Zhao Ren
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Welcome

I am an Assistant Professor of Statistics in Dietrich School of Arts and Sciences at the University of Pittsburgh. Before coming to Pitt, I received Ph.D. in Statistics at Yale University in Aug 2014 under Professor Harrison Zhou's advisorship.

Curriculum Vitae
Research Interests
  • High Dimensional Statistical Inference,
  • Covariance/Precision Matrix Estimation,
  • Graphical Models and Statistical Machine Learning,
  • Nonparametric/High Dimensional Robust Statistics,
  • Nonparametric Function Estimation,
  • Applications in Statistical Genomics.

Publications 
(Names in alphabetical order except for *) 
  • User-Friendly Covariance Estimation for Heavy-Tailed Distributions (with Y. Ke, S. Minsker, Q. Sun and W.X. Zhou ) to appear, Statistical Science [pdf]
  • Minimax Estimation of Large Precision Matrices with Bandable Cholesky Factor* (with Y. Liu (*Student first authorship) ) to appear, Annals of Statistics 2019 [pdf]
  • Tuning-Free Heterogeneous Inference in Massive Networks* (with Y. Kang, Y. Fan and J. Lv (*First authorship) ) to appear, Journal of the American Statistical Association 2019 [pdf][Program]
  • Sparse CCA via Precision Adjusted Iterative Thresholding (with M. Chen, C. Gao and H. Zhou) Proceedings of the Seventh International Congress of Chinese Mathematicians 2019 (Editors: Lizhen Ji, Lo Yang and Shing-Tung Yau) International Press, Volume II:481-534 [pdf]
  • Variable Screening with Multiple Studies* (with T. Ma and G. Tseng (*Student first authorship) ) to appear, Statistica Sinica 2018 [pdf]
  • SILGGM: An Extensive R Package for Efficient Statistical Inference in Large-scale Gene Networks* (with R. Zhang and W. Chen (*Student first authorship; Serve as Correspondence author) ) PLOS Computational Biology 2018 14(8):e1006369 [pdf]
  • Robust Covariance and Scatter Matrix Estimation under Huber's Contamination Model (with M. Chen and C. Gao) Annals of Statistics 2018 46(5):1932-1960 [pdf]
  • Variable Selection for a Categorical Varying-Coefficient Model with Identifications for Determinants of Body Mass Index (with J. Gao, B. Peng and X. Zhang) Annals of Applied Statistics 2017 11(2):1117-1145 [pdf]
  • A General Decision Theory for Huber's ε-Contamination Model (with M. Chen and C. Gao) Electronic Journal of Statistics 2016 10(2):3752-3774 [pdf]
  • Estimating Structured High-Dimensional Covariance and Precision Matrices: Optimal Rates and Adaptive Estimation (with T. Cai and H. Zhou) Electronic Journal of Statistics (with Discussions and Rejoinder) 2016 10(1):1-89 [pdf]
  • FastGGM: An Efficient Algorithm for the Inference of Gaussian Graphical Model in Biological Networks* (with T. Wang, Y. Ding, Z. Fang, Z. Sun, M. MacDonald, R. Sweet, J. Wang and W. Chen (*Co-first authorship) ) PLOS Computational Biology  2016 12(2):e1004755 [pdf]
  • Asymptotically Normal and Efficient Estimation of Covariate-Adjusted Gaussian Graphical Model (with M. Chen, H. Zhao and H. Zhou) Journal of the American Statistical Association  2016 111(513):394-406 [pdf]
  • Minimax Estimation in Sparse Canonical Correlation Analysis (with C. Gao, Z. Ma and H. Zhou) Annals of Statistics  2015 43(5):2168-2197 [pdf]
  • Asymptotic Normality and Optimalities in Estimation of Large Gaussian Graphical Model (with T. Sun, C. Zhang and H. Zhou) Annals of Statistics  2015 43(3):991-1026 [pdf]
  • Optimal Rates of Convergence for Estimating Toeplitz Covariance Matrices (with T. Cai and H. Zhou) Probability Theory and Related Fields  2013, 156(1-2):101-143 [pdf]
  • Discussion : Latent Variable Graphical Model Selection via Convex Optimization (with H. Zhou) Annals of Statistics  2012 40(4):1989-1996 [pdf]

Software
  • FastGGM: A fast algorithm for inference of Gaussian graphical model. [website]
  • SILGGM: Statistical Inference of Large-Scale Gaussian Graphical Model in Gene Networks. [website]

Teaching and Tutoring 

Teaching
  • STAT 1000 Applied Statistical Methods, University of Pittsburgh  (Fall 2016)
  • STAT 1151 Introduction to Probability, University of Pittsburgh  (Fall 2014)
  • STAT 1152 Introduction to Mathematical Statistics, University of Pittsburgh  (Spring 2018)
  • STAT 1631/2630 Intermediate Probability, University of Pittsburgh  (Fall 2017, Fall 2018)
  • STAT 1632/2640 Intermediate Mathematical Statistics, University of Pittsburgh  (Spring 2020)
  • STAT 2631 Theory of Statistics, University of Pittsburgh  (Spring 2020)
  • STAT 2641 Asymptotic Methods in Statistics, University of Pittsburgh  (Spring 2016, Spring 2017, Fall 2018)
  • STAT 2691 Nonparametric Theory, University of Pittsburgh  (Spring 2015, Fall 2017, Fall 2019)
  • STAT 3694 Introduction to High-Dimensional Statistics, University of Pittsburgh  (Fall 2015, Spring 2019)
Tutoring
  • Yale Residential College Math and Science Program for Math and Science Courses (2012-2014)
Picture

Contact
Zhao Ren
Department of Statistics
1812 Wesley W. Posvar Hall
Pittsburgh, PA 15260 
Email: zren (at) pitt (dot) edu