On Sketching the q to p Norms. - Aditya Krishnan 001; Sidhanth Mohanty; David P. Woodruff (APPROX-RANDOM, 2018)

Algorithms for Noisy Broadcast with Erasures. - Ofer Grossman; Bernhard Haeupler; Sidhanth Mohanty (ICALP, 2018)

Algorithms for Noisy Broadcast under Erasures. - Ofer Grossman; Bernhard Haeupler; Sidhanth Mohanty (CoRR, 2018)

X-Ramanujan Graphs. - Sidhanth Mohanty; Ryan O'Donnell (CoRR, 2019)

Pseudo-deterministic Streaming. - Shafi Goldwasser; Ofer Grossman; Sidhanth Mohanty; David P. Woodruff (Electron. Colloquium Comput. Complex., 2019)

List Decodable Mean Estimation in Nearly Linear Time. - Yeshwanth Cherapanamjeri; Sidhanth Mohanty; Morris Yau (FOCS, 2020)

High-Dimensional Expanders from Expanders. - Siqi Liu 005; Sidhanth Mohanty; Elizabeth Yang (ITCS, 2020)

X-Ramanujan graphs. - Sidhanth Mohanty; Ryan O'Donnell (SODA, 2020)

The SDP Value for Random Two-Eigenvalue CSPs. - Sidhanth Mohanty; Ryan O'Donnell; Pedro Paredes 002 (STACS, 2020)

Lifting sum-of-squares lower bounds: degree-2 to degree-4. - Sidhanth Mohanty; Prasad Raghavendra; Jeff Xu (STOC, 2020)

On statistical inference when fixed points of belief propagation are unstable. - Siqi Liu 005; Sidhanth Mohanty; Prasad Raghavendra (FOCS, 2021)

High-Girth Near-Ramanujan Graphs with Lossy Vertex Expansion. - Theo McKenzie; Sidhanth Mohanty (ICALP, 2021)

Local Statistics, Semidefinite Programming, and Community Detection. - Jess Banks; Sidhanth Mohanty; Prasad Raghavendra (SODA, 2021)

Computational phase transitions in sparse planted problems? - Siqi Liu 005; Sidhanth Mohanty; Prasad Raghavendra (CoRR, 2021)

Many nodal domains in random regular graphs. - Shirshendu Ganguly; Theo McKenzie; Sidhanth Mohanty; Nikhil Srivastava (CoRR, 2021)

Certifying Solution Geometry in Random CSPs: Counts, Clusters and Balance. - Jun-Ting Hsieh; Sidhanth Mohanty; Jeff Xu (CCC, 2022)

Testing thresholds for high-dimensional sparse random geometric graphs. - Siqi Liu 005; Sidhanth Mohanty; Tselil Schramm; Elizabeth Yang (STOC, 2022)

Explicit Near-Ramanujan Graphs of Every Degree. - Sidhanth Mohanty; Ryan O'Donnell; Pedro Paredes 002 (SIAM J. Comput., 2022)

A simple and sharper proof of the hypergraph Moore bound. - Jun-Ting Hsieh; Pravesh K. Kothari; Sidhanth Mohanty (SODA, 2023)

Local and Global Expansion in Random Geometric Graphs. - Siqi Liu 005; Sidhanth Mohanty; Tselil Schramm; Elizabeth Yang (STOC, 2023)

Phase Transitions in Inference - Sidhanth Mohanty (2023)

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

Fast Mixing in Sparse Random Ising Models. - Kuikui Liu; Sidhanth Mohanty; Amit Rajaraman; David X. Wu (FOCS, 2024)

Explicit Two-Sided Unique-Neighbor Expanders. - Jun-Ting Hsieh; Theo McKenzie; Sidhanth Mohanty; Pedro Paredes 002 (STOC, 2024)

Robust Recovery for Stochastic Block Models, Simplified and Generalized. - Sidhanth Mohanty; Prasad Raghavendra; David X. Wu (STOC, 2024)

Small Even Covers, Locally Decodable Codes and Restricted Subgraphs of Edge-Colored Kikuchi Graphs. - Jun-Ting Hsieh; Pravesh K. Kothari; Sidhanth Mohanty; David Munhá Correia; Benny Sudakov (CoRR, 2024)

Explicit Two-Sided Vertex Expanders beyond the Spectral Barrier. - Jun-Ting Hsieh; Ting-Chun Lin; Sidhanth Mohanty; Ryan O'Donnell; Rachel Yun Zhang (STOC, 2025)

Weak Poincaré Inequalities, Simulated Annealing, and Sampling from Spherical Spin Glasses. - Brice Huang; Sidhanth Mohanty; Amit Rajaraman; David X. Wu (STOC, 2025)

Explicit Lossless Vertex Expanders. - Jun-Ting Hsieh; Alexander Lubotzky; Sidhanth Mohanty; Assaf Reiner; Rachel Yun Zhang (CoRR, 2025)

Sparsifying Cayley Graphs on Every Group. - Jun-Ting Hsieh; Daniel Z. Lee; Sidhanth Mohanty; Aaron Putterman; Rachel Yun Zhang (CoRR, 2025)