Professional Bio

A free-spirited young man with grand aspirations, I entered graduate school at the University of Michigan (Ann Arbor) in September of 2002. For the next six years, I toiled at coursework (Computer Science, Economics, Statistics, Mathematics, and Operations Research) and research (game theory and mechanism design, mostly of computational variety, machine learning, mostly applied to game theory and mechanism design, and simulations, mostly theory of simulation-based analysis of game theoretic interactions). In May, 2008, I finally found myself in front of my lively dissertation committee (Michael Wellman, Satinder Singh, Edmund Durfee, and Emre Ozdenoren) attempting to explain what it is that I had done those past six years. It seems that I was convincing enough to pass the dissertation defense, and, indeed, even to be nominated for the ACM Dissertation Award. While the ACM award was granted to another, I did receive honorable mention as a runner-up for the IFAAMAS Dissertation Award. In July of 2008, my family and I made a move to Philadelphia, where I was to being my two-year post doc at the University of Pennsylvania under the supervision of Michael Kearns. This move was rather refreshing, both financially and intellectually. While my interest in strictly computational things had not flagged, I had developed a new one in behavioral game theory, especially in simulating human behavior, with models developed from experimental data, and another in information economics, tipping, and nudging.

It seems, perhaps, strange that I have gone from computational mechanism design to modeling human behavior, but it should not. As a mechanism designer (in a broad sense), a central problem that you face is predicting what happens once the mechanism is in place. If what happens is determined by human behavior, it seems only natural that we must model it effectively. If a mechanism is designed for a market place dominated by software agents, by contrast, it should hardly be surprising that the behavior and outcomes one would expect would be of a qualitatively different kind than if the market was populated by people. Of course, we may imagine that a further distinction in behavior can be drawn between individuals and groups, as well as between different cultures, etc. As such, simulation-based modeling of behavior of agents in multiagent systems is to be a sophisticated science, not one characterized by a one-size-fits-all philosophy. My long-term broad research agenda, then, is to develop the science of computational modeling of agent behavior in multiagent systems.