## Yiqiao Zhong
## BioI am a tenure-track assistant professor in the Department of Statistics at the University of Wisconsin–Madison. I started my appointment from Fall 2022. My research is primarily motivated by advances in data science. I enjoy working on modern statistics and machine learning problems, especially deep learning theory and high-dimensional statistics. Very recently, my research interests have centered around analyses of deep learning, especially Large Language Models (LLMs). I am interested in both understanding the theoretical underpinning of LLMs and the practical techniques and concerns such as training and interpretability. Previously, I was a postdoc at Stanford University, as a part of Collaboration on the Theoretical Foundations of Deep Learning, where I was advised by Prof. Andrea Montanari and Prof. David Donoho. Prior to this, I obtained my Ph.D. in 2019 from Princeton University, where I was advised by Prof. Jianqing Fan. I received my B.S. in mathematics from Peking University in 2014. ## Research agenda
In a recent representative paper, I examined various pretrained Transformer models and explored the hidden geometry inside these black-box models. The interesting geometric structure seems to contain many stories to be told!
A recent paper excellently surveys recent progress for the statistical foundations of deep learning. I presented a brief introduction to several key ideas in a lecture for CS762 in October 2022. You can find my slides here.
Self-supervised learning, especially contrastive learning (e.g., A recent paper) Neighborhood embedding and visualization
Spectral methods, PCA and factor models Statistical networks, matrix completion and synchronization problems Nonconvex optimization and SDP relaxation Eigenvector perturbation analysis, entrywise/ bounds
My Google Scholar profile. My research blog. ## Interested in working with me?I am looking for motivated students (statistics, applied math, CS, etc.) to work on any aspect of statistics, machine learning, or applied problems. I'd be happy to chat if you want to learn about my research, start working on a research project, or look for summer internship. The best way to reach out to me is through emails. ## CV |