Alumni

Zach Branson

Zach Branson

Statistics (PhD '19)
Assistant Teaching Professor, Carnegie Mellon University, Department of Statistics
My work focuses on developing new methods for designing and analyzing experiments and observational studies. I've worked on applications in education,... Read more about Zach Branson
Luis Campos

Luis Campos

Statistics (PhD '19)
Senior Data Scientist, Etsy
I'm interested in understanding the principles that lead to successful model building and developing tools to guide practitioners to this end. These... Read more about Luis Campos
Aaron R. Kaufman

Aaron R Kaufman

Government (PhD '19)
Assistant Professor, New York University Abu Dhabi, Political Science Department
I work on applying machine learning, especially text, and causal inference, especially in experimental design, to American political behavior and institutions.
Thomas Leavitt

Thomas Leavitt

Postdoctoral Research Fellow, Harvard Medical School
My research develops methods in causal inference, with a specific emphasis on Difference-in-Differences, design-based inference and its integration with... Read more about Thomas Leavitt
Reagan Mozer

Reagan Mozer

Statistics (PhD '19)
Assistant Professor of Mathematical Sciences, Bentley University
My research focuses on the development and application of methods for causal inference with complex data, including text data, randomized experiments... Read more about Reagan Mozer
Nicole Pashley

Nicole Pashley

Statistics (PhD '20)
Assistant Professor, Rutgers University, Department of Statistics
I'm interested in improving tools and methodology in causal inference and experimental design
Maxime Rischard

Maxime Rischard

Statistics (PhD '19)
Lead Scientist, Cervest
My research applies geostatistical methods to causal inference questions, such as the geographic regression discontinuity design (GeoRDD). More broadly, I’m... Read more about Maxime Rischard