Bio
I am a fourth-year PhD student at UT Austin, where I am advised by Scott Aaronson and supported by an NSF Graduate Research Fellowship. My research interests are in complexity theory and quantum information. Previously, I was an undergraduate studying EECS at UC Berkeley, where I was incredibly fortunate to be advised by Avishay Tal and Prasad Raghavendra. During the summer of 2023, I was an intern at Sandia National Laboratories mentored by Ojas Parekh. For more details, you can find my CV here.
In Spring 2024, I was a long-term participant at the Simons Institute program on Quantum Algorithms, Complexity, and Fault Tolerance.
Outside of research, I am an avid enjoyer of nature, especially zoology. I also play basketball and tennis, and am a big fan of Steph Curry and the Golden State Warriors.
Research Overview
I am broadly interested in quantum information and complexity theory. Concretely, some topics of my research include:- Quantum Learning Theory
- Quantum Complexity Theory
- Fermions
- Stabilizer Formalism
- Analysis of Boolean Functions
- Property Testing
- Query Complexity
Papers
Authors are ordered alphabetically by last name, as is customary in my field.
- Mildly-Interacting Fermionic Unitaries are Efficiently Learnable (arXiv)
Vishnu Iyer
- Tolerant Testing of Stabilizer States with Mixed State Inputs (arXiv)
Vishnu Iyer, Daniel Liang
- Agnostic Tomography of Stabilizer Product States (arXiv)
Sabee Grewal, Vishnu Iyer, William Kretschmer, and Daniel Liang
- Pseudoentanglement Ain't Cheap (arXiv)
Sabee Grewal, Vishnu Iyer, William Kretschmer, and Daniel Liang
TQC 2024
- PDQMA = DQMA = NEXP: QMA With Hidden Variables and Non-collapsing Measurements (arXiv)
Scott Aaronson, Sabee Grewal, Vishnu Iyer, Simon Marshall, and Ronak Ramachandran
- On the Rational Degree of Boolean Functions and Applications (arXiv, ECCC)
Vishnu Iyer, Siddhartha Jain, Robin Kothari, Matt Kovacs-Deak, Vinayak Kumar, Luke Schaeffer, Daochen Wang, and Michael Whitmeyer
- Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates (arXiv)
Sabee Grewal, Vishnu Iyer, William Kretschmer, and Daniel Liang
QIP 2024
- Improved Stabilizer Estimation via Bell Difference Sampling (arXiv)
Sabee Grewal, Vishnu Iyer, William Kretschmer, and Daniel Liang
QIP 2024, STOC 2024
- Low-Stabilizer-Complexity Quantum States are not Pseudorandom (arXiv)
Sabee Grewal, Vishnu Iyer, William Kretschmer, and Daniel Liang
ITCS 2023 (Best Student Paper Award)
- Junta Distance Approximation with sub-Exponential Queries (arXiv, ECCC)
Vishnu Iyer, Avishay Tal and Michael Whitmeyer
CCC 2021
Teaching
I am keenly interested in teaching computer science and have served on course staff for 8 different course offerings:UT Austin:
- CS 395T: Analysis of Boolean Functions (Spring 2023)
- Quantum Information Science I (Spring 2022)
- CS 331: Algorithms and CS Theory (Fall 2021)
- CS 170: Efficient Algorithms and Intractable Problems (Spring 2020)
- CS 170: Efficient Algorithms and Intractable Problems (Fall 2019)
- CS 70: Discrete Math and Probability (Summer 2019)
- CS 170: Efficient Algorithms and Intractable Problems (Spring 2019)
- CS 70: Discrete Math and Probability (Summer 2018)
In 2019, I received the Oustanding GSI award from the UC Berkeley Graduate Division, for which I am incredibly grateful to my students and mentors. My full evaluations at UC Berkeley can be found here.
Service
I believe that my role as an academic involves service. As an undergraduate, I served on the EECS Undergraduate Study Committee (UGSC), interfacing with professors to address issues such as elitism and discrimination. In addition, I worked with the department to design, administer, and analyze the annual undergraduate experience survey. My work in this area helped facilitate a number of reforms, including the EE/CS community week and calls for culture change within EECS extracurricular groups.I am a volunteer with Texas Prison Education Initiative, where I teach UT Austin's discrete mathematics course.
back to top