Hunter Nisonoff
Scientist II, Machine Learning at Generate:Biomedicines
United States
Summary
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Senior🎓
Top SchoolHunter Nisonoff is a machine learning scientist with 11 years of experience applying computational methods to protein engineering, currently building ML-driven discovery pipelines at Generate:Biomedicines. He holds a PhD in Computational Biology from UC Berkeley and a mathematics background from Duke, combining rigorous theory with practical modeling skills honed during a stint at D. E. Shaw Research. His work bridges deep learning, biophysics, and experimental collaboration to accelerate design of biomolecules, with an emphasis on moving models toward impactful wet-lab validation. Known for translating complex scientific questions into reproducible code and data workflows, he brings both research depth and applied engineering to biotech product teams.
11 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Computational Biology, Doctor of Philosophy - PhD, Computational Biology at University of California, BerkeleyMathematics, Mathematics at Duke University
Github Skills (105)
python10
deep-learning10
gpu10
graph-convolutional-networks10
nbdev10
fastai10
graph10
graph-neural-network10
geometric-deep-learning10
pytorch10
machine-learning10
bioinformatics10
protein-structure9
simulations8
emacs-lisp8
Programming languages (6)
Github contributions (5)
hnisonoff/emacs-init
Aug 2017 - Mar 2022
Contributions:6 pushes, 1 branch in 4 years 7 months
donaldlab/OSPREY3
Sep 2015 - May 2020
Open Source Protein REdesign for You v3
Contributions:123 commits, 2 PRs, 75 pushes in 4 years 8 months
bioinformaticsproteinredesign
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