
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
Highgirth nearRamanujan 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 SumofSquares Lower Bounds: Degree2 to Degree4
[pdf]
Sidhanth Mohanty, Prasad Raghavendra,
Jeff Xu
STOC 2020
Explicit nearRamanujan 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 twoeigenvalue CSPs
[pdf]
Sidhanth Mohanty, Ryan O'Donnell,
Pedro Paredes
STACS 2020
Pseudodeterministic Streaming
[pdf]
Shafi Goldwasser,
Ofer Grossman,
Sidhanth Mohanty,
David P. Woodruff
ITCS 2020
HighDimensional Expanders from Expanders
[pdf]
Siqi Liu,
Sidhanth Mohanty, Elizabeth Yang
ITCS 2020
XRamanujan 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