Research Interests
Long memory and nonlinear time series
Spatial statistics
Spectral analysis
Environmental Statistics
Econometrics
Functional data analysis
High dimensional data analysis
Resampling methods
Time series analysis
Applications in atmospheric science, economics, finance and neuroscience
Education
PhD, Statistics, University of Chicago, 2006
Grants
NSF-CMG0724752 (co-PI)
NSF-DMS0804937 (PI)
NSF-DMS1104545 (PI)
NSF-DMS1407037 (PI)
NSF-DMS1607489 (PI)
Research Board at UIUC
ABinBev
Jump
Awards and Honors
The Tjalling C. Koopmans Econometric Theory Prize, 2009 (with Wei Biao Wu)
Arnold O. Beckman Research Award, UIUC 2010 Econometric Theory Multa Scripist Award, 2011.
Centennial Scholar, College of Liberal Arts and Sciences, 2013-2016
Additional Campus Affiliations
Adjunct Professor, Statistics
External Links
Recent Publications
Zhang, Y., Wang, R., & Shao, X. (2025). Adaptive Testing for High-Dimensional Data. Journal of the American Statistical Association. Advance online publication. https://doi.org/10.1080/01621459.2024.2439617
Jiang, F., Gao, H., & Shao, X. (2024). Testing Serial Independence of Object-Valued Time Series. Biometrika, 111(3), 925-944. https://doi.org/10.1093/biomet/asad069
Jiang, F., Zhu, C., & Shao, X. (2024). Two-sample and change-point inference for non-Euclidean valued time series. Electronic Journal of Statistics, 18(1), 848-894. https://doi.org/10.1214/24-EJS2218
Kurisu, D., Kato, K., & Shao, X. (2024). Gaussian Approximation and Spatially Dependent Wild Bootstrap for High-Dimensional Spatial Data. Journal of the American Statistical Association, 119(547), 1820-1832. https://doi.org/10.1080/01621459.2023.2218578
Li, L., Shao, X., & Yu, Z. (2024). A Slicing-Free Perspective to Sufficient Dimension Reduction: Selective Review and Recent Developments. International Statistical Review, 92(3), 355-382. https://doi.org/10.1111/insr.12565