Assistant Instructional Professor in Computational Social Science
1155 East 60th Street, Room 221
Dr. Ferrari is an Assistant Instructional Professor in the Masters in Computational Social Science program and a Political Scientist with expertise in OECD and Latin America countries. He holds a PhD degree in Political Science and Scientific Computing from the University of Michigan, Ann Arbor, and an MA degree in Statistics from the same university. Dr. Ferrari is interested in a wide range of topics in computational social sciences, comparative politics, and political methodology. He teaches courses on Computational Methods for Political Science, Advanced Machine Learning, Bayesian Statistics, and Introduction to Computer Science. His doctoral research proposes innovative hierarchical unsupervised learning methods to estimate latent interactions in observational and experimental studies and to measure the polarization of policy preferences. Broadly, his substantive research combines political economy, political sociology, and social cognition approaches to study the formation of political preferences. In his recent research, he examines the connections between people's socioeconomic conditions, cognitive perceptions about the socioeconomic environment, and political opinions. For more information, please visit his homepage.