Please note: This seminar will take place in DC 1304.
Santhoshini Velusamy, Research Assistant Professor
Toyota Technological Institute at Chicago
The amount of data being generated and stored has increased rapidly over the past few decades. While data is measured in massive units like petabytes and zetabytes, the capacity of a device’s readily accessible memory, such as RAM, is only a few hundred gigabytes.
My research focuses on solving fundamental problems in new models of computation that consider the storage limitations of local memory. In this talk, I will discuss my work on Constraint Satisfaction Problems (CSPs) — a well-studied class of combinatorial optimization problems with wide-ranging applications in computer science — in the streaming model. In addition to fully characterizing the solvability of CSPs in this model through new algorithms and matching impossibility results, my work also reveals exciting new connections to other models. I will conclude the talk by discussing future directions.
Bio: Santhoshini Velusamy is currently a Research Assistant Professor at Toyota Technological Institute at Chicago. She completed her PhD in 2023 from Harvard University, where she was supervised by Prof. Madhu Sudan. She is the recipient of a Google PhD fellowship and an NSF CRII award.
Santhoshini does research in theoretical computer science and is specifically interested in the design and analysis of algorithms in modern computational settings like streaming. She is also interested in problems in algorithmic game theory.