Sidhanth Mohanty

Postdoctoral Researcher, MIT CSAIL

Email: sidhanth (at) csail (dot) mit (dot) edu

Office: G626 Stata Center

I am a postdoc in the Theory of Computation group at MIT, fortunate to be hosted by Sam Hopkins. I am supported by FODSI. I am generally interested in theoretical computer science and probability theory. Most recently, I have been interested in the algorithms and complexity of inference problems. If you happen to encounter any of my work, feel free to reach out: questions and feedback are highly appreciated!

My PhD education was in the Theory Group at UC Berkeley, under the amazing guidance of Prasad Raghavendra.

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

Publications

Locally Stationary Distributions: A Framework for Analyzing Slow-Mixing Markov Chains [pdf]
Kuikui Liu, Sidhanth Mohanty, Prasad Raghavendra, Amit Rajaraman, David X. Wu
     FOCS 2024

Fast Mixing in Sparse Random Ising Models [pdf]
Kuikui Liu, Sidhanth Mohanty, Amit Rajaraman, David X. Wu
     FOCS 2024

Robust recovery for stochastic block models, simplified and generalized [pdf]
Sidhanth Mohanty, Prasad Raghavendra, David X. Wu
     STOC 2024

Explicit two-sided unique-neighbor expanders [pdf]
Jun-Ting Hsieh, Theo McKenzie, Sidhanth Mohanty, Pedro Paredes
     STOC 2024

Small Even Covers, Locally Decodable Codes and Restricted Subgraphs of Edge-Colored Kikuchi Graphs [pdf]
Jun-Ting Hsieh, Pravesh K. Kothari, Sidhanth Mohanty, David Munhá Correia, Benny Sudakov
     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
     SIAM Journal on Computing 2024
     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 exposition

Local-to-global theorems for high-dimensional expansion [pdf]