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“The sexiest job in the next ten years will be statisticians,” Google's chief economist Hal Varian kept saying. In 2009, we couldn’t have known just how right he was about to become – with one tiny difference: they’re called data scientists now. And they’re about to take over the world... I am very fortunate to live in exciting times and become one of them!

I like to think about problems from both the applied and theoretical perspectives. I am particularly fascinated by effective strategies, fast algorithms and the beautiful theories , that are inspired by and can inform practical applications.

Research Interests

• • High-Dimensional Statistical Learning;

  • Large Scale Statistical Computation;

  • Nonparmetric and Semiparametric Modeling;

  • Time Series and Quantitative Finance;

  • Survival Analysis and Public Health;

  • Artificial Intelligence.

Selected Publications

• • Guo, S. and Qiao, X. (2023). On Consistency and Sparsity for High-Dimensional Functional Time Series with an Application to Autoregressions. Bernoulli, 29(1), 451-472.

  • Ma, Y., Guo, S. and Wang, H. (2023). Sparse Spatio-Temporal Autoregressions by Profiling and Bagging. Journal of Econometrics, Vol 232, Issue 1, 132-147.

  • Chen, C., Guo, S. and Qiao, X. (2022). Functional linear regression: Dependence and Error Contamination. Journal of Business and Economic Statistics, Vol 40, No. 1, 444-457. `

  • Guo, S., Han, Y., and Wang, Q. (2021). Better Nonparametric Confidence Intervals via Robust Bias Correction for Quantile Regression. Stat., Vol 10, Issue 1, e370.

  • Qiao, X., Qian, C., James, G. and Guo, S. (2020). Doubly Functional Graphical Models in High Dimensions. Biometrika. Vol 107, Issue 2, 415-431.

  • Guo, S., Li, D. and Li, M. (2019). Strict stationarity testing and GLAD estimation for double autoregressive models. Journal of Econometrics, Vol 211, Issue 2, 319-337 .

  • Qiao, X., Guo, S. and James, G. (2019). Functional Graphical Models. Journal of the American Statistical Association, Vol 114, 525, 211-222.

  • Guo, S., Box, J., and Zhang, W. (2017). A dynamic structure for high dimensional covariance matrices and its application in portfolio allocation. Journal of the American Statistical Association, 517, V112, 235-253. [online]

  • Guo, S., Wang, Y. and Yao, Q. (2016). High dimensional and banded vector autoregressions. Biometrika, 103, 889-903. [online]

  • Guo, S. and Zeng, D.(2014). An overview of semiparametric models in survival analysis. Journal of Statistical Planning and Inference , V151-152, 1-16. [online]

  • Fan, J., Guo, S. and Hao, N. (2012). Variance estimation using refitted cross-validation in ultrahigh dimensional regression. Journal of the Royal Statistical Society, Series B , 74,37-65. [online]

  • Chen, K., Guo, S., Lin, Y. and Ying, Z. (2010). Least absolute relative error estimation. Journal of the American Statistical Association , 105, 1104-1112. [online]

  • Chen, K., Guo, S., Sun, L. and Wang, J. L. (2010). Global partial likelihood for nonparametric proportional hazards model. Journal of the American Statistical Association , 105, 750-760. [online]

Recent News

• • Fang, Q., Guo, S. and Qiao, X. (2022). Adaptive Thresholding of High Dimensional Covariance Function. Acceptable after Minor Revision in Journal of American Statistical Association.

Upcoming Trips

Past Trips

• Invited talk at the 4th Institute of Mathematical Statistics Asia Pacific Rim Meeting, Chinese University of Hong Kong, Hong Kong, June 2016

• Invited talk at Symposium on Financial Engineering and Risk Management (FERM 2016), Sun Yat-Sen University, Guang Zhou, China, June 2016

• Invited talk at the 9th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2016), Spain, 9-11 December 2016.

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