MyUW   


 


Department of Statistics

University of Wisconsin-Madison

1300 University Avenue

Madison, WI 53706


cmzhang at stat dot wisc dot edu

Office: 1155 MSC

Phone: 608-262-0084

Fax: 608-262-0032






        Chunming Zhang

        RESEARCH

        STUDENT

        TEACHING

        PROFESSIONAL ACTIVITY


Position Held:

  • 2010-now: Professor of Statistics, University of Wisconsin-Madison.
  • 2005-2010: Associate Professor of Statistics, University of Wisconsin-Madison.
  • July-August 2001: Research Fellow, Australian National University.
  • 2000-2005: Assistant Professor of Statistics, University of Wisconsin-Madison.

Education:

Research Interests: My research interests encompass statistical learning theory and methods in computational neuroscience, biostatistics, and financial econometrics, as well as the analysis of imaging, spatial, and temporal data. Additionally, my work explores dimension reduction, high-dimensional inference, multiple hypothesis testing, large-scale simultaneous inference, non-parametric and semi-parametric modeling and inference, functional and longitudinal data analysis, robust statistics, and traffic forecasting in transportation.

  • Medical imaging data analysis;
  • Statistical methods for neuroinformatics and bioinformatics;
  • Statistical methods for financial econometrics;
  • Dimension reduction and high-dimensional inference;
  • Multiple testing; large-scale simultaneous inference and applications;
  • Non- and semi-parametric modeling & inference;
  • Functional & longitudinal data analysis;
  • Robust statistics;
  • Traffic forecasting in transportation

Selected Publications (in Research): (Co-authors noted as (s) for students and (a) for the thesis advisor)

  1. Fan, N.(s), Zhang, C.M., and Zhang, Z.J. (2024). "Dynamic modeling via autoregressive conditional GB2 for cross-sectional maxima of financial time series data," Journal of Business & Economic Statistics, accepted. (This paper focuses on financial time series data.)
  2. Zhang, C.M., Gao, M.(s), and Jia, S.J.(s) (2024). "DAG-informed structure learning from multi-dimensional point processes," Journal of Machine Learning Research, 25(352):1-56. (This paper focuses on neuron spike train data.)
  3. Gao, M.(s), Zhang, C.M., and Zhou, J. (2024). "Learning network-structured dependence from non-stationary multivariate point process data," IEEE Transactions on Information Theory, 70(8):5935-5968. (This paper focuses on neuron spike train data.)
  4. Zhang, C.M., Zhu, L.X., and Shen, Y.B.(s) (2023). "Robust estimation in regression and classification methods for large-dimensional data," Machine Learning, 112(9):3361-3411. [MATLAB codes available on GitHub] (This paper focuses on the classification of lymphoma and colon cancer data.)
  5. Guo, R.S.(s), Zhang, C.M., and Zhang, Z.J. (2020). "Maximum Independent Component Analysis with application to EEG data," Statistical Science, 35(1):145-157. (Special Issue on Statistics and Science, with the Guest Editor David Siegmund). (This paper focuses on brain EEG data.)
  6. Liu, J.(s), Zhang, C.M., and Page, D. (2016). "Multiple testing under dependence via graphical models," Annals of Applied Statistics, 10(3):1699-1724. (This paper focuses on GWAS on breast cancer.)
  7. Zhang, C.M., Chai, Y.(s), Guo, X.(s), Gao, M.(s), Devilbiss, D.M., and Zhang, Z. (2016). "Statistical learning of neuronal functional connectivity," Technometrics, 58(3):350-359. (Special issue on big data) [MATLAB codes available on GitHub] (This paper focuses on neuron spike train data.)
  8. Du, L.(s) and Zhang, C.M. (2014). "Single-index modulated multiple testing," Annals of Statistics, 42(4):1262-1311. (This paper focuses on prostate cancer data.)
  9. Yu, T.(s), Zhang, C.M., Alexander, A.L., and Davidson, R.J. (2013). "Local tests for identifying anisotropic diffusion areas in human brain with DTI," Annals of Applied Statistics, 7(1):201-225. (This paper focuses on brain Diffusion Tensor Imaging data.)
  10. Zhang, C.M., Fan, J.(a), and Yu, T.(s) (2011). "Multiple testing via FDRL for large-scale imaging data," Annals of Statistics, 39(1):613-642. (This paper focuses on brain fMRI data.)
  11. Zhang, C.M., Jiang, Y.(s), and Chai, Y.(s) (2010). "Penalized Bregman divergence for large-dimensional regression and classification," Biometrika, 97(3):551-566. (This paper focuses on cardiac arrhythmia data.)
  12. Zhang, C.M. and Yu, T.(s) (2008). "Semiparametric detection of significant activation for brain fMRI," Annals of Statistics, 36(4):1693-1725. (This paper focuses on brain fMRI data.)
  13. Hall, P., Minnotte, M.C., and Zhang, C.M. (2004). "Bump hunting with non-Gaussian kernels," Annals of Statistics, 32(5):2124-2141.
  14. Zhang, C.M. (2003). "Calibrating the degrees of freedom for automatic data smoothing and effective curve checking," Journal of the American Statistical Association, 98(463):609-628.
  15. Fan, J.(a) and Zhang, C.M. (2003). "A reexamination of diffusion estimators with applications to financial model validation," Journal of the American Statistical Association, 98(461):118-134. (This paper focuses on financial time series data.)
  16. Fan, J.(a), Zhang, C.M., and Zhang, Jian (2001). "Generalized likelihood ratio statistics and Wilks phenomenon," Annals of Statistics, 29(1):153-193. (correction, Annals of Statistics, 2002, 30(6):1811-1811.)

Professional Service:

 Editorial Boards:

  • Associate Editor for Annals of Statistics (2007-2009; 2019-2021);
  • Associate Editor for Journal of the American Statistical Association (2011-2013; 2014-2017; 2023-);
  • Associate Editor for Journal of Statistical Planning and Inference (2012-2018);
  • Associate Editor for Journal of Data Science (2020-);
  • Associate Editor for The New England Journal of Statistics in Data Science (2020-)
  • Guest Associate Editor for Statistica Sinica (2005)
 Statistical Society:
  • Awards Committee (2023-2025), International Chinese Statistical Association.
  • Chair (2022), ICSA Award Committee, International Chinese Statistical Association.
  • Chair-Elect (2022) and Chair (2023), Section on Nonparametric Statistics, American Statistical Association.
  • Program Co-Chair, Scientific Committee for the 2019 IMS-China International Conference on Statistics and Probability, July 6-10, 2019, Dalian, China.
  • Publication Committee (2015-2017), International Chinese Statistical Association.
  • Program Committee (2014-2015), 2015 Joint Statistical Meetings, Representative for Section on Nonparametric Statistics, American Statistical Association.
  • Program Chair-Elect (2014) and Program Chair (2015), Section on Nonparametric Statistics, American Statistical Association.
  • Award Committee, Student Paper Competition (December 2013-January 2014), for JSM 2014 Boston, Section on Statistics in Imaging, American Statistical Association.
  • Charting Committee, The International Society for NonParametric Statistics (ISNPS) (2012-2015).
  • Board of Directors (2009-2011), International Chinese Statistical Association.
  • Committee on Nominations (August 2009-August 2010), Institute of Mathematical Statistics.

Teaching: STAT-610 (Spring 2025); STAT-609 (Fall 2024); STAT-351 (Spring 2024)

  • STAT-351 (Introductory Nonparametric Statistics).
  • STAT-609 (Mathematical Statistics I).
  • STAT-610 (Mathematical Statistics II).
  • STAT-732 (Large Sample Theory of Statistical Inference)
  • STAT-809 (Non-Parametric Statistics).
 
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