mgm高梅美线路: 师资团队Faculty






· 机器学习: 非参数模型降维,流型结构上的优化,子空间学习

· 数理统计: 低秩回归,高维变量选择,函数型数据分析,时间序列分析

· 应用统计:统计遗传学


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Corresponding authorship is indicated by #

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1. Kejun He, Heng Lian, Shujie Ma, and Jianhua Z. Huang (2018). Dimensionality reduction and variable selection in multivariate varying-coefficient models with a large number of covariates. Journal of the American Statistical Association, 113(522), 746-754.

2. Shiyuan He, Kejun He#, and Jianhua Z. Huang (2022). Improved estimation of high-dimensional additive models using subspace learning. Journal of Computational and Graphical Statistics, 31(3), 866-876.

3. Kejun He, Yifan Wang*, Wei Su*, and Hanfang Yang (2022). A varying-coefficient regression approach to modeling the effects of wind speed on the dispersion of pollutants. Environmental and Ecological Statistics, 29(2), 433-452.

4. Fengyu Zhang*, Ya Zhou*, Kejun He#, and Raymond K. W. Wong (2022). Multivariate varying-coefficient models via tensor decomposition. Statistica Sinica, in press.

5. Tong Wang*, Kejun He, Wei Ma, Dipankar Bandyopadhyay, and Samiran Sinha (2023). Efficient estimation of the generalized odds rate model for clustered current status data. The Canadian Journal of Statistics /La revue canadienne de statistique, 51(4), 1150-1170.

6. Shuoli Chen*, Kejun He#, Shiyuan He, Yang Ni, and Raymond K. W. Wong (2023). Bayesian nonlinear tensor regression with functional fused elastic net prior. Technometrics, 65(4), 524-536.


7. Shiyuan He, Hanxuan Ye*, and Kejun He# (2022). Spline estimation of functional principal components via manifold conjugate gradient algorithm. Statistics and Computing, 32, 106.

8. Shiyuan He, Hanxuan Ye*, and Kejun He# (2023). A unified analysis of multi-task functional linear regression models with manifold constraint and composite quadratic penalty. Journal of Machine Learning Research, 24(291), 1–69.  

9. Shirun Shen*, Huiya Zhou*, Kejun He#, and Lan Zhou (2023). Principal component analysis of two-dimensional functional data with serial correlation. Journal of Agricultural, Biological and Environmental Statistics, in press.

10. Shiyuan He, Jianhua Z. Huang, and Kejun He# (2023). Penalized spline estimation of principal components for sparse functional data: Rates of convergence. Bernoulli, in press.


11. Kejun He# and Jianhua Z. Huang (2016). Asymptotic properties of adaptive group Lasso for sparse reduced rank regression. Stat, 5(1), 251-261.

12. Ya Zhou* and Kejun He# (2021). An improved tensor regression model via location smoothing. Stat, 10(1), 1–15.

13. Ya Zhou*, Raymond K. W. Wong, and Kejun He# (2021). Tensor linear regression: Degeneracy and solution. IEEE Access, 9(1), 7775–7788.

14. Fangting Zhou*, Kejun He, Qiwei Li, Robert S. Chapkin, and Yang Ni (2022). Bayesian biclustering for microbial metagenomic sequencing data via multinomial matrix factorization. Biostatistics, 23(3), 891-909.

15. Fangting Zhou*, Kejun He#, James J. Cai, Laurie A. Davidson, Robert S. Chapkin, and Yang Ni (2022). A unified Bayesian framework for bi-overlapping-clustering multi-omic data via sparse matrix factorization. Statistics in Biosciences, in press.

16. Zhuofan Wang*, Fangting Zhou*, Kejun He#, and Yang Ni (2023). Multi-way overlapping clustering by Bayesian tensor decomposition. Statistics and Its Interface, in press.


17. Qiang Xia, Kejun He, and Cuizhen Niu (2017). A model-adaptive test for parametric single-index time series models. Journal of Time Series Analysis, 38(6), 981-999.

18. Qiang Xia, Heung Wong, Shirun Shen*, and Kejun He# (2021). Factor analysis for high dimensional time series: Consistent estimation and efficient computation. Statistical Analysis and Data Mining, 15(2), 247-263.  


19. Fangting Zhou*, Kejun He#, and Yang Ni (2022). Individualized causal discovery with latent trajectory embedded Bayesian networks. Biometrics, in press.

20. Fangting Zhou*, Kejun He, and Yang Ni (2022). Causal discovery with heterogeneous observational data. Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence (38th UAI), PMLR 180, 2383–2393.

21. Fangting Zhou*, Kejun He, Kunbo Wang, Yanxun Xu, and Yang Ni (2023). Functional Bayesian networks for discovering causality from multivariate functional data. Biometrics, in press.  


22. Canaan M. Whitfield-Cargile, Noah D. Cohen, Kejun He, Ivan Ivanov, Jennifer S. Goldsby, Ana Chamoun-Emanuelli, Brad R. Weeks, Laurie A. Davidson, and Robert S. Chapkin (2017). Non-invasive transcriptome is reflective of tissue-level transcriptome in a model of NSAID enteropathy. Scientific Reports, 7, 14687.

23. Kejun He, Sharon M. Donovan, Ivan Ivanov, Jennifer S. Goldsby, Laurie A. Davidson, and Robert S. Chapkin (2020). Assessing the multivariate relationship between the human infant intestinal exfoliated cell transcriptome (exfoliome) and microbiome in response to diet. Microorganisms, 12(8), 2032.

24. Huijuan Zhou*, Kejun He, Jun Chen, and Xianyang Zhang (2022). LinDA: Linear models for differential abundance analysis of microbiome compositional data. Genome Biology, 23, 95.


· Ya Zhou*, Raymond K. W. Wong, and Kejun He# (2023+). Broadcasted nonparametric tensor regression. Fourth-round revision at Journal of the Royal Statistical Society: Series B (Statistical Methodology).

· Fengyu Zhang* and Kejun He# (2023+). A comparative study of two manifold approaches on low-rank matrix optimization. Major revision at Statistics and Computing.

· Kejun He, Shiyuan He, and Jianhua Z. Huang (2023+). Asymptotically faster estimation of high-dimensional additive models using subspace learning. Under review at Scandinavian Journal of Statistics.

· Linsui Deng*, Kejun He#, Xianyang Zhang (2023+). Powerful spatial multiple testing via borrowing neighboring information. Under review at Statistica Sinica.

· Linsui Deng*, Kejun He#, Xianyang Zhang (2023+). Joint mirror procedure: Controlling false discovery rate for identifying simultaneous signals. Under review at Biometrics.

· Yan Zhong, Kejun He, Gefei Li (2023+). Reduced-rank clustered coefficient regression for addressing multicollinearity in heterogeneous coefficient estimation. Under review at Biometrics.


· 函数型数据的典型相关性分析,主持,中国人民大学,结项

· 非参数模型中的低秩和稀疏结构,主持,国家自然科学基金青年科学基金项目,结项

· 函数型数据分析的积分算子估计-几何降秩模型,参与,国家自然科学基金青年科学基金项目,结项

· 健康大数据分析共享平台建设,参与,国家重点研发计划,结项

· 非参数独立性检验及其应用研究,参与,国家自然科学基金委员会面上项目,在研

· 金融数据合成与智能模型风险监测关键技术及应用,参与,国家重点研发计划,在研