Contact Information
725 S. Wright St.
M/C 374
Champaign, IL 61820
Biography
2016 – Present: Full Professor, Department of Statistics, University of Illinois at Urbana-Champaign
2016 – Present: Ph.D. Program Director, Department of Statistics
2006 – 2016: Assistant/Associate Professor, Department of Statistics, University of Illinois at Urbana-Champaign
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
External Links
Recent Publications
He, X., & Shao, X. (2022). A Conversation with Stephen Portnoy. Statistical Science, 37(3), 443-454. https://doi.org/10.1214/21-STS845
Wang, R., Zhu, C., Volgushev, S., & Shao, X. (2022). INFERENCE FOR CHANGE POINTS IN HIGH-DIMENSIONAL DATA VIA SELFNORMALIZATION. Annals of Statistics, 50(2), 781-806. https://doi.org/10.1214/21-AOS2127
Wang, G., Zhu, K., & Shao, X. (2022). Testing for the Martingale Difference Hypothesis in Multivariate Time Series Models. Journal of Business and Economic Statistics, 40(3), 980-994. https://doi.org/10.1080/07350015.2021.1889568
Jiang, F., Zhao, Z., & Shao, X. (Accepted/In press). Modelling the COVID-19 infection trajectory: A piecewise linear quantile trend model. Journal of the Royal Statistical Society. Series B: Statistical Methodology. https://doi.org/10.1111/rssb.12453
Zhang, Y., Wang, R., & Shao, X. (Accepted/In press). Adaptive Inference for Change Points in High-Dimensional Data. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2021.1884562