Weichi Wu Associate Professor

Research Areas: time series, change point analysis, M estimation, statistical network analysis

Office: Room 212-C, Weiqing Building, Tsinghua University

Phone: +86-10-62772725

Email: wuweichi@tsinghua.edu.cn

  • 2020.12-Present Associate Professor (Tenure Track) Department of Industrial Engineering, Center for Statistical Science, Tsinghua University, China.
  • 2018.12-2020.12  Assistant Professor,Center for Statistical Science and Department of Industrial Engineering,Tsinghua University, China.
  • 2017.10-2018.12  Research Associate Institute of Statistics, Department of Mathematics,Ruhr University Bochum, Germany.Research Mentor: Prof. Holger Dette
  • 2015.07-2017.07 Research Associate Department of Statistical Science, Big Data Institute, University College London, UK. Research Mentor: Prof. Patrick Wolfe & Prof. Sofia Olhede

  • 2010-2015  University of Toronto, Canada  Ph.D. in Statistics, Supervisor: Prof. Zhou Zhou
  • 2008-2010  Columbia University in the City of New York, USA M.A. in Statistics
  • 2004-2008 Peking University, China B.S. in Physics

  • Dette, H., & Wu, W* (2024+) Confidence surfaces for the mean of locally stationary functional time series, Statistica Sinica, to appear
  • Wu, W., Olhede, S., & Wolfe, P. (2024+) Tractably Modelling Dependence in Networks Beyond Exchangeability, Bernoulli, to appear
  • Bai,L#.&Wu, W.*(2024+). Difference-based covariance matrix estimate in time series nonparametric regression with applications to specification tests, Biometrika, to appear.
  • Dette, H., & Wu, W., Prediction in locally stationary time series, accepted by Journal of Business & Economic Statistics
  • Dette, H., Dhar, S.S. & Wu,W., Identifying shifts between two regression curves, accepted by Annals of the Institute of Statistical Mathematics.
  • Dette, H., & Wu, W. (2019). Detecting Relevant Changes in the Mean of a Non-stationary Process. The Annals of Statistics, 47(6), 3578–3608.
  • Wu, W., & Zhou, Z. (2018). Gradient-based Structural Change Detection for Nonstationary Time Series M-estimation. The Annals of Statistics, 46(3), 1197-1224.
  • Wu, W., & Zhou, Z. (2018). Simultaneous Quantile Inference for Non-stationary Long-memory Time Series. Bernoulli, 24(4A), 2991-3012.
  • Dette, H., Wu, W., & Zhou, Z. (2018). Change Point Analysis of Correlation in Non-stationary Time Series. Statistica Sinica, 29(2), 611-644.
  • Wu, W., & Zhou, Z. (2017). Nonparametric Inference for Time-varying Coefficient Quantile Regression. Journal of Business & Economic Statistics, 35(1), 98-109.

Invited Academic Presentations 2020
  • Session chair, the 14th International Conference on Computational and Financial Econometrics,UK.
  • The 13th International Conference on Computational and Financial Econometrics, UK.
  • IMS (Institute of Mathematical Statistics)-China International Conference on Statistics and Probability, China.
  • 12th International Conference on Computational and Financial Econometrics, Italy
  • Workshop on Matrix Estimation Meets Statistical Network Analysis:  Extracting lowdimensional structures in high dimension, Oberwolfach  Research Institute for Mathematics, Germany
  • Fudan Data Science Conference, Fudan University, Shanghai, China.
  • IMS (Institute of Mathematical Statistics)-China International Conference on Statistics and Probability, Guang Xi province, China.
  • 1st International Conference on Econometrics and Statistics, Hong Kong University of Science and Technology, HongKong.
  • 10th International Conference on Computational and Financial  Econometrics, Spain.
  • Research Seminar, Department of Mathematics, University of Bristol, UK.
  • Joint Statistics and Econometrics Seminar, LSE, UK. 
  • Joint Seminar, Department of Statistics, TU Dortmund and Department of Mathematics, Ruhr University Bochum, Germany.
  • SPG Group Seminar, Department of Statistics, UCL, UK.
  • Structural Change Detection For Regression Quantile with Non-Stationary Errors, JSM Seattle, USA (contributed talk).