Summary
Andrew Baumgartner is a biostatistician and theoretical physicist with eight years of experience applying statistical physics, information theory, and probabilistic machine learning to biological and biomedical data. He models stochastic processes underlying electronic health records, single-cell and bulk multi-omics, and immune repertoires to uncover dynamics of differentiation, clonal evolution, and disease trajectories. At Phenome Health he leads development of portable probabilistic models and ensures statistical validity across diverse projects, building on prior research scientist and postdoc roles at the Institute for Systems Biology. His work blends rigorous theory (PhD in theoretical and mathematical physics) with practical data science, translating statistical mechanics concepts into actionable biomedical analyses. Notably, he has applied uncommon tools—like topological data analysis and holographic principles—to real-world genomics problems, reflecting a knack for interdisciplinary methodology. Based in Seattle, he combines deep quantitative modeling with a focus on reproducible, portable approaches for clinical and systems medicine applications.
8 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Theoretical and Mathematical Physics, Doctor of Philosophy - PhD, Theoretical and Mathematical Physics at University of Washington
Bachelor of Science (B.S.), Physics and Mathematics, Bachelor of Science (B.S.), Physics and Mathematics at Manhattan College