Sushant Sachdeva has received a 2022 Early Researcher Award from the Government of Ontario in support of research that could have a major impact on the optimization of networks, from the electrical grid to telecommunications and transportation.

Important computational problems on networks can be captured by abstracting them as optimization problems on graphs, explains Sachdeva, an assistant professor in the tri-campus graduate Department of Computer Science and the U of T Mississauga Department of Mathematical and Computational Sciences.

Real-world physical networks are constrained by geography, and as a result, their corresponding graphs have considerable additional structure, making them planar or near-planar in nature.

Through his research, Sachdeva aims to combine the graph structure afforded by planar graphs with methods from continuous optimization to design much faster algorithms for planar graphs.

He anticipates that the results from this latest research will be directly applicable to network optimization, responding rapidly to changing conditions and helping remove capacity bottlenecks in the physical networks that we engage with on a daily basis.

In addition to his roles at U of T, Sachdeva is also a faculty affiliate of the Vector Institute for Artificial Intelligence. His research interests lie broadly in algorithms and their connections to optimization, machine learning, and statistics. His recent research focus has been the design of fast algorithms for graph problems.

Before joining U of T, he was a research scientist at Google. He completed his postdoc at Yale with Dan Spielman in 2016, his PhD from Princeton in 2013 under Sanjeev Arora, and his BTech from IIT Bombay in 2008. He is the recipient of Google Faculty Research Award, NSERC Discovery Grant, Connaught Early Researcher award, Simons Berkeley Research Fellowship, and the IITB President of India Gold Medal.