Sam Sinai is a machine learning leader and co-founder turned VP who has spent the last decade applying ML, stochastic optimization, and evolutionary principles to accelerate protein design at Dyno Therapeutics. With a PhD in Mathematical and Computational Biology from Harvard and an M.Eng. in AI from MIT, he bridges deep academic rigor and product-driven research to build production-ready ML systems for synthetic biology. He has progressed from founding ML lead to head of the function, scaling teams and methods that translate evolutionary models into actionable design improvements. Based in New York, he combines computational biology expertise with practical software engineering experience, having taught and developed tools across academia and industry. Colleagues rely on him for both conceptual innovations in ML-for-biology and hands-on delivery of algorithms that measurably improve protein engineering efficiency.
11 years of coding experience
10 years of employment as a software developer
Master of Engineering (M.Eng.) Artificial Intelligence, Master of Engineering (M.Eng.) Artificial Intelligence at Massachusetts Institute of Technology
Allameh Helli
Doctor of Philosophy (Ph.D.) Mathematical and Computational Biology, Doctor of Philosophy (Ph.D.) Mathematical and Computational Biology at Harvard University
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Sam Sinai - VP, Head Of Machine Learning at Dyno Therapeutics