Michael Zietz
Embedded Software Developer at Anduril Industries
California, United States
Summary
👤
Senior🎓
Top SchoolMichael Zietz is an embedded software developer and computational geneticist with 10 years of experience applying machine learning and statistical methods to biomedical problems. He recently transitioned from academia—where his PhD work at Columbia and contributions like WebGWAS.org, NSIDES, and fast heritability/PRS methods dramatically sped up genetic analyses—to industry at Anduril, bringing a track record of turning compute-heavy research into production-ready, high-performance tools. His background in physics and biotech research labs (Columbia, Penn, Cedars-Sinai) informs a pragmatic approach to reproducible research, dimensionality reduction, and parallel computation. Notably, he has published widely-cited work linking blood type to COVID-19 outcomes and built tools that reduce genetic test runtimes by orders of magnitude. Based in California, he bridges deep methodological innovation with embedded systems development to deliver efficient, real-world solutions.
10 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD, Biomedical Informatics, Doctor of Philosophy - PhD, Biomedical Informatics at Columbia University in the City of New YorkMaster of Science - MS, Physics, Master of Science - MS, Physics at University of Pennsylvania
Github Skills (112)
hail10
permutation10
genomics10
degrees10
journal9
doi9
connectivity9
tidyverse9
r-language9
genetics9
blockchain9
gwas9
ethereum9
bioinformatics9
tidymodels9
Programming languages (11)
Github contributions (5)
zietzm/hetmech
May 2017 - Jun 2020
Greene Lab/Theory In Practice collaboration on identifying mechanisms using hetnets
Contributions:6 PRs, 406 pushes, 103 branches in 3 years 1 month
hetnetscollaborationlabtheory
zietzm/xswap
Dec 2018 - Aug 2019
Contributions:4 PRs, 190 pushes, 55 branches in 8 months
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