Panagiotis (Panos) Toulis studies causal inference in complex settings (e.g., networks) using methods of structured inference, such as permutation tests. He is also interested in the interface of statistics and optimization, particularly in inference problems on large data sets through stochastic gradient descent.

His research has been published in the Journal of the Royal Statistical Society, Annals of Statistics, Biometrika, Journal of Econometrics, Statistics and Computing, and Games and Economic Behavior, as well as in major machine learning and economics conferences. For his research, Toulis has received the Arthur P. Dempster Award from Harvard University’s Department of Statistics, the LinkedIn Economic Graph Challenge award, and the 2012 Google United States/Canada PhD Fellowship in statistics.

Toulis got his PhD in statistics from Harvard University, advised by Edo Airoldi, David Parkes, and Don Rubin. He also holds MS degrees in statistics and computer science from Harvard University, and a BS in electrical and computer engineering from Aristotle University in Thessaloniki, Greece. Outside of academia, he has prior corporate experience in software engineering at Google Inc. and at startup companies in Greece. He also enjoys science fiction, history, and politics.

Academic Areas

  • Econometrics and Statistics

2022 - 2023 Course Schedule

Number Title Quarter
41100 Applied Regression Analysis 2022 (Autumn)
41600 Econometrics and Statistics Colloquium 2023 (Spring)