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Max Goplerud is an Assistant Professor in the Department of Government at the University of Texas at Austin. He specializes in political methodology, focusing on Bayesian statistics, machine learning, and legislative politics. His research aligns with developing new methodologies that enhance political science research, particularly by leveraging Bayesian methods and machine learning approaches. Goplerud has authored working papers that address various common challenges in political science, such as heterogeneous effects and hierarchical models, and he critically evaluates existing methodological limitations that affect substantive research. His work emphasizes a comprehensive understanding of legislative behavior through text-as-data comparative analyses across different regions, including Europe, the United States, and Japan. His scholarship has been published in reputable journals, including the American Political Science Review and Political Analysis.
General requirements for the Graduate School at UT Austin apply to all programs unless otherwise specified.