Panagiotis (Panos) Toulis studies causal inference and experimental design in complex systems, such as multi-agent economies and social networks, in order to evaluate the efficacy of interventions on such systems. Applications of this research include market design and policy analysis. He focuses on three distinct problems, namely interference, entanglement, and dynamics, each of which can invalidate classical causal methods. He is also interested in the interface of statistics and optimization, particularly the principled statistical analysis of large data sets, with a focus on implicit stochastic approximation methods, which are numerically stable.
His research has been published in the Annals of Statistics, Games of Economic Behavior, and Statistics and Computing, and in major machine learning and economics conferences. He received the Arthur P. Dempster Award from Harvard University’s Department of Statistics, which is given annually to a PhD student who has made significant contributions to theoretical or foundational research in statistics. Other honors include the LinkedIn Economic Graph Challenge award and a Google United States/Canada PhD Fellowship in statistics.
Toulis holds a BS in electrical and computer engineering from Aristotle University in Thessaloniki, Greece, as well as MS degrees in statistics and computer science, and a PhD in statistics from Harvard University. Outside of academia, he has prior corporate experience in software engineering at Google Inc. and at several startup companies in Greece. He also enjoys science fiction, history, and politics.
2016 - 2017 Course Schedule
||Applied Regression Analysis