I am a PhD candidate in the Department of Government at Harvard University and an affiliate of the Institute for Quantitative Social Science and the Minda de Gunzberg Center for European Studies. In the fall of 2020, I will be joining the Department of Political Science at the University of Pittsburgh as an assistant professor.
My on-going research fits into two strands. First, I create new methods to facilitate political science research by leveraging the intersection of Bayesian methods and machine learning. Each of the three papers in my dissertation creates a new method to tackle a class of problem (heterogeneous effects, hierarchical models, and ideal point estimation) that is commonly studied but where existing methods have limitations that constrain substantive researchers. Second, I focus on understanding legislative behaviour using text-as-data in a comparative context including studies on Europe, United States, and Japan.
My research on these topics and others is published in Political Analysis, Comparative Political Studies, Legislative Studies Quarterly, the Annual Review of Political Science, and Parliamentary Affairs.
I can be contacted at goplerud[at]g.harvard.edu and a CV can be found here.