Adjunct Faculty & Ph.D. Candidate in Political Science | M.S. Candidate in Data Science

Ali Amini is an adjunct faculty and Ph.D. candidate in Political Science at the School of Public Affairs and an M.S. candidate in Data Science in the Department of Mathematics and Statistics at American University in Washington, D.C.

Working with Prof. David Barker—his mentor and former Director of the Social, Behavioral and Economic (SBE) Sciences at the National Science Foundation—has shaped his commitment to good science and deepened his appreciation for the nuances of political psychology. He has served as a data editor and member of the editorial team at Political Analysis, where he worked under the supervision and mentorship of Prof. Jeff Gill. Collaborating with him on projects in AI, survey methodology, and Bayesian inference has shaped his appreciation for political methodology.

His dissertation, Three Essays on AI, Survey Measurement and Political psychology, develops new theory for American Politics, framework for survey methodology and use frontier AI to empirically test them. Ali's dissertation committee is evenly represented by political psychologists and methodologist. Professor David Barker (Chair) and Professor Jan Leighley, current NSF program directors, represent the political behavior side, while Professors Jeff Gill and Ryan Moore bring methodological expertise. His dissertation chapter on introducing transfer learning paradigm for survey research received the Bud Roper Fellow Award from the American Association for Public Opinion Research (AAPOR) in 2025. His chapter on Artificial Polarization, which develops a Bayesian benchmarking of LLMs, received travel award from Princeton and APSA Section 10 for PolMeth 2026, and recognized as student runner-up award for the AAPOR 2026.