Back to top

Jeff Gill Distinguished Professor Department of Government

Contact
Send email to Jeff Gill
(202) 885-6275
SPA - Government
Kerwin Hall - 109B
By Appointment
Additional Positions at AU
Distinguished Professor, Department of Math & Statistics
Distinguished Professor, Department of Government
Degrees
Postdoc, Harvard University
PhD, American University
MBA, Georgetown University
BA, Mathematics, University of California, Los Angeles

Languages Spoken
C++, R, Fortran, Python, Pascal, Cobol, SAS
Favorite Spot on Campus
Julian's benches
Bio
Jeff Gill is Distinguished Professor of Government and of Mathematics & Statistics. He is also a member of the Center for Neuroscience and Behavior and the inaugural Director at SPA's Center for Data Science, where he coordinates and supports empirical research across the campus by developing links with federal agencies, providing research support to faculty and graduate students, and building infrastructure to handle large and complex datasets. His research applies Bayesian modeling and data analysis (decision theory, testing, model selection, elicited priors) to questions in general social science quantitative methodology, political behavior and institutions, medical/health data analysis especially physiology, circulation/blood, pediatric traumatic brain injury, and epidemiological measurement/data issues, using computationally intensive tools (Monte Carlo methods, MCMC, stochastic optimization, non-parametrics). Gill serves as Editor-in-Chief of the journal Political Analysis since January of 2018. He is also an Inaugural Fellow and past-President of the Society for Political Methodology.
See Also
SPA Center for Data Science
SPA Department of Government
For the Media
To request an interview for a news story, call AU Communications at 202-885-5950 or submit a request.

Teaching

Spring 2022

  • GOVT-898 Doctoral Continuing Enrollment

  • GOVT-899 Doctoral Dissertation

Summer 2022

  • GOVT-899 Doctoral Dissertation

Fall 2022

  • GOVT-898 Doctoral Continuing Enrollment

  • STAT-618 Bayesian Statistics