Education

  • M.S., Ph.D. University of Michigan
  • B.A. Swarthmore College

Areas of Expertise

  • Game Theory
  • Agent-Based Modeling
  • Artificial Intelligence
  • Machine Learning

Background

I joined the Mathematics and Computer Science department at Davidson in 2019, after four years as a visiting assistant professor at Swarthmore. I teach introductory and upper-level classes across the computer science curriculum ranging from theory to artificial intelligence to systems.

My research in computational game theory lies at the boundary of computer science and economics, and straddles the CS subfields of theory, artificial intelligence, and machine learning. I use game theory to analyze incentive problems that arise in computer science applications, and also use computational methods to enable better game theory. This involves designing agent-based simulations to gather data about multi-agent systems and applying machine learning to build game-theoretic models and predict behavior. I am also interested in algorithms for playing and solving games that people play, as well as games that model economic interactions.

My main hobbies are board games and sports, especially ultimate Frisbee. I’m almost always happy to take a quick break to play a game, toss a disc, or just have a chat; so please stop by my office and say hi!