I am a 5th-year PhD student in Statistics at Carnegie Mellon University, where I am advised by Zach Branson and Edward Kennedy. Additionally, I have had the pleasure of working with Siva Balakrishnan and Larry Wasserman. My primary research interests are at the intersection of statistics, machine learning, and causal inference. Some topics I have worked on include

During my PhD, I have gained experience as a teaching assistant for several courses related to causal inference and other areas of statistics. I also instructed CMU’s Sophomore-level Introduction to Statistical Inference course.

I completed my undergraduate education at Swarthmore College, where I earned a Bachelor’s degree in Mathematics and Economics in 2016. Before starting my PhD, I worked for three years as a Research Analyst and later as a Senior Research Analyst at the Brattle Group. There, I helped analyze data and build statistical models for legal, regulatory, and policy issues.



Google Scholar and CV (current as of March 2024)


Contributor to npcausal package


Our paper, Nonparametric Estimation of Conditional Incremental Effects, was accepted at the Journal of Causal Inference

Our paper, Incremental Propensity Score Effects for Criminology, was accepted at the Journal of Quantitative Criminology

My poster on double cross-fit doubly robust estimators won the Ten Have award at ACIC 2023


As Course Instructor

As Teaching Assistant