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Zhou Yu

  • About

    • Department: Faculty of Economics and Management
    • Gender: male
    • Post: Deputy Director of FEM
    • Graduate School: East China Normal University
    • Degree: PhD
    • Academic Credentials:
    • Tel: 021-54345058
    • Email: zyu@stat.ecnu.edu.cn
    • Office: Room A1707, Science Building
    • Address: School of Statistics, East China Normal University, 3663 Zhongshan Road(N.), Shanghai, P.R.China
    • PostCode: 200062
    • Fax:

    WorkExperience

    2010-2011, Postdoctoral fellow,  Department of Mathematics, Hong Kong Baptist University

    2011-2013, Lecture, School of Statistics, East China Normal University

    2013-2015, Postdoctoral fellow, Department of Statistics, University of Wisconsin-Madison 

    2013-2016, Associate Professor, School of Statistics, East China Normal University

    2016-          Professor, School of Statistics, East China Normal University


    Education

    2000-2004, Hefei University of Technology, B.S.

    2004-2010, East China Normal University,  Ph.D. 


    Resume

    Other Appointments

    Research Fields

    High-dimensional data analysis

    Statistical machine learning


    Enrollment and Training

    Course

    Survey Methodology

    Selected Topics of Modern Statistical Methods 

    Advanced Mathematical Statistics

    Statistical Learning Theory


    Scientific


    1. NSFC General Program (11971170):  Sufficient Dimension Reduction Based on Model Averaging;

    2. NSFC General Program (11571111):  Multi-Dimensional Dependent Variable Sufficient Dimension Reduction and Multi-Population Sufficient Dimension Reduction;

    3. NSFC Youth Program (11201151):  Hypothesis Testing of High-Dimension Data Based on Sufficient Dimension Reduction. 


    Academic Achievements


    Selected Publications


    (1) Yinfeng Chen, Yuling Jiao, Rui Qiu and Zhou Yu (2024). Deep Nonlinear Sufficient Dimension Reduction. To appear in Annals of Statistics.

     

    (2) Rui Qiu, Shuntuo Xu and Zhou Yu (2024). Neural Networks Meet Random Forests. Journal of the Royal Statistical Society Series B: Statistical Methodology. DOI: 10.1093/jrsssb/qkae038.

     

    (3) Rui Qiu, Zhou Yu and Ruoqing Zhu (2024). Random Forest Weighted Local Fréchet Regression with Random Objects. Journal of Machine Learning Research, 25(107), 1-69.

     

    (4) Jian Huang, Yuling Jiao, Xu Liao ,Jin Liu and Zhou Yu  (2024) Deep Dimension Reduction for Supervised Representtion Learning. IEEE Transactions on Information Theory,  70(5), 3583-3598.

      

    (5) Chao Ying and Zhou Yu (2022) Frechet sufficient Dimension Reduction for Random Objects.  Biometrika, 109(4), 975-992.

     

    (6) Kyongwon Kim, Bing Li, Zhou Yu and Lexin Li (2020) On Post Dimension Reduction Statistical Inference. Annals of Statistics, 48(3), 1567-1592.

      

    (7) Kai Tan, Lei Shi and Zhou Yu (2020). Sparse SIR: Optimal Rates and Adaptive Estimation. Annals of Statistics, 48(1), 64-85.

      

    (8) Zhou Yu, Yuexiao Dong and Jun Shao (2016). On Marginal Sliced Inverse Regression for Ultrahigh Dimensional Model-Free Feature Selection , Annals of Statistics, 44(6), 2594~2623.    

      

    (9) Zhou Yu,Yuexiao Dong and Li-Xing Zhu (2016). Trace Pursuit: A General Framework for Model-Free Variable Selection, Journal of the American Statistical Association, 2016, 111(514), 813~821.   

      

    (10) Zhou Yu, Liping Zhu, Heng Peng and Li-Xing Zhu (2013). Dimension Reduction and Predictor Selection in Semiparametric Models, Biometrika, 100(3), 641~654.    

      

    (11) Zhenghui Feng, Xuerong Meggie Wen, Zhou Yu and Li-Xing Zhu (2013). On Partial Sufficient Dimension Reduction With Applications to Partially Linear Multi-Index Models. Journal of the American Statistical Association, 108(501): 237~246.


    Honor

    Honor:

    1. Shanghai Youth Top Talent;

    2. Shanghai University Distinguished Professor;

    3. Shanghai Youth Science and Technology Rising-Star Program;

      

    Awards:

    1. 2019 Shanghai Natural Science Award;

    2. Second prize of the 10th National Statistical Research Achievement Award (Doctoral Dissertation)