Jason Yamada-hanff is a Principal Bioinformatics Scientist with 15 years of experience at the intersection of computational biology, software engineering, and computer vision. With a PhD in Neuroscience from Harvard Medical School, he leads teams building production-grade pipelines, machine-vision devices, and cloud services—blending statistical inference, SQL-backed architectures, and reproducible data platforms. He has a track record of performance and resource optimizations (e.g., 10×–30× image processing speedups and 100× memory reductions for sequencing analyses) and routinely ships solutions in Python, R, Docker, and PostgreSQL. Comfortable across many languages from C++ to Haskell and Rust, he combines deep domain knowledge in biology with pragmatic systems design. Based in Los Angeles, he’s equally at home mentoring engineers and rolling up his sleeves to implement efficient, auditable pipelines that enable new scientific insights. An underrated strength is his history of modernizing legacy scientific codebases and tooling—bringing reproducibility and testing to research software.
15 years of coding experience
10 years of employment as a software developer
Bachelor of Arts (BA), Biology, Bachelor of Arts (BA), Biology at Swarthmore College
Doctor of Philosophy (PhD), Neuroscience, Doctor of Philosophy (PhD), Neuroscience at Harvard Medical School
A clone of the animated decision tree at http://www.r2d3.us/ in React, React-Motion, and d3
Contributions:52 commits, 10 pushes, 2 branches in 1 year 3 months
decision-treereactreact-motion
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