Sidhanth Mohanty

Email: sidhanthm (at) cs (dot) berkeley (dot) edu

Office: 634 Soda Hall

I am a PhD student in the Theory Group at UC Berkeley, fortunate to be advised by Prasad Raghavendra. Most recently, I have been exploring the connections between semidefinite programming and the statistical physics lens into algorithm design. More generally, I am interested in probability & combinatorics.

My undergraduate education was at Carnegie Mellon University where I had the fortune of being advised by Ryan O'Donnell on my senior thesis. I am also grateful for the mentorship of Anil Ada, Bernhard Haeupler, Ariel Procaccia, and David Woodruff during my time at CMU.

My research is supported by the Google PhD Fellowship.


Publications

High-girth near-Ramanujan graphs with lossy vertex expansion [pdf]
Theo McKenzie, Sidhanth Mohanty
Manuscript

Local Statistics, Semidefinite Programming, and Community Detection [pdf]
Jess Banks, Sidhanth Mohanty, Prasad Raghavendra
SODA 2021

List Decodable Mean Estimation in Nearly Linear Time [pdf]
Yeshwanth Cherapanamjeri, Sidhanth Mohanty, Morris Yau
FOCS 2020

Lifting Sum-of-Squares Lower Bounds: Degree-2 to Degree-4 [pdf]
Sidhanth Mohanty, Prasad Raghavendra, Jeff Xu
STOC 2020

Explicit near-Ramanujan graphs of every degree [pdf]
Sidhanth Mohanty, Ryan O'Donnell, Pedro Paredes
STOC 2020
Invited to SICOMP Special Issue for STOC 2020

The SDP value for random two-eigenvalue CSPs [pdf]
Sidhanth Mohanty, Ryan O'Donnell, Pedro Paredes
STACS 2020

Pseudo-deterministic Streaming [pdf]
Shafi Goldwasser, Ofer Grossman, Sidhanth Mohanty, David P. Woodruff
ITCS 2020

High-Dimensional Expanders from Expanders [pdf]
Siqi Liu, Sidhanth Mohanty, Elizabeth Yang
ITCS 2020

X-Ramanujan Graphs [pdf]
Sidhanth Mohanty, Ryan O'Donnell
SODA 2020

On Sketching the q to p norms [pdf]
Aditya Krishnan, Sidhanth Mohanty, David P. Woodruff
APPROX 2018

Algorithms for Noisy Broadcast with Erasures [pdf, slides]
Ofer Grossman, Bernhard Haeupler, Sidhanth Mohanty
ICALP 2018