I am a second-year PhD student studying Theoretical Computer Science at MIT advised by Ryan Williams. Before this, I was an undergraduate at Rutgers University, where I was lucky enough to discuss research and learn from Eric Allender and Michael Saks. I also participated twice in the DIMACS REU program.
Most of my research is in the field of Computational Complexity Theory, which quantifies the amount of resources — like time and hardware — needed to solve computational tasks, like finding the fastest route from point A to point B on a map.
my first initial + ilango @mit.edu (plus not included)
My research so far has focused on understanding the complexity of a problem called MCSP. While MCSP has been studied since at least the 1950s, it remains quite mysterious, evading the kind of understanding we have for thousands of other problems in complexity theory. Even so, researchers have discovered fascinating connections between MCSP and other areas in Theoretical Computer Science.
For example, MCSP could be a "universal attack on cryptography": if you found a fast algorithm for MCSP, you could use it to break any type of cryptography. Thus, we expect (but do not know) that MCSP is not an easy problem to solve. My research is working towards proving MCSP is hard, which is a necessary step towards attaining provably secure cryptography.
(reverse chronological order)
FOCS ‘20 · Best Student Paper Award ·
Full Vesion PDF
ITCS ‘20 · Best Student Paper Award
CSR ‘19 · to appear in Theory of Computing Systems Special Issue for CSR ‘19
Electronic Journal of Combinatorics · Formal Power Series and Algebraic Combinatorics Conference (FPSAC ‘19)