Clayton Sanford is a Senior Research Scientist with a Ph.D. in Computer Science from Columbia and over a decade of experience at the intersection of machine learning and theoretical computer science. He focuses on the mathematical foundations of neural networks—especially transformers—to improve interpretability, transparency, and accountability, work that was supported by an NSF GRFP. Clayton has transitioned from academic research to industry roles at Google (student researcher to senior research scientist) and internships at Microsoft and AI2, where he combined theory with large-scale empirical studies and climate and combinatorial applications. He has a strong track record of proving theoretical advantages for model classes while training transformers at scale for complex reasoning tasks. Based in San Francisco, he’s actively seeking full-time ML research roles in NYC and brings both deep theory chops and practical systems experience. An unusual strength is his sustained ability to move between formal proofs and production-scale model training, which lets him both certify and scale novel ML ideas.
11 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Applied Mathematics-Computer Science, GPA: 3.9, Bachelor of Science - BS, Applied Mathematics-Computer Science, GPA: 3.9 at Brown University
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Columbia University in the City of New York
Soquel High School
Master of Philosophy - MPhil, Computer Science, Master of Philosophy - MPhil, Computer Science at Columbia University
Contributions:75 pushes, 1 branch in 8 years 3 months
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Clayton Sanford - Senior Research Scientist at Google