Jason Anastasopoulos


Assistant Professor of Political Science
Assistant Professor of Public Administration and Policy
Faculty Affiliate, Institute of Artificial Intelligence

Curriculum Vitae

Professional Website

Dr. Anastasopoulos is an Assistant Professor in the Department of Political Science, the Department of Public Administration and Policy and is a faculty affiliate at the Institute of Artificial Intelligence. His research focuses on understanding how technology shapes democratic political institutions and decisionmaking with a focus on American and European bureaucracies. He also has research interests in the political economy of immigration and religion.

His work has been published or accepted for publication at the American Political Science Review, Political Analysis, the Journal of Public Administration Research and Theory, Electoral Studies and  American Politics Research.

Dr. Anastasopoulos also does research on political methodology at the intersection of machine learning, big data and causal inference. His research in this area includes using machine learning algorithms to improve upon classical causal inference techniques,  text-as-data, image analysis, scalable missing data imputation and Bayesian causal inference. 

Selected Publications
  1. Jason Anastasopoulos and Anthony Bertelli. “Understanding Delegation Through Machine Learning: A Method and Application to the European Union.” Accepted for publication. American Political Science Review.
  1. Reagan Mozer, Luke Miratrix, Aaron Kaufmann and Jason Anastasopoulos. “Matching with Text Data: An Experimental Evaluation of Methods for Matching Documents and of Measuring Match Quality.” Forthcoming. Political Analysis.
  1. Jason Anastasopoulos and Andrew B. Whitford.Machine Learning for Public Administration Research,with Application to Organizational Reputation.” Journal of Public Administration Research and Theory.