Summary
Prateek Yadav is a Senior Research Scientist with a decade of experience at the intersection of continual learning, sparsity, and modular AI, currently contributing to DeepMind after research roles at UNC Chapel Hill, Meta, and internships across Google DeepMind, Microsoft, and AWS. His PhD work focuses on making deep models generalize across domains by leveraging memory, mixture-of-experts, and efficient sparse mechanisms, with prior research spanning interpretability, compositional reasoning, graph/hypergraph methods, uncertainty estimation, and Bayesian temporal modeling. He has a strong applied track record—developing continual learning for code models at AWS, improving content quality via social graph signals at LinkedIn, and pre-training frontier models at Meta—grounded in an undergraduate foundation in pure mathematics from IISc. Known for bridging theoretical insights with practical systems, he often combines rigorous probabilistic thinking with engineering at scale.
10 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Mathematics and Computer Science, Bachelor of Science - BS, Mathematics and Computer Science at Indian Institute of Science (IISc)
High School, Physics, Chemistry and Mathematics, High School, Physics, Chemistry and Mathematics at Step By Step High School , Jaipur
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at The University of North Carolina at Chapel Hill
Middle School, Middle School at St. Anselm's North City School , Jaipur
English, Hindi