معرفی
Zach Branson is an Associate Teaching Professor and Assistant Director for the Undergraduate Program at Carnegie Mellon University's Department of Statistics & Data Science within the Dietrich College of Humanities and Social Sciences. His work bridges theoretical and applied statistics, with a focus on experimental design and causal inference.
- PhD in Statistics, Harvard University (2019)
- BS in Economics and Statistics, Carnegie Mellon University (2014)
- BA in Professional Writing, Carnegie Mellon University (2014)
Branson's research centers on experimental design and causal inference, particularly addressing questions like "Does a treatment cause a change in outcomes?" His methodological interests include covariate balance, matching, randonization tests, and regression discontinuity designs. Applications span education, epidemiology, mental health, and text analysis.
His recent publications emphasize causal inference in educational and social sciences, with methodological innovations in rerandomization, propensity score trimming, and regression discontinuity designs. Key themes include improving covariate balance, handling continuous treatments, and applying Bayesian nonparametric approaches to spatial data.
- NSF Graduate Research Fellowship (for PhD work on experimental design)
Branson actively engages in teaching causality and statistical communication to undergraduates, advocating for capstone courses (e.g., 36-490, 36-493, 36-497) to foster practical data science skills. He also contributed to public-facing statistical pedagogy through "data science portfolio" projects.
