Brief CV: Zhaoxing Gao

Education

• Ph.D in Mathematics (Statistics), Hong Kong University of Science and Technology, Hong Kong, China, 2016

• B.S. in Mathematics, Sichuan University, China, 2012

Work experience

• July 2024-now: Professor of Statistics
  • University of Electronic Science and Technology of China
• July 2021-June 2024: ZJU100 Young Professor
  • Center for Data Science, Zhejiang University
• Aug 2019-July 2021: Assistant Professor of Statistics
  • Lehigh University, USA
• May 2017-Aug 2019: Post-Doc
  • University of Chicago Booth School of Business, USA
  • Mentor: Professor Qiwei Yao
• Sep 2016-April 2017: Post-Doc
  • London School of Economics and Political Science, UK
  • Mentor: Professor Ruey Tsay

Publications

1. Fang, P., Gao, Z., and Tsay, R.S. (2025+). Determination Of The Effective Cointegration Rank In High-dimensional Time-series Predictive Regressions. Journal of Business & Economic Statistics. Forthcoming.
2. Jiang, H., Shen, B., Li, Yu. and Gao, Z. (2025+). Regularized Estimation of High-Dimensional Matrix-Variate Autoregressive Models. Statistica Sinica. Forthcoming. [Link]
3. Gao, Z., and Tsay, R.S. (2025+). Denoising and Multilinear Projected-Estimation of High-Dimensional Matrix-Variate Factor Time Series. IEEE Transactions on Information Theory. Forthcoming. [Link]
4. Gao, Z., and Tsay, R.S. (2024+). Supervised Dynamic PCA: Linear Dynamic Forecasting with Many Predictors. Journal of the American Statistical Association. Forthcoming. [Link]
5. Gao, Z., and Tsay, R.S. (2023). Divide-and-Conquer: A Distributed Hierarchical Factor Approach to Modeling Large-Scale Time Series Data. Journal of the American Statistical Association, 118(544), 2698-2711. [Link]
6. Gao, Z., Mi, Z., and Ling, S. (2023). Testing threshold effect in single-index models. Statistics and Its Interface, 16(1), 43-56. [Link]
7. Gao, Z. and Tsay, R. S. (2023). A two-way transformed factor model for matrix-variate time series. Econometrics and Statistics, 27, 83--101. [Link]
8. Gao, Z. and Tsay, R. S. (2022). Modeling high-dimensional time series: a factor model with dynamically dependent factors and diverging eigenvalues. Journal of the American Statistical Association, 117(539), 1398-1414. [Link]
9. Gao, Z. and Tsay, R. S. (2021). Modeling high-dimensional unit-root time series. International Journal of Forecasting， 37(4), 1535-1555.[Link]
10. Gao, Z., Ma, Y., Wang, H. and Yao, Q. (2019). Banded spatio-temporal autoregressions. Journal of Econometrics, 208(1), 211–230. [Link]
11. Gao, Z. and Tsay, R. S. (2019). A structural-factor approach for modeling high-dimensional time series and space-time data. Journal of Time Series Analysis, 40, 343–362. [Link]
12. Gao, Z., and Ling, S. (2019). Statistical inference for structurally changed threshold autoregressive models. Statistica Sinica, 29(4), 1803–1829. [Link]
13. Gao, Z., Ling, S., and Tong, H. (2018). Tests for TAR models vs. STAR models–a separate family of hypotheses approach. Statistica Sinica, 28(4), 2857–2883. [Link]
14. Wu, Z.(指导学生), Chen, X., and Gao, Z. (2023). Bayesian Non-parametric Method for Decision Support: Forecasting Online Product Sales. Decision Support Systems, 174, 114019 [Link]
15. Fang, P.(指导学生), Gao, Z.(通讯), and Tsay, R.S. (2023). Supervised Kernel Principal Component Analysis for Forecasting. Finance Research Letters, 58, 104292 [Link]

Talks

• Speaker, Recent Advances in Time Series Analysis, Chicago, USA, May 2023

• Speaker, Tsinghua Forum for Yong Statisticians, Beijing, China, Oct. 2021

• Speaker, Joint Statistical Meetings, Denver, Colorado, USA, July, 2019

• Speaker, Econometrics and Statistics Lunch Seminar, University of Chicago Booth School of Business, Chicago, USA, Mar, 2018

• Participant, 2017 NBER-NSF Time Series Conference, Kellogg School of Management, Northwestern University, USA, Sep,2017

• Participant, Fourth Economic Networks and Finance Conference, LSE, UK, Dec 2016.

• Invited speaker, Complex Time Series Modelling and Forecasting: Dynamic Network, Spatio-temporal Data, and Functional Processes. {\bf Sanya, Hainan, China. Jan, 2018

• Speaker, Time Series and Machine Learning Group Seminar, London School of Economics, London, UK, Nov, 2016

• Invited speaker, From change-point detection to functional data, in honor of the 60th birthday of Professor Lajos Hovath, Graz University of Technology, Graz, Austria, Oct, 2016

• Invited speaker, Tsinghua-Sanya International Workshop on Time Series Econometrics, Sanya, Hainan, China, Dec, 2015

• Invited speaker, CRiSM Workshop: Non-likelihood Based Statistical Modelling. {\bf The University of Warwick, Coventry, UK, Sep, 2015

• Invited speaker, 5th Annual IMS Sponsored Workshop in Finance, Insurance, Probability and Statistics, Rutgers University, USA, June,2015

Teaching

• Instructor–Zhejiang University
  • Time Series Analysis for Management Science, Fall, 08/2021–Now
• Instructor–Lehigh University
  • MATH 231 Probability and Statistics 08/2019–12/2019
  • MATH 338 Linear Models In Statistics 01/2020—05/2020
• Teaching Assistant–University of Chicago Booth School of Business
  • Business 41914 (MBA\&PhD): Multivariate Time Series Analysis 03/2019–6/2019
• Co-instructor–London School of Economics Winter 2016
  • ST 425 Statistical Inference: Principles, Methods and Computation 09/2016–12/2016
• Teaching Assistant–Hong Kong University of Science and Technology 2013–2016
  • MATH 4824A Mathematical Models in Economics and Finance Spring 2013–2014
  • MATH 2421 Probability Fall 2014–2015
  • MATH 1014 Calculus Spring 2014–2015
  • MATH 4423 Nonparametric Statistics Fall 2015–2016
  • MATH 4425 Introductory Time Series Spring 2015–2016

Service

• Associate Editor: Journal of Forecasting, 2023-now