
Hi! I’m Adam, a Bayesian statistician and data scientist. I like working on impactful problems where careful statistical thinking matters. If you’d like to collaborate or just chat, get in touch.
I work with the Center for Forecasting and Outbreak Analytics at CDC on epidemic surveillance. My current focus is on building daily, county-level estimates of the reproduction number using GAMs. Previously, I developed and applied tools for estimating delay distributions.
I also support Active Site on the design and analysis of studies evaluating real world AI assistance for biological tasks (e.g. 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.