Email: vmkumar at cs dot utexas dot edu

I am a third-year Ph.D. student in UT Austin's Computer Science Theory group, fortunate to be advised by David Zuckerman. I am interested in analytic and combinatorial problems in pseudorandomenss, like correlation bounds, Boolean function analysis, and coding theory.

Before joining UT Austin in 2021, I received my B.S. in mathematics and computer science at Caltech. I'm extremely grateful to have been mentored by Venkatesan Guruswami and Leonard Schulman during my undergraduate years.

**On the Rational Degree of Boolean Functions and Applications**

Vishnu Iyer, Siddhartha Jain, Matt Kovacs-Deak, Vinayak M. Kumar, Luke Schaeffer, Daochen Wang, Michael Whitmeyer

*Preprint*

(arXiv)**Relaxed Local Correctability from Local Testing**

Vinayak M. Kumar, Geoffrey Mon

*STOC 2024 (to appear)*

Danny Lewin Best Student Paper Award

(ECCC)(arXiv)**Tight Correlation Bounds for Circuits Between AC0 and TC0**

Vinayak M. Kumar

*CCC 2023*

(ECCC) (arXiv) (CCC Proceedings)**Pseudobinomiality of the Sticky Random Walk**

Venkatesan Guruswami, Vinayak M. Kumar

*ITCS 2021*

(ECCC) (ITCS Proceedings) (My Talk at ITCS)**Condition Number Bounds for Causal Inference**

Spencer Gordon, Vinayak M. Kumar, Leonard Schulman, Piyush Srivastava

*UAI 2021*

(UAI Proceedings) (Piyush's Talk at Simons)

- CS 395T: Pseudorandomness (Fall 2023)
- CS 388C: Combinatorics and Graph Theory (Spring 2023)

- CS 151: Complexity Theory (Spring 2021)
- CS 139: Design and Analysis of Algorithms (Winter 2021)
- CS 38: Introduction to Algorithms (Spring 2020)
- CS 21: Complexity Theory (Winter 2020)
- Ma 0: Transition to Mathematical Proofs (Summer 2020)