Research Website
This is Ethan Ashby’s research website. I am a Statistician in the Early Development Biometrics group at Genentech. I earned my PhD from the Department of Biostatistics at the University of Washington, where my research focused on developing statistical methods to evaluate vaccine effectiveness. My research was supported financially through the NSF Graduate Research Fellowship Grant. I also graduated with a BA in Mathematics from Pomona College.
I am broadly interested in the statistics for clinical trials, causal inference, survival analysis, treatment effect heterogeneity, and causal interference.
Highlights
New preprint on arXiv!
Published:
My paper, “Improving the efficiency of infectious disease prevention trials using negative control outcome event times”, is now available on arXiv. We investigate how adjusting for negative control infection times can improve the efficiency of prevention efficacy estimates against a target infection time through overlapping exposure mechanisms. The work draws heavily on semiparametric theory for coarsened/censored data models and also includes some nice connections to classical survival analysis results such as the redistribute-to-the-right algorithm. Focusing on the case of a HIV prevention study, we show that adjusting for other sexually transmitted infection times could improve precision by 27% whereas adjusting for the best available baseline covariates led to negligible improvements. You can find the manuscript linked here.
Time-varying VE Paper wins ASA Early in Career Award
Published:
My paper, “Debiasing hazard-based, time-varying vaccine effects using vaccine-irrelevant infections: An observational extension of a pivotal Phase 3 COVID-19 vaccine efficacy trial”, was selected as an Early in Career Paper Award Winner by the American Statistical Association (ASA) in 2026. Many thanks to all my collaborators, and I am excited to attend the JSM meeting in August 2026 to present my work!
Time-varying VE paper wins Student Distinguished Paper Award at ENAR
Published:
My paper, “Debiasing hazard-based, time-varying vaccine effects using vaccine-irrelevant infections: An observational extension of a pivotal Phase 3 COVID-19 vaccine efficacy trial”, was selected as a Distinguished Student Paper Award Winner by the Eastern North American Region (ENAR) of the International Biometrics Society (IBS) in 2026. Many thanks to all my collaborators, and I am excited to attend the ENAR Spring meeting in March 2026 to present my work!