Max Goplerud

Max Goplerud is an Assistant Professor in the Department of Government at the University of Texas at Austin, where he teaches courses in political methodology and Bayesian statistics. He received his Ph.D. from Harvard University in 2020, where he was an affiliate of the Institute for Quantitative Social Science and the Minda de Gunzberg Center for European Studies.

His educational background includes:

• Ph.D. in Government, Harvard University (2020)

Goplerud's research spans two primary areas. First, he develops new statistical methods at the intersection of Bayesian statistics and machine learning to address limitations in existing approaches for political science research. His methodological work focuses on solving problems related to heterogeneous effects, hierarchical models, and ideal point estimation. Second, he applies text-as-data methods to study legislative behavior across different political contexts, including Europe, the United States, and Japan. His research combines advanced statistical techniques with substantive political questions, creating tools that enhance empirical analysis in political science.

His publications reveal a strong focus on methodological innovation in political methodology. Goplerud frequently publishes in top political science and statistics journals, with recent work appearing in the American Political Science Review, American Journal of Political Science, Journal of Politics, Biometrika, Political Analysis, and Bayesian Analysis. His research bridges the gap between statistical methodology and political science applications, with particular emphasis on Bayesian approaches, variational inference, and machine learning techniques adapted for political science research questions.

Goplerud has developed several R packages that implement his methodological contributions:

• vglmer - for estimating hierarchical models using variational inference
• FactorHet - for estimating heterogeneous effects in factorial and conjoint experiments
• gKRLS - for kernel regularized least squares estimation

He teaches graduate courses including Bayesian Statistics and Statistical Analysis in Political Science, as well as undergraduate research methods courses. His teaching spans institutions including the University of Texas at Austin and the University of Pittsburgh, where he previously taught courses on measurement, Bayesian statistics, and social data visualization.