Basic Information:
Tong Wang is an Assistant Professor of the School of Statistics and Data Science at Southeast University. She studied in the Department of Applied Statistics, School of Mathematics, Sun Yat-sen University from 2014 to 2019 and obtained a Bachelor's Degree. She then studied in the Department of Statistics, Faculty of Science, The Chinese University of Hong Kong from 2019 to 2023 and obtained a Doctoral Degree. From September 2023 to August 2025, she served as a Postdoctoral Researcher in the Department of Biostatistics, Yale School of Public Health, Yale University, USA, and from October 2025 to January 2026, she served as a Postdoctoral Researcher in the Department of Industrial Engineering and Management, National University of Singapore.
Research area:
Her main research interests include generative learning, deep learning, semi-supervised learning, and nonparametric regression.
Selected Papers:
[1] Song, S.*, Wang, T.*, Shen, G., Lin, Y., & Huang, J. 2025. Wasserstein generative regression. Journal of the Royal Statistical Society Series B: Statistical Methodology, qkaf053.
[2] Liu, X.*, Wang, T.*, Lin, Y., & Wang, Z. 2025. Semi-supervised inference for the high-dimensional quantile regression. Science China Mathematics, 1-30.
[3] Wang, T., Tang, W., Lin, Y., & Su, W. (2023). Semi‐supervised inference for nonparametric logistic regression. Statistics in Medicine, 42(15), 2573-2589.
