Sanjiv Kumar


Google Fellow, VP
Google Research, NY
New York, NY 10011, USA
sanjivk@google.com




Short Bio
Sanjiv Kumar is a Google Fellow and VP at Google Research, where he is leading a team on theory and applications of large ML Foundation Models and Generative AI. His recent research interests include rethinking existing modeling and compute paradigms in LLMs with a focus on developing alternative techniques that allow fast training and inference. He also leads research in deep retrieval and ranking, massive-scale similarity search, and online clustering, impacting a large number of applications in Google Search, YouTube, Ads, Android, Chrome and Cloud. He has led the development of the state-of-the-art open-source similarity search engine, ScaNN, which has been widely adopted externally. Sanjiv has published more than 125 papers in the field of machine learning, computer vision and robotics, and holds 60+ patents. His work on convergence of Adam received the best paper award in ICLR, 2018. He is an action editor of JMLR and holds a PhD (2005) from the School of Computer Science at Carnegie Mellon University.


Research Interests

Large Scale Machine Learning, LLMs and Generative AI, Computer Vision, Health AI, Robotics


Teaching

EECS6898: Large-Scale Machine Learning, Fall 2010, Columbia University, New York, NY.


Tutorial

Approximate Nearest Neighbor Search (Trees and Hashes): Part-I, Part-II.
Fast Matrix Decomposition: Part-I, Part-II.


Recent Publications [ All Publications ]