My research interests lie at the interface of artificial intelligence, theoretical computer science, and information theory. I seek conceptual insights into how contemporary AI systems learn through the lens of computational learning theory.

I am fortunate to be advised by Nathan Srebro.

Some Papers

• Learning single-index models via harmonic decomposition Nirmit Joshi, Hugo Koubbi, Theodor Misiakiewicz, Nathan Srebro

  Preprint

• A Theory of Learning with Autoregressive Chain of Thought Nirmit Joshi, Gal Vardi, Adam Block, Surbhi Goel, Zhiyuan Li, Theodor Misiakiewicz, Nathan Srebro

  COLT 2025

• Community Detection in the Hypergraph SBM: Exact Recovery Given the Similarity Matrix Julia Gaudio, Nirmit Joshi

  COLT 2023