Email: sidhanthm (at) cs (dot) berkeley (dot) edu
Office: 634 Soda Hall
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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] |