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.
I am generally interested in algorithms, probability, and combinatorics. Most recently, I have been
trying to analyze simple local algorithms for inference problems.
If you happen to encounter any of my work, feel free to reach out:
questions and feedback are highly appreciated!

My undergraduate education was at Carnegie Mellon University where I was lucky to be advised by
Ryan O'Donnell. 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.

## PublicationsExplicit two-sided unique-neighbor expanders
[pdf]
Jun-Ting Hsieh, Theo McKenzie, Sidhanth Mohanty, Pedro Paredes Manuscript Local and global expansion in random geometric graphs
[pdf]
Siqi Liu, Sidhanth Mohanty, Tselil Schramm, Elizabeth Yang STOC 2023 A simple and sharper proof of the hypergraph Moore bound
[pdf]
Jun-Ting Hsieh, Pravesh K. Kothari, Sidhanth Mohanty SODA 2023 Testing thresholds for high-dimensional sparse random geometric graphs
[pdf]
Siqi Liu, Sidhanth Mohanty, Tselil Schramm, Elizabeth Yang STOC 2022 Invited to SICOMP Special Issue for STOC 2022
Many nodal domains in random regular graphs
[pdf]
Shirshendu Ganguly, Theo McKenzie, Sidhanth Mohanty, Nikhil Srivastava Communications in Mathematical Physics, to appear Certifying solution geometry in random CSPs: counts, clusters and balance
[pdf]
Jun-Ting Hsieh, Sidhanth Mohanty, Jeff Xu CCC 2022 On statistical inference when fixed points of belief propagation are unstable
[pdf]
Siqi Liu, Sidhanth Mohanty, Prasad Raghavendra FOCS 2021 High-girth near-Ramanujan graphs with lossy vertex expansion
[pdf]
Theo McKenzie, Sidhanth Mohanty ICALP 2021 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 SIAM Journal on Computing 2021 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 |
## Other expositionLocal-to-global theorems for high-dimensional expansion
[pdf] |