Tian-Yi Zhou's Personal Website

Hi, this is Tian-Yi Zhou.

This site is no longer being updated. Please visit my new website at https://tianyizhougt.github.io/.

I am a fourth-year Machine Learning Ph.D. student at Georgia Institute of Technology, where I am fortunate to be advised by Prof. Xiaoming Huo. I study the theoretical aspects of deep learning. My current research interests lie in the intersection of approximation theory and statistical learning theory.

Prior to PhD, I earned my B.Sc. in Statistics with first-class honors at the University of Hong Kong. I was an Overseas Research Fellow in 2019, working with Prof Ming Yuan at Columbia University, New York. I have had the fortune to work with Prof Qiang Fu (UBC), Prof Xin Guo (U Queensland), and Prof Guodong Li (HKU).

My email: tzhou306 [at] gatech [dot] edu

Publications and Preprints

In Submission

Classification of Unbounded Data by Gaussian Mixture Models via deep ReLU Networks [ArXiv]
Tian-Yi Zhou and Xiaoming Huo.
Under review at Journal of Machine Learning Research (JMLR). (2023)

ARC-ACO (Algorithms and Randomness Center) Fellowship at Georgia Tech (2023)

Journal & Conference Proceedings

Gone with the Weed: Incidents of Adolescent Marijuana Use in the United States, 1976-2021 [paper link]
Gu, Jiaxin, Xin Guo, Xiaoxi Liu, Yue Yuan, Yushu Zhu, Minheng Chen, Tian-Yi Zhou, and Qiang Fu
Annals of Epidemiology. (2023)

Learning Ability of Interpolating Deep Convolutional Neural Networks [paper link][ArXiv]
Tian-Yi Zhou and Xiaoming Huo
Applied and Computational Harmonic Analysis (ACHA). (2023)

Second Place, The 13th American Institute of Mathematical Sciences (AIMS) Conference Student Paper Competition (2023)
Selected to present at Association for Women in Mathematics (AWM) Research Symposium (2023)
Runner-up, Alice and John Jarvis Ph.D. student paper competition at Georgia Tech ISyE (2022)

Approximation and non-parametric estimation of functions over high-dimensional spheres via deep ReLU networks [paper link]
Namjoon Suh, Tian-Yi Zhou, and Xiaoming Huo
ICLR 2023.

Modified Poisson regression analysis of grouped and right‐censored counts [paper link]
Qiang Fu, Tian-Yi Zhou, and Xin Guo
Journal of the Royal Statistical Society: Series A (Statistics in Society). (2021)

Education and Experiences

Ph.D. in Machine Learning, Minor in Operations Research (2020 - present)

H. Milton Stewart School of Industrial and Systems Engineering (ISyE), Georgia Institute of Technology

B.Sc. in Statistics, First Class Honour (2016-2020)

Department of Statistics and Actuarial Science, The University of Hong Kong (HKU)

Overseas Research Fellow (2019)

Department of Statistics, Columbia University

Exchange Student (Supported by HKU Worldwide Exchange) (2019)

Department of Statistics, University of California, Los Angeles

Recent and Upcoming Talks

10th International Congress on Industrial and Applied Mathematics (ICIAM)

Waseda University, Tokyo, Japan, 08/2023

Georgia Tech Algorithms & Randomness Center (ARC) Colloquium

Georgia Tech, Atlanta, GA, 09/2023

2023 Association for Women in Mathematics (AWM) Research Symposium

Clark Atlanta University, Atlanta, GA, 09/2023

2023 Cornell Young Researchers Workshop (Poster)

Cornell University, Ithaca, NY, 10/2023

Georgia Tech SIAM student seminar (School of Math)

Georgia Tech, Atlanta, GA, 10/2023

Analysis and Data Science Seminar (Department of Math & Statistics)

SUNY Albany, Albany, NY, 02/2023

SIAM Conference on Parallel Processing for Scientific Computing (PP24)

Baltimore, MD, 03/2023