Summary
Sreejan Kumar is a postdoctoral research scientist combining quantitative neuroscience and machine learning across Columbia's Zuckerman Institute and NYU Psychology, supported by the Leon Levy Foundation. He holds a PhD from Princeton in Quantitative & Computational Neuroscience and has a decade of research experience spanning human neuroimaging, neuromotor interfaces at Meta, and systems neuroscience from Caltech to Yale. His work has earned a NeurIPS best paper award and a Google PhD Fellowship, with publications in NeurIPS, ICLR, PLoS Computational Biology, and Nature Communications. Comfortable at the intersection of theory and experiment, he builds and evaluates computational models that link neural data to behavior and adaptive systems. Based in New Jersey, he blends rigorous statistical training (CS and Stats double major from Yale) with hands-on prototyping of neural interfaces and closed-loop experiments.
10 years of coding experience
10 years of employment as a software developer
Science Math Computer Science Magnet Program, Science Math Computer Science Magnet Program at Poolesville High School
Bachelor's degree Computer Science and Statistics & Data Science (double major), Bachelor's degree Computer Science and Statistics & Data Science (double major) at Yale University
Doctor of Philosophy - PhD Quantitative & Computational Neuroscience, Doctor of Philosophy - PhD Quantitative & Computational Neuroscience at Princeton University