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.
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.
To appear in 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.