![]() | Postdoctoral Researcher, MIT CSAIL Email: sidhanth (at) csail (dot) mit (dot) edu Office: G626 Stata Center |
I am a mathematician/computer scientist, generally interested in theoretical computer science and probability theory. Most recently, I have been interested in mixing times of Markov chains, high-dimensional expansion, random matrix theory, and error-correcting codes. I am currently a postdoc in the Theory of Computation group at MIT, fortunate to be hosted by Sam Hopkins, and supported by FODSI.
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.
I am starting as an Assistant Professor in the Computer Science department at Northwestern University in Fall 2025.
PublicationsExplicit Lossless Vertex Expanders [pdf] Explicit Two‑Sided Vertex Expanders Beyond the Spectral Barrier [pdf] Weak Poincaré Inequalities, Simulated Annealing, and Sampling from Spherical Spin Glasses [pdf] Locally Stationary Distributions: A Framework for Analyzing Slow‑Mixing Markov Chains [pdf] Fast Mixing in Sparse Random Ising Models [pdf] Robust recovery for stochastic block models, simplified and generalized [pdf] Explicit two‑sided unique‑neighbor expanders [pdf] Small Even Covers, Locally Decodable Codes and Restricted Subgraphs of Edge‑Colored Kikuchi Graphs [pdf] Local and global expansion in random geometric graphs [pdf] A simple and sharper proof of the hypergraph Moore bound [pdf] Testing thresholds for high‑dimensional sparse random geometric graphs [pdf] Many nodal domains in random regular graphs [pdf] Certifying solution geometry in random CSPs: counts, clusters and balance [pdf] On statistical inference when fixed points of belief propagation are unstable [pdf] High‑girth near‑Ramanujan graphs with lossy vertex expansion [pdf] Local Statistics, Semidefinite Programming, and Community Detection [pdf] List Decodable Mean Estimation in Nearly Linear Time [pdf] Lifting Sum‑of‑Squares Lower Bounds: Degree‑2 to Degree‑4 [pdf] Explicit near‑Ramanujan graphs of every degree [pdf] The SDP value for random two‑eigenvalue CSPs [pdf] Pseudo‑deterministic Streaming [pdf] High‑Dimensional Expanders from Expanders [pdf] X‑Ramanujan graphs [pdf] On Sketching the q to p norms [pdf] Algorithms for Noisy Broadcast with Erasures [pdf], [slides] | Other expositionLocal-to-global theorems for high-dimensional expansion [pdf] |