Summary
Aaron Fisher is a Principal Statistical Scientist with 11 years of experience applying rigorous biostatistics and machine learning to real-world genomic and health data, currently leading methodological work at Genentech after roles at Foundation Medicine and Takeda. He earned a PhD in Biostatistics from Johns Hopkins and completed postdoctoral work with leaders in biostatistics and computer science, focusing on interpretability, causal inference, and fast scalable algorithms. His expertise spans survival analysis, causal inference, online hypothesis testing, functional data and Bayesian methods, with a track record of developing R packages and computational tools for large-scale genomic and neuroimaging datasets. Notably, he has worked on fast bootstrap PCA for brain MRI and on causal approaches to air pollution effects, blending deep statistical theory with practical, production-ready implementations. Based in Boston, he combines academic rigor with industry impact, often bringing insights from circadian rhythms and health equity into personalized medicine and adaptive trial design.
11 years of coding experience
5 years of employment as a software developer
Johns Hopkins University
B.A. Economics (Major) Mathematics (Minor), B.A. Economics (Major) Mathematics (Minor) at University of Rochester