I’m currently a post-doc at University of Texas At Austin as part of the COVID-19 Consortium. I finished my Ph.D. in biostatistics at UMass Amherst in the fall of 2021 with Dr. Nick Reich.
My research falls into two broad categories, Bayesian epidemic modeling and disease network inference. More specifically, Dan Sheldon and I built a Bayesian compartmental model to forecast COVID-19 mortality that was used by the U.S. Centers of Disease Control to try and understand future COVID-19 disease burden. Our model was one of the top 3 models submitted to the CDC according to Cramer et al. [1]. I also am very interested in the effect network dynamics has on disease inference. Estimates of vaccine effectiveness from observational data can suffer from pretty severe biases under non test negative design settings. Luckily, causal inference can help us mitigate this bias.
If you are looking for my work on the MechBayes COVID-19 forecasting effort take a look at the COVID-19 Modeling page.
My free time is mostly spent hanging out with my dogs, hiking, or staring at my chess board.
Here is my most up to date cv.