\(\dagger\)” indicates joint first authorship.

Submitted works

  1. Zeng, J., Min, K. and Mai, Q. (2023). Robust Sliced Inverse Regression: Optimal Estimation for Heavy-Tailed Data in High Dimensions

  2. \(\dagger\) Chen, L. and Zeng, J. (2023). Dimension Reduction for Extreme Regression via Contour Projection.

  3. Zeng, J., Zhang, X. and Hao, N. (2024). Second-Order Sparse Sufficient Dimension Reduction with Applications to Quadratic Discriminant Analysis.


  1. \(\dagger\) Zeng, J. and Zhang, X. (2024). Tensor and Multimodal Data Analysis. In: Gaw, N., Pardalos, P.M., Gahrooei, M.R. (eds) Multimodal and Tensor Data Analytics for Industrial Systems Improvement. Springer Optimization and Its Applications, vol 211. Springer, Cham.

  2. Zeng, J., Mai, Q. and Zhang, X. (2024). Subspace Estimation with Automatic Dimension and Variable Selection in Sufficient Dimension Reduction. Journal of the American Statistical Association, 119(545), 343–355. [pdf][code]

  3. \(\dagger\) Li, L., Zeng, J. and Zhang, X. (2023). Generalized Liquid Association Analysis for Multimodal Data Integration. Journal of the American Statistical Association, 118(543), 1984–1996. [pdf][code]

  4. Zeng, J., Zhang, X. and Mai, Q. (2023). An Efficient Convex Formulation for Reduced-Rank Linear Discriminant Analysis in High Dimensions. Statistics Sinica, 33, 1249-1270. [pdf][code]

  5. Zeng, J., Wang, W. and Zhang, X. (2021). TRES: An R Package for Tensor Regression and Envelope Algorithms. Journal of Statistical Software, 99, 1-31. [pdf][R package]


My research is partially supported by the National Natural Science Foundation of China (NSFC) Grant 12301365 (2024.01–2026.12). Thank you, NSFC!