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.


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

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

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