Bio: Matthew O. Jackson is the William D. Eberle Professor of Economics at Stanford University and an external faculty member of the Santa Fe Institute. He was at Northwestern University and Caltech before joining Stanford, and received his BA from Princeton University in 1984 and PhD from Stanford in 1988. Jackson’s research interests include game theory, microeconomic theory, and the study of social and economic networks, on which he has published many articles and the books ‘The Human Network’ and ‘Social and Economic Networks’. He also teaches an online course on networks and co-teaches two others on game theory. Jackson is a Member of the National Academy of Sciences and a Fellow of the American Academy of Arts and Sciences, the American Association for the Advancement of Science, the Econometric Society, the Game Theory Society, and an Economic Theory Fellow. His other honors include a Guggenheim Fellowship, the Social Choice and Welfare Prize, the von Neumann Award from Rajk Laszlo College, an honorary doctorate from Aix-Marseille University, the Jean-Jacques Laffont Prize from the Toulouse School of Economics, the Slater Family Lecturer of the Year Prize from the Technion, the B.E.Press Arrow Prize for Senior Economists, the BBVA Frontiers of Knowledge Award in Economics, Finance, and Management, and teaching awards. He has served on the editorial boards of Econometrica, Games and Economic Behavior, PNAS, the Review of Economic Design, and as the President of the Game Theory Society.

Bio: Qiaozhu is a professor in the School of Information and the Department of EECS at the University of Michigan. His research focuses on large-scale data mining, machine learning, information retrieval, and natural language processing, with broad applications to networks, Web, and healthcare. Qiaozhu is an ACM distinguished member (2017) and a recipient of the NSF Career Award (2011). His work has received multiple best paper awards at WWW, ICML, KDD, WSDM, and other major conferences. He is the founding director of the master degree of applied data science at the University of Michigan. He has rich experience organizing workshops and related events, including being the General Co-Chair of SIGIR 2018.

Bio: Stephanie Wang is a Professor of Economics at the University of Pittsburgh. She is an experimental economist working on topics in behavioral game theory, political economy, and choice under uncertainty among others. Recent work explores the distribution of attitudes towards losses in the general population, projective thinking in strategic situations, and persuasive arguments in the field. Her research has appeared in various academic journals including American Economic Review, Econometrica, PNAS, and Review of Economic Studies. She is an Associate Editor at European Economic Review, Games and Economic Behavior, Journal of Political Economy Microeconomics, and Management Science. She received a PhD from Princeton University, a MSc from LSE, and SBs in Brain and Cognitive Sciences and Economics from MIT. She has been a Postdoctoral Scholar at Caltech and a Visiting Associate Professor at Stanford University. She is a co-founder of MobLab.

Bio: Yutong is a Ph.D. candidate and a Barbour Scholar at the University of Michigan School of Information, advised by Prof. Qiaozhu Mei. With a general research interest in AI behavioral sicence, AI for science, and AI for innovation, she has published research papers in major journals and conferences such as PNAS, WWW, ICLR, AAAI, etc. Yutong has co-organized workshops on topics including AI behavioral science and graph learning. She also regularly served as a reviewer in AI-related conferences including WWW, KDD, NeurIPS, ICML, AAAI, etc. Her research has been recognized with the University of Michigan Barbour Scholarship and D. E. Shaw Research Graduate and Postdoctoral Women’s Fellowship.

Bio: Walter Yuan is the CEO and co-founder of MobLab and Empathia AI. At MobLab, Walter spearheaded the development of a widely adopted platform for social science classroom experiments used by thousands of educational institutions globally. With a background in biology from the University of Wisconsin-Madison, he co-founded Empathia AI, combining AI expertise and clinical insights to create a medical copilot aimed at reducing physician burnout and improving patient care. Walter previously managed experimental laboratories at Caltech and UCLA, supporting a wide range of social science research. In his free time, he collaborates on research projects with colleagues from Stanford, Michigan, and other institutions.