Qingzhao Zhang
Professional Title: Professor
Administrative Position:
Alma Mater: Academy of Mathematics and Systems Science, CAS
Contact Information: 0592-2180502
E-Mail:
Business Address: B503, Economics Building
Office Hours:Monday, 9:30am-11:30am
External Homepage:
Research Papers

Selected Publications:(* corresponding author,#co-first author or alphabetical order)

  1. Li, X., Zhang, S.,  Ren, M.* and Zhang, Q.*(2026) Integrative learning of linear non-Gaussian directed acyclic graphs with application on multisource gene regulatory network analysis. Annals of Applied Statistics, 20(1), 46-67.

  2. Li, J., Zhang, Q. and Ma, S.*(2026) Integrating Genetic and Pathological Imaging Data for Cancer Prognosis with a DNN-based Semiparametric Model. Biometrics, 82(1), ujag045.

  3. Li, Y., Huang, Y., Sheng, Y.* and Zhang, Q.*(2026). Adaptive incorporation of external summary information in the Cox regression under population heterogeneity. Statistics in Medicine, 45(1-2), e70371.

  4. Li, R., Zhang, Q.* and Ma, S.*(2026) Conditional Graphical Model with A Hierarchical Sparse Estimation. Statistics and Computing, 36, 30.

  5. Li, R., Zhang, Q.* and Ma, S.*(2026) Regulation-Incorporated Gene Expression Network-Based Heterogeneity Analysis. Statistica Sinica, 36(1), 373-394. 

  6. Jiang, J., Fang, K., Ma, S. and Zhang, Q.*(2026). Hierarchical structure-guided high-dimensional multi-view clustering. Journal of Multivariate Analysis, 211, 105488.

  7. Li, L., Ma, S. and Zhang, Q.*(2025) Subgroup Analysis of Differential Networks with Latent Variables. Statistics and Computing, 35, 140. 

  8. Chen, Y., Zhang, Q.* and Ma, S.(2025) Local clustering for functional data. Journal of Computational and Graphical Statistics, 34(3), 1075-1090. 

  9. Zhang, Q., Zhou, J. and Ren, M.*(2025) Network embedding-based directed community detection with unknown community number. Journal of Computational and Graphical Statistics, 34(3), 812-823. 

  10. Xu, F., Ma, S., Zhang, Q.* and Xu, Y.*(2025) Robust transfer learning for high-dimensional GLM using γ-divergence in cancer genomics. Statistics in Medicine, 44 (15-17), e70170.

  11. Pu, D., Fang, K., Lan, W.*, Yu, J. and Zhang, Q.* (2025) Reduced Rank Spatio-temporal Models. Journal of Business and Economic Statistics, 43, 98-109.

  12. Chen, Y., Fang, K., Lan, W.*, Tsai, C. and Zhang, Q.* (2025) Community Influence Analysis in Social Networks.Computational Statistics & Data Analysis, 202, 108037.

  13. Pu, D.#, Fang, K.#, Lan, W.*, Yu, J. and Zhang, Q.#(2024) Multivariate Reduced Rank Spatio-temporal Models.Journal of Econometrics, 246(1-2), 105897.

  14. Zhang, X., Zhang, Q. and Fang, K.*(2024) Functional linear model with prior information of subjects' network.Journal of Computational and Graphical Statistics, 33(4), 1150-1159.

  15. Chen, Y., Zhang, Q., Ma, S. and Fang, K.*(2024) Heterogeneity-aware Clustered Distributed Learning for Multi-source Data Analysis. Journal of Machine Learning Research, 25(211),1-60.

  16. Ma, C., Lin, C., Xue, Y., Zhang, S., Zhang, Q. and Ma, S. *(2024). Information-Incorporated Clustering Analysis of Disease Prevalence Trends. Annals of Applied Statistics, 18(2), 1035-1050. 

  17. Fang, K., Lan, W.*, Pu, D. and Zhang, Q.# (2024). Spatial Autoregressive Models with Generalized Spatial Disturbances. Statistica Sinica, 34(2), 1–21. 

  18. Liang, W., Zhang, Q.* and Ma, S* (2024). Hierarchical false discovery rate control for highdimensional survival analysis with interactions.Computational Statistics & Data Analysis,192, 107906.

  19. Liang, W., Zhang, Q.* and Ma, S.*(2023). Locally sparse quantile estimation for a partially functional interaction model.Computational Statistics & Data Analysis, 186, 107782.

  20. 匡南*(2023). SVM40(4), 138–150. 

  21. Zhong, T., Zhang, Q., Huang, J., Wu, M.* and Ma, S.*(2023) Heterogeneity Analysis via Integrating multi-sources high-dimensional data with applications to cancer studies. Statistica Sinica, 33, 729-758

  22. Ren, M., Zhang, Q., Zhang, S., Zhong, T., Huang, J. and Ma, S.*(2022) Hierarchical Cancer Heterogeneity Analysis Using Histopathological Imaging Data. Biometrics, 79(4), 1579–1591.

  23. Ren, M., Zhang, S., Zhang, Q.* and Ma, S.*(2022). Gaussian Graphical Model-based Heterogeneity Analysis via Penalized Fusion. Biometrics, 78(2), 524–535.

  24. Yi, H., Zhang, Q., Lin, C.* and Ma, S.*(2022). Information-incorporated Gaussian Graphical Model for Gene Expression Data. Biometrics, 78(2), 512–523.

  25. Fang, K., Chen, Y., Ma, S. and Zhang, Q.*(2022). Biclustering Analysis of Functionals via Penalized Fusion.Journal of Multivariate Analysis, 189, 104874.

  26. He, B., Zhong, T., Huang, J., Liu, Y., Zhang, Q.* and Ma, S.*(2021). Histopathological Imaging-based Cancer Heterogeneity Analysis via Penalized Fusion with Model Averaging. Biometrics, 77(4), 1397-1408.

  27. Zhang, T., Li, Z., Liu, A. and Zhang, Q.* (2021). Estimation of Partial Derivative Functionals with an Application to Human Mortality Data Analysis. Science China Mathematics, 64(9), 2117–2140.

  28. Zhang, Q., Ma, S. and Huang, Y.*(2021). Promote sign consistency in the joint estimation of precision matrices. Computational Statistics & Data Analysis, 159, 107210.

  29. Lai, P., Wang, F, Zhu, T. and Zhang, Q.*(2021). Model identification and selection for the single-index varying coefficient models. Annals of the Institute of Statistical Mathematics, 73, 457–480.

  30. Wu, M., Zhang, Q. and Ma, S.*(2020). Structured Gene-Environment Interaction Analysis. Biometrics, 76, 23–35.

  31. Fan, X., Fang, K., Ma, S. and Zhang, Q.*(2020). Integrating Approximate Single Factor Graphical Models.Statistics in Medicine, 39, 146–155.

  32. Fan, X., Fang, K., Ma, S., Wang, S. and Zhang, Q.*(2019). Assisted Graphical Model for Gene Expression Data Analysis. Statistics in Medicine, 38, 2364–2380.

  33. Chai, H., Zhang, Q., Huang, J. and Ma, S.*(2019). Inference for Low-Dimensional Covariates in a High-Dimensional Accelerated Failure Time Model. Statistica Sinica, 29, 877–894.

  34. Wu, C., Zhang, Q.#, Jiang, Y. and Ma, S.*(2018). Robust Network-based Analysis of the Associations between (Epi)Genetic Measurements.Journal of Multivariate Analysis, 168,119–130.

  35. Zhang, Q., Duan, X. and Zhou, X.* (2017). A Weighted Wilcoxon estimate for the covariatespecific ROC curve.Science China Mathematics, 60, 1705–1716.

  36. Huang, Y., Zhang, Q.#, Zhang, S., Huang, J. and Ma, S.* (2017) Promoting similarity of sparsity structures in integrative analysis with penalizationJournal of the American Statistical Association, 112, 342–350.

  37. Sun, Z., Chen, F., Zhou, X. and Zhang, Q.* (2017). Improved model checking methods for parametric models with responses missing at random. Journal of Multivariate Analysis, 154,147-161.

  38. Zhang, Q., Zhang, S., Liu, J., Huang, J. and Ma, S.* (2016). Penalized integrative analysis under the accelerated failure time model.Statistica Sinica, 26, 493-508.

  39. Zang, Y., Zhang, S., Li, Q. and Zhang, Q.* (2016). Jackknife empirical likelihood test for high-dimensional regression coefficients. Computational Statistics & Data Analysis, 94, 302-316.

  40. Zhang, T., Zhang, Q. and Wang, Q.* (2014). Model detection for functional polynomial regression.Computational Statistics & Data Analysis, 70, 183-197.

  41. Zhang, Q., Li, D.* and Wang, H. (2013). A note on tail dependence regression.Journal of Multivariate Analysis, 120, 163-172.

  42. Zhang, Q. and Wang, Q.* (2013). Local least absolute relative error estimating approach for partially linear multiplicative model. Statistica Sinica, 23, 1091-1116.