Yeshwanth is a first year PhD student in Computer Science at UC Berkeley, advised by Peter Bartlett. Yeshwanth is broadly interested in statistical and computational issues arising in machine learning, focusing on the development of efficient algorithms and computational lower bounds. Previously, he spent two years as a research fellow in the Machine Learning and Optimization Group at Microsoft Research, India, where he worked with Prateek Jain, Praneeth Netrapalli and Nagarajan Natarajan on provable non-convex algorithms for machine learning. Previously, Yeshwanth was an undergraduate student at IIT Bombay where he obtained his B. Tech in Computer Science in 2015. Yeshwanth worked on Entity Linking and Disambiguation with Ganesh Ramakrishnan and Soumen Chakrabarti for his undergraduate thesis.