Chief AI Officer and co-founder Suvrit Sra, PhD is an expert on large-scale machine learning and optimization. He is the Esther and Harold E. Edgerton (1927) Career Development Associate Professor of Electrical Engineering and Computer Science at MIT and a core faculty member in the MIT Institute for Data, Systems, and Society.
Suvrit is the author of many peer-reviewed publications in machine learning, data mining, statistics, optimization, and mathematics, has been issued several patents and is the editor of Optimization for Machine Learning (MIT Press). He founded the OPT (Optimization for Machine Learning) series of workshops at the NIPS conference, which he has co-chaired since 2008 and was an area chair for NeuRIPS 2019.
In 2019, Suvrit received a National Science Foundation career award for his research “Modern nonconvex optimization for machine learning: foundations of geometric and scalable techniques.” In 2018, Suvrit received NSF TRIPODS+X funding for research at the intersection of healthcare and AI: “Learning with Expert-In-The-Loop for Multimodal Weakly Labeled Data and an Application to Massive Scale Medical Imaging.” In 2017, Suvrit was the recipient of an NSF BIGDATA grant to create a novel suite of models and algorithms for analyzing complex datasets, with a particular focus on three factors crucial for next-generation machine learning: interpretability, interactivity and automated learning.
Suvrit received his PhD in Computer Science from the University of Texas at Austin and has served as visiting faculty at UC Berkeley and Carnegie Mellon.