Speakers
David Childers is an Assistant Professor of Economics at Carnegie Mellon University. In his research, he combines approaches from Econometrics, Machine Learning, and High-dimensional Statistics to devise performant and theoretically sound methods for computation, estimation, and decision-making in structured, high-dimensional, dynamic environments, with applications to macroeconomics and causal inference.
Xintong Wang is an incoming Assistant Professor in the Department of Computer Science at Rutgers University (starting in January 2024). Her research interests lie in the intersection of artificial intelligence and economics. Her recent work focuses on studying multi-agent, game-theoretic environments where agents interact, often with the aid of algorithms, and agents' desires may not easily and reliably match up. Examples include online platforms, financial markets, a rush-hour commute, and a game of poker. Through integrating computational tools (e.g., machine learning, simulation techniques) and economic principles (e.g., game theory), she explores two broad categories of problems: (i) understanding agent incentives and behavior to design rules or systems that can lead to socially optimal outcomes from agent interactions; (ii) addressing computational challenges that arise when operating or analyzing multi-agent systems.
Stefan Bucher is a postdoctoral associate at MIT Sloan School of Management. His research is at the intersection of behavioral economics and machine learning. Following his PhD from New York University's Department of Economics, he was a postdoctoral researcher with Peter Dayan at the Tübingen AI Center and the Max Planck Institute for Biological Cybernetics.
Mahdi Kahou is an assistant professor of economics at Bowdoin College. His research is at the intersection of macroeconomics, machine learning and econometrics.
Michael Curry is currently a postdoc, splitting time between Sven Seuken's Computation and Economics Research Group at the University of Zürich, and David Parkes' group at Harvard SEAS. He received his Ph.D. from the University of Maryland, College Park in the Computer Science department, advised by John Dickerson and Tom Goldstein and affiliated with the Center for Machine Learning. Previously he attended Columbia University, where he received an MS in computer science, and Amherst College, where he received a BA in computer science. His research interest includes differentiable economics, machine learning for matching and allocation, adversarial machine learning, and Reinforcement learning.
Marlon Azinovic is a postdoctoral visiting scholar at the Economics Department at the University of Pennsylvania. His research interests are macroeconomics, financial economics, heterogeneous agent models, inequality, deep learning for solving macro models, and computational methods more generally. He will join the Economics Department at the University of North Carolina at Chapel Hill as Assistant Professor this fall. Previously he was a postdoc at the Economics Department at the University of Zurich in the group of Nir Jaimovich and PhD student at the Finance Department at the University of Zurich and the Swiss Finance Institute. His PhD advisor was Felix Kübler and his co-advisor was Simon Scheidegger.
Johnathon Payne is an Assistant Professor in the Bendheim Center for Finance in the Department of Economics at Princeton University. He completed my Ph.D. at New York University. His research studies questions in finance, banking, macroeconomics, economic history, computational economics and econometrics.