部分代表性成果：(* 通讯作者，#共同一作或姓氏字母排列)

1. Chen, Y., Zhang, Q.* and Ma, S.(2024+) Local clustering for functional data. Journal of Computational and Graphical Statistics

2. Zhang, Q., Zhou, J. and Ren, M.*(2024+) Network embedding-based directed community detection with unknown community number. Journal of Computational and Graphical Statistics

3. Li, R., Zhang, Q.* and Ma, S.*(2026) Heterogeneity conditional Gaussian Graphical Models. Statistica Sinica, 36(2). Doi: 10.5705/ss.202023.0109

4. 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.

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

6. 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.

7. 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.

8. 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.

9. 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. 

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

11. 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.

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

13. 张庆昭，陈子怡，方匡南*(2023). 多源异常检测的整合单类SVM方法及应用. 统计研究, 40(4), 138–150. 

14. 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

15. 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.

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

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

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

19. 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.

20. 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.

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

22. 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.

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

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

25. 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.

26. 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.

27. 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.

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

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

30. 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.

31. 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.

32. 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.

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

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

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