
Hi! I’m Adam, a Bayesian statistician and data scientist. I like working on high impact problems with sparse, noisy, biased, or hard won data, where careful statistical thinking matters.
If you’d like to collaborate or just chat, get in touch.
I work with the CDC’s Center for Forecasting and Outbreak Analytics on epidemic forecasting. I’m building towards daily, county-level estimates of the time-varying reproduction number using generalized additive models. I previously focused on developing and applying tools for estimating delay distributions.
I also work with Active Site on the design and analysis of studies evaluating real world AI assistance for biological tasks (Hong et al. 2026).
I completed my PhD “Bayesian spatio-temporal methods for small-area estimation of HIV indicators” at Imperial College London on the StatML CDT with Seth Flaxman and Jeffrey Imai-Eaton. I worked on comparing models for area-level spatial correlation, estimating district-level HIV risk group proportions [Howes et al. (2023); SHIPP], and developing Bayesian inference methods (Howes et al. 2025).
I’ve been a visiting researcher at the MIT Media Lab contributing to the Nucleic Acid Observatory project for detecting biological threats, and at the University of Waterloo working on adaptive quadrature methods. After my PhD, I worked at the University of Oxford modelling food security with the WFP (Ishida et al. 2025), and contributed to an individual-based model supporting Blueprint Biosecurity’s far UVC roadmap.