Prof. Sushant Sachdeva is an Assistant Professor in the Department of Computer Science at the University of Toronto and in the Department of Mathematical and Computational Sciences at the University of Toronto, Mississauga. He is also a faculty affiliate at the Vector Institute. He obtained his B.Tech. degree in Computer Science and Engineering from IIT Bombay in 2008 and his Ph.D. in Computer Science from Princeton University in 2013.
Prof. Sachdeva was a Simons-Berkeley research fellow at the University of California, Berkeley in 2014. Subsequently, he was a postdoc at Yale University from 2014 until 2016. He spent a yearas a Research Scientist at Google during 2015-2016.
Prof. Sachdeva works on developing fast algorithms with guaranteed performance for problems ranging from computer science to machine learning and statistics. He specializes in graph algorithms, synthesizing tools from continuous optimization and discrete analysis. He is most well-known for his work on randomized Gaussian elimination for solving linear systems, and fast algorithms for computing network flow capacities.
Prof. Sachdeva has many awards and fellowships to his credit which include the Sloan Research Fellowship (2023), the FOCS Best Paper Award (2022), the Ontario Early Researcher Award (2022), the Google Faculty Research Award (2018), the NSERC Discovery Award (2018), and the IITB President of India Gold Medal (2008).