Vinayak M. Kumar

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.

Publications

• 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)

Teaching

• 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)