I am the Class of 1987 Professor of Politics at the Department of Politics, Princeton University.

I specialize in political methodology and legislative behavior, with an interest in the application of text-as-data/NLP, Bayesian statistics, machine learning, item response theory and generalized linear models in political science. My substantive field is comparative politics, and I focus primarily on the United Kingdom. I'm especially interested in British Political Development for the period after the Great Reform Act. On this site, you can find a copy of my vita (pdf), data, code and some of my working papers.

Previously, I served as Professor of Politics and Data Science at New York University. From 2016--2022, I was the Deputy Director and the Director of Graduate Studies (MSDS) at the Center for Data Science, and Chair of the Executive Committee of the Moore-Sloan Data Science Environment. I received my PhD from the University of Rochester, Department of Political Science, in 2008. From 2008 to 2015, I was an Assistant Professor and then the John L. Loeb Associate Professor of the Social Sciences in the Department of Government at Harvard University.

I currently serve as the President of the Society for Political Methodology, and I am head of APSA Section 10. I serve on the executive committee of Data-Driven Social Science, and on the executive committee of Princeton Language + Intelligence. I am a member of the advisory board of the Data Science Institute at LSE.

Separate to my "academic" output, I wrote an essay on rejection, some advice on being a grad student and a talk on job talks that some people found helpful. I've also written an oped for Nature, and one for Nature Computational Science, on Large Language Models.