Contact

Email: bmhuang at stanford dot edu

I am a Stanford Science Fellow and NSF postdoc in the Department of Statistics, hosted by Andrea Montanari. I received my PhD in Electrical Engineering and Computer Science at MIT, where I was fortunate to be advised by Guy Bresler and Nike Sun.

I am interested in high-dimensional probability and statistical physics, especially the limits of efficient algorithms in disordered problems.

I will join Yale Statistics and Data Science as an assistant professor in January 2027.

Selected Papers

See my research page for a full list.

• B. Huang and M. Sellke. Strong Low Degree Hardness for Stable Local Optima in Spin Glasses.
  Preprint 2025.

• B. Huang, S. Mohanty, A. Rajaraman, and D. X. Wu. Weak Poincaré Inequalities, Simulated Annealing, and Sampling from Spherical Spin Glasses.
  STOC 2025.

• B. Huang. Capacity Threshold for the Ising Perceptron.
  FOCS 2024. Best Student Paper.

• B. Huang, A. Montanari, and H. T. Pham. Sampling from Spherical Spin Glasses in Total Variation via Algorithmic Stochastic Localization.
  Preprint 2024.

• B. Huang and M. Sellke. A Constructive Proof of the Spherical Parisi Formula.
  Preprint 2023.

• S. Chen, B. Huang, J. Li, A. Liu, and M. Sellke. When Does Adaptivity Help for Quantum State Learning?
  FOCS 2023.

• B. Huang and M. Sellke. Tight Lipschitz Hardness for Optimizing Mean Field Spin Glasses.
  Communications on Pure and Applied Mathematics 78(1) (2025), 60-119.
  Conference version: FOCS 2022.

• G. Bresler and B. Huang. The Algorithmic Phase Transition of Random k-SAT for Low Degree Polynomials.
  FOCS 2021.