I am a fifth year graduate student in the EECS department at MIT, currently advised by Professor Elchanan Mossel. I was formerly advised by Professor Dana Moshkovitz, with whom I got my Master's degree. Before that, I was an undergraduate at UC Berkeley, where I primarily worked in the Wireless Foundations group (now Berkeley Laboratory for Information and System Sciences) with Professor Anant Sahai. I am interested in theoretical computer science, with special interests in hardness of approximation, coding theory, and statistics.
How Many Subpopulations is Too Many? Exponential Lower Bounds for Inferring Population Histories[arXiv]
with Younhun Kim, Frederic Koehler, Ankur Moitra, and Elchanan Mossel
Submitted to RECOMB 2019
Being Corrupt Requires Being Clever, But Detecting Corruption Doesn't [arXiV]
with Yan Jin and Elchanan Mossel
To appear in ITCS 2019
From Soft Classifiers to Hard Decisions: How fair can we be? [arXiV]
with Ran Canetti, Aloni Cohen, Nishanth Dikkala, Sarah Scheffler, and Adam Smith
(Old title: "Post-processing Calibrated Classifiers." To appear in FAT* 2019)
Equalizing Financial Impact in Supervised Learning [arXiV]
Efficient Multiparty Interactive Coding for Insertions and Deletions
with Ran Gelles and Yael Kalai
Relaxed Locally Correctable Codes [ECCC]
with Tom Gur and Ron Rothblum
in ITCS, 2018.
A No-Go Theorem for Derandomized Parallel Repetition: Beyond Feige-Killian. [pdf] [arXiv]
with Dana Moshkovitz and Henry Yuen.
in RANDOM 2016.
Side-information in Control and Estimation [pdf]
with Gireeja Ranade and Anant Sahai.
in International Symposium on Information Theory (ISIT) 2014
I co-organized the Great Ideas in Theoretical Computer Science Seminar with Tal Wagner from Fall 2014 to Fall 2015.
I am currently a co-organizer for the Algorithms and Complexity Seminar at MIT
Email: govind (at) mit (dot) edu