Arthur Dolgopolov is an economist with research interests in game theory, computational and experimental methods, especially in a dynamic context.
He will obtain his Ph.D. in Summer 2020 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 often uses dynamic programming, optimization, revealed preference, and economic experiments.
Arthur is currently working on two-sided bargaining models, mechanism design without money, and algorithms for revealing strategies in repeated games. At the EUI Arthur will continue this agenda and focus on the behavior of automated market trading algorithms. More specifically, he will use automata models to recover information about the algorithms from their trading behavior.
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.