John Abel is a computational scientist and machine-learning engineer with 11 years of experience applying systems biology and data-driven methods to understand disease and accelerate biomedical discovery. He holds a PhD in Systems Biology from Harvard and has moved from academic neurobiology research at MIT/MGH into senior industry roles, most recently leading computational science and AI at immunotherapy and pathology-focused companies. His work spans building reproducible biomedical ML pipelines, translational data science for pathology, and systems-level modeling—skills he now brings to a stealth startup in Boston. Colleagues describe him as someone who bridges rigorous experimental empiricism with production-ready ML, translating complex biological questions into deployable computational solutions. Notably, his background combines deep control-theory and systems modeling training with hands-on pathology ML productization, giving him a rare mix of theory and applied engineering.
11 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Systems Biology, Doctor of Philosophy (Ph.D.) Systems Biology at Harvard University
Master of Science (M.S.) Chemical Engineering, Master of Science (M.S.) Chemical Engineering at UC Santa Barbara
Bachelor of Science (B.S.) Chemical Engineering, Bachelor of Science (B.S.) Chemical Engineering at Tufts University
Contributions:45 pushes, 1 branch in 6 years 6 months
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John Abel - Member Of Technical Staff at Stealth Startup