About

For my undergraduate degree, I studied Mathematics at the State University of New York at Geneseo. I then worked from 2014-2018 as a software developer at Silent Spring Institute in Newton, Massachusetts, where I worked on methods for making complex scientific information accessible to lay audiences.

From 2018-2022 I pursued a PhD in Biostatistics in the Department of Biostatistics & Epidemiology at the University of Massachusetts Amherst, with Leontine Alkema as my advisor. For the 2021-2022 academic year I studied with Antoine Chambaz at the MAP5 laboratory, Université de Paris, on a Chateaubriand Fellowship.

My thesis was titled “Bayesian Hierarchical Temporal Modeling and Targeted Learning with Application to Reproductive Health”. The slides I used for the defense give a nice overview of the thesis, and are available here.

My current research interests include Bayesian modeling, causal inference, semi-parametric statistics, and targeted learning. I’m interested in applications in global health, climate change, and political economy.