Biography

Arthur Dolgopolov is an economist with research interests in game theory, computational and experimental methods, especially in a dynamic context.

He holds a Ph.D. from George Mason University, where he worked as a research assistant at the Interdisciplinary Center for Economic Science. Arthur's Ph.D. thesis demonstrates how to consistently and non-parametrically recover strategies of players from their actions. In his work, he uses dynamic programming, optimization, revealed preference, and economic experiments.

Arthur is currently working with professor Giacomo Calzolari, studying convergence of reinforcement learning algorithms in different environments with implications both for human learning and automated trading systems.

Expertise for Teaching and Mentoring of Ph.D. Researchers
Arthur served as a teaching assistant for graduate game theory and microeconomics classes at George Mason University. He also taught undergraduate courses on economic problems and public policies, the math camp, and he is currently teaching international economics.