Contact: ksingal@seas.upenn.edu
I am currently a PhD student at the University of Pennsylvania, where I am extremely grateful to be advised by Erik Waingarten and Sanjeev Khanna. Broadly, my research interests lie in efficient algorithm design for problems in machine learning and high-dimensional geometry. Specifically, my work has focused on designing provably fast and accurate algorithms for vector quantization, clustering, attention, and other problems dealing with high-dimensional data. Previously, I studied computer science and mathematics at Columbia University, where I was fortunate to have been mentored by Alexandr Andoni and Xi Chen.
I am currently a co-organizer of the Penn Theory Seminar. Please reach out if you're interested in giving a talk!
Inner Product Aware Quantization: Provably Fast, Accurate, and Adaptive Algorithms
Nathan White, Krish Singal
Preprint
A Polynomial Space Lower Bound for Diameter Estimation in Dynamic Streams
Sanjeev Khanna, Ashwin Padaki, Krish Singal, Erik Waingarten
On the Size and Complexity of Scrambles
Seamus Connor, Steven DiSilvio, Sasha Kononova, Ralph Morrison, Krish Singal
Nila Cibu, Kexin Ding, Steven DiSilvio, Sasha Kononova, Chan Lee, Ralph Morrison, Krish Singal
Preprint
Chip-Firing Games on Banana Trees
Marchelle Beougher, Nila Cibu, Kexin Ding, Steven DiSilvio, Kristin Heysse, Sasha Kononova, Chan Lee, Ralph Morrison, Krish Singal
Preprint
MC$^2$: Rigorous and Efficient Directed Greybox Fuzzing
Abhishek Shah, Dongdong She, Samanway Sadhu, Krish Singal, Peter Coffman, Suman Jana
ACM CCS 2022   Honorable Mention for Best Paper Award
I have served as a reviewer for: STACS 2026
In Fall 2023, I co-led a seminar on the Analysis of Boolean Functions as part of the Columbia Undergraduate Learning Seminar in Theoretical Computer Science.
I have served as a teaching assistant for the following course offerings
In my free time, I enjoy long-distance running, reading, writing, playing music, and watching movies.