Random matrices &
high-dimensional probability
Spectral limits, extreme eigenvalues, and concentration for random matrices, graphs, and tensors, with an emphasis on sparse and dependent structures.
University of Southern California
Yizhe Zhu朱亦哲
Assistant Professor of Mathematics
I study probability and its connections to statistics, machine learning, and the mathematical foundations of AI.
yizhezhu@usc.eduOffice · KAP 464B
Research
Randomness. Structure. Learning.
Random matrices &
High-dimensional
inference & learning
Spectral and iterative algorithms for community detection and low-rank recovery, and connections between random matrix theory, kernel methods, and deep learning.
Differential privacy &
synthetic data
Statistical and computational foundations of private synthetic data: privacy–utility tradeoffs, adaptation to data structure, and fundamental limits.
Background
About me
I am an Assistant Professor in the Department of Mathematics at the University of Southern California.
From January 2022 to June 2024, I was a Visiting Assistant Professor at UC Irvine and a postdoc in the NSF–Simons Collaboration on the Theoretical Foundations of Deep Learning, mentored by Roman Vershynin. In Fall 2021, I was a Postdoctoral Fellow at the Simons Laufer Mathematical Sciences Institute.
I received my Ph.D. in Mathematics from UC San Diego in 2021, advised by Ioana Dumitriu, and my bachelor’s degree in Mathematics and Applied Mathematics from Shanghai Jiao Tong University.
Community
Seminars
I co-organize these research seminars.