made significant contributions to private set intersection protocols, secure computation frameworks, and cryptographic primitives that enable privacy-preserving data analysis across various domains including genomics and machine learning. Her publication record reveals a consistent focus on advancing secure computation techniques, with recent work exploring structure-aware private set intersection, updatable cryptographic protocols, and applications of cryptography to emerging domains like federated genomics. Her research demonstrates a progression from theoretical foundations toward practical implementations that address real-world privacy challenges. NSF CAREER Award Meta Research Award Google Research Scholar Award Amazon Research Award Dr. Miao actively mentors PhD students including Xinyi Shi, Phuoc Van Long Pham, and Jifeng Wang, as well as postdoc Gayathri Garimella. She serves on program committees for major cryptography conferences including Crypto, TCC, and Asiacrypt. Her teaching portfolio includes courses on applied cryptography, introduction to cryptography and computer security, and special topics in secure computation, demonstrating her commitment to educating the next generation of cryptographers. She also runs a crypto reading group at Brown University for students interested in cryptography research. As part of Brown's Theory Group, Dr. Miao collaborates with colleagues on advancing the theoretical foundations of computer science while maintaining a strong focus on practical applications of cryptographic techniques.
Daniel Chen is an Assistant Professor of Business Analytics at the Carroll School of Management, Boston College. His research focuses on strategy in online platforms, leveraging machine learning and structural estimation to analyze two-sided markets and gig economy dynamics. He holds a Ph.D. in Operations Management from the Wharton School (University of Pennsylvania), advised by Gad Allon, and degrees from the University of Southern California, including an M.S. in Mathematical Finance and a B.S. in Economics/Mathematics. His work addresses strategic interactions between platforms and users, with a particular emphasis on data-driven solutions. Research Interests: Chen’s research spans gig economy operations, causal inference with machine learning, algorithmic transparency, and network-based rating systems. He collaborates with industry partners like driver analytics companies to study worker behavior, platform efficiency, and policy impacts. His methodologies combine theoretical modeling with empirical analysis, addressing real-world challenges in platform design and regulatory frameworks. Awards: Finalist, 2023 INFORMS Behavioral Operations Management Best Working Paper Award Labs/Teams: Collaborates with a driver analytics company to analyze gig economy datasets, contributing to both academic research and practical policy recommendations. His work bridges theoretical insights with actionable strategies for platforms and regulators.
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.
Mustafa Akan is an Associate Professor of Operations Management at the Tepper School of Business, Carnegie Mellon University . He holds a Ph.D. in Managerial Economics and Strategy from Northwestern University (2008) and a B.Sc. in Industrial Engineering from Carnegie Mellon University (2004). Research Interests : His work focuses on healthcare operations management , queueing theory , and dynamic pricing strategies . He investigates efficient resource allocation in service systems, equity in organ transplantation, and optimization of remanufacturing processes under uncertainty. His research bridges applied mathematics , computation theory , and business strategy . Article Trends : Recent publications address liver allocation equity (2025), two-sided market pricing (2025), and task allocation in tandem queueing systems (2024). Earlier works explore transplant health disparities (2024), remanufacturing procurement (2023), and fashion product pricing (2021). Common themes include service science , healthcare operations , and policy-driven optimization . Scientific Awards : Best Dissertation Award (INFORMS Aviation Applications Section, 2008) Xerox Faculty Chair (2009) INFORMS Best Paper in Service Science (2009) POMS Healthcare Best Paper Award (2012) Lave-Weil Prize (2013) Gerald L. Thompson Teaching Award (2014) NSF CAREER Award (2014) Mehrotra Research Excellence Award (2024) DEIJ Best Paper Award (2023) Teaching & Grants : He teaches courses like Healthcare Operations , Risk Analytics , and Demand Management & Price Optimization . His NSF CAREER Award (2014) supports research in operational systems. He has served on committees for INFORMS , POMS , and Naval Research Logistics .
Aviv Nevo is the George A. Weiss and Lydia Bravo Weiss University Professor at the University of Pennsylvania, holding joint appointments in the Department of Economics (School of Arts and Sciences) and the Marketing Department at the Wharton School. His research focuses on empirical industrial organization, antitrust economics, marketing, and econometrics, with applications to consumer packaged goods, healthcare, telecom, and real estate. Nevo earned his Ph.D. (1997) and AM (1994) in economics from Harvard University and a BSc in mathematics and economics from Tel Aviv University (1991). He joined Penn through the Penn Integrates Knowledge (PIK) program, which recognizes scholars who bridge disciplines. His work has examined price competition, merger implications, and regulatory policy, with notable contributions to understanding market dynamics in digital platforms and telecommunications. Nevo serves as a fellow of the Econometric Society, a research associate at NBER, and co-editor of Econometrica and the RAND Journal of Economics . Nevo’s research interests span antitrust analysis, consumer behavior, and applied econometrics. His recent studies address issues such as steering incentives in telecom gatekeepers, substitution effects in streaming media, and the misuse of economic metrics in merger reviews. He has advised on high-profile cases, including the Sabre/Farelogix and Aetna-Humana mergers, integrating empirical rigor into policy debates. Awards: Fellow of the Econometric Society, NBER Research Associate, Institute for Fiscal Studies International Fellow. Editorial Roles: Co-editor of Econometrica and RAND Journal of Economics . Professional Activities: PIK University Professor, Penn Integrates Knowledge initiative participant. Nevo’s work bridges academia and policy, with a focus on real-world applications of economic theory. His teaching spans both economics and marketing disciplines, reflecting his dual departmental affiliation.
