FANG, Xiao

Associate Professor, Department of Statistics, The Chinese University of Hong Kong

Address:
Department of Statistics
The Chinese University of Hong Kong
Shatin, N.T.
Hong Kong
Phone:
+852 3943-5254

Email:
xfang at sta.cuhk.edu.hk

Education

2007.7-2012.4, Ph.D., Statistics, National University of Singapore, supervised by Louis H. Y. Chen and Zhengxiao Wu.
2003.9-2007.7, B.S., Mathematics, Peking University

Positions held

2022.8-present, Associate Professor, The Chinese University of Hong Kong
2024.1-2024.6, Visiting Scholar, Stanford University
2016.8-2022.7, Assistant Professor, The Chinese University of Hong Kong
2014.8-2016.7, Instructor, National University of Singapore
2012.10-2014.7, Postdoctoral Fellow, Stanford University
2012.5-2012.9, Research Fellow, National University of Singapore

Research

My research interests include asymptotic theory in probability and statistics, Stein’s method for distributional approximations, multivariate and high-dimensional central limit theorems, and change-point analysis.

Preprints and submitted papers (available on arXiv)

  1. Normal approximation for exponential random graphs. (with Song-Hao Liu and Qi-Man Shao)
  2. Second-order approximation of exponential random graph models. (with Wen-Yi Ding)
  3. High-dimensional central limit theorems by Stein’s method in the degenerate case. (with Yuta Koike, Song-Hao Liu and Yi-Kun Zhao)
  4. Edgeworth expansion by Stein’s method. (with Song-Hao Liu)
  5. Detection and estimation of local signals. (with David Siegmund)
  6. Multivariate normal approximation by Stein’s method: the concentration inequality approach. (with Louis H. Y. Chen)

Published or accepted papers

  1. Large-dimensional central limit theorem with fourth-moment error bounds on convex sets and balls. (with Yuta Koike) To appear in Annals of Applied Probability.
  2. Sharp high-dimensional central limit theorems for log-concave distributions. (with Yuta Koike) To appear in Annales de l’Institut Henri Poincaré, Probabilités et Statistiques.
  3. High order steady-state diffusion approximations. (with Anton Braverman and J. G. Dai) To appear in Operations Research.
  4. Cramér-type moderate deviation for quadratic forms with a fast rate. (with Song-Hao Liu and Qi-Man Shao) Bernoulli 29 (2023), 2466-2491.
  5. From p-Wasserstein bounds to moderate deviations. (with Yuta Koike) Electronic Journal of Probability 28 (2023), 1-52.
  6. New error bounds in multivariate normal approximations via exchangeable pairs with applications to Wishart matrices and fourth moment theorems. (with Yuta Koike) Annals of Applied Probability 32 (2022), 602-631.
  7. Normal approximation and fourth moment theorems for monochromatic triangles. (with Bhaswar B. Bhattacharya and Han Yan) Random Structures & Algorithms 60 (2022), 25-53.
  8. Arcsine laws for random walks generated from random permutations with applications to genomics. (with Han Liang Gan, Susan Holmes, Haiyan Huang, Erol Peköz, Adrian Röllin, and Wenpin Tang) Journal of Applied Probability 58 (2021), 851-867.
  9. High-dimensional central limit theorems by Stein’s method. (with Yuta Koike) Annals of Applied Probability 31 (2021), 1660-1686.
  10. Segmentation and estimation of change-point models: false positive control and confidence regions. (with Jian Li and David Siegmund) Annals of Statistics 48 (2020), 1615-1647.
  11. A refined Cramér-type moderate deviation for sums of local statistics. (with Li Luo and Qi-Man Shao) Bernoulli 26 (2020), 2319-2352.
  12. Wasserstein-2 bounds in normal approximation under local dependence. Electronic Journal of Probability 24 (2019), 1-14.
  13. Multivariate approximations in Wasserstein distance by Stein’s method and Bismut’s formula. (with Qi-Man Shao and Lihu Xu) Probability Theory and Related Fields 174 (2019), 945-979. [Correction]
  14. Limit theorems with rate of convergence under sublinear expectations. (with Shige Peng, Qi-Man Shao and Yongsheng Song) Bernoulli 25 (2019), 2564-2596.
  15. A multivariate CLT for bounded decomposable random vectors with the best known rate. Journal of Theoretical Probability 29 (2016), 1510-1523.
  16. Poisson approximation for two scan statistics with rates of convergence. (with David Siegmund) Annals of Applied Probability 26 (2016), 2384-2418.
  17. Rates of convergence for multivariate normal approximation with applications to dense graphs and doubly indexed permutation statistics. (with Adrian Röllin) Bernoulli 21 (2015), 2157-2189.
  18. On the error bound in a combinatorial central limit theorem. (with Louis H. Y. Chen) Bernoulli 21 (2015), 335-359.
  19. A universal error bound in the CLT for counting monochromatic edges in uniformly colored graphs. Electronic Communications in Probability 20 (2015), 1-6.
  20. Discretized normal approximation by Stein’s method. Bernoulli 20 (2014), 1404-1431.
  21. Moderate deviations in Poisson approximation: a first attempt. (with Louis H. Y. Chen and Qi-Man Shao) Statistica Sinica 23 (2013), 1523-1540.
  22. From Stein identities to moderate deviations. (with Louis H. Y. Chen and Qi-Man Shao) Annals of Probability 41 (2013), 262-293.

Teaching

STAT3007 Introduction to Stochastic Processes, CUHK, fall 2023.
STAT5005 Advanced Probability Theory, CUHK, fall 2018-2023.
STAT2102 Basic Statistical Concepts and Methods II, CUHK, spring 2017-2023.
STAT3210 Statistical Techniques in Life Sciences, CUHK, fall 2016 and 2017.
ST4232 Nonparametric Statistics, NUS, spring 2016.
ST5207 Nonparametric Regression, NUS, fall 2015.
ST5218 Advanced Statistical Methods in Finance, NUS, spring 2015.
ST5221 Probability and Stochastic Processes, NUS, fall 2014.

Grants

2024.1-2026.12 Hong Kong RGC GRF 14303423
2023.1-2025.12 Hong Kong RGC GRF 14304822
2021.9-2024.8, Hong Kong RGC GRF 14305821
2019.1-2021.12, Hong Kong RGC GRF 14302418
2018.1-2020.12, Hong Kong RGC ECS 24301617
2017.1-, CUHK Direct Grants
2016.8-2022.7, CUHK Start-up Grant

Professional Services

Invited reviewer for Mathematical Reviews; referee for Ann. Appl. Probab., Ann. Probab., Ann. Statist., Bernoulli, J. R. Stat. Soc. Ser. B, etc.

Updated in April 2024.