He received his PhD from the NYU Department of Politics in September, 2012, specializing in U.S. politics (political behavior, campaigns, opinion, political psychology, social media) and political methodology (quantitative text analysis, machine learning, bayesian methods, agent-based models, networks). His dissertation develops new techniques in text analysis to model the interplay between speech, belief, and behavior in legislatures, campaign advertising, and online communication. His current research projects examine argument and long-term opinion change online; the spread and evolution of ideas over Twitter; and predicting and explaining Supreme Court decisions using the text of legal briefs.