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.
Nonparametric Estimation of Conditional Incremental Effects
A. McClean, Z. Branson, and E. H. Kennedy
Incremental causal effects: an introduction and review
M. Bonvini*, A. McClean*, Z. Branson, and E. H. Kennedy
Handbook of Matching and Weighting in Causal Inference, 2023, arxiv
* Equal contribution
Incremental Propensity Score Effects for Criminology: An Application Assessing the Relationship Between Houselessness, Behavioral Health Problems, and Recidivism
L. Jacobs, A. McClean, Z. Branson, E. H. Kennedy, and A. Fixler