Yan Zhong

2016 - 2021, Texas A&M University, Department of Statistics, PhD

2014 - 2017, Renmin University of China, School of Statistics, Master

2010 - 2014, Renmin University of China, School of Statistics, Bachelor

From 2021.6, East China Normal University, School of Statistics, Assistant Professor

PhD in Statistics, Assistant Professor at East China Normal University.

TBA

Statistical machine learning; Dimensionality reduction; Network data analysis; Applications of statistical methods in biology and epidemiology.

TBA

*Corresponding Author，Equal Contribution, ^Student

Machine Learning, Statistical Computing:

Xu, Shuntuo^, Zhou Yu*, and Yan Zhong (alphabetical order). On Adaptive Kernel Learning for Nonparametric Regression, Classification and Beyond. IEEE Transactions on Information Theory (2026).

Zhong, Yan, Lei Ma, and Xiaomeng Yan*. Topology-Optimal Multiple Gossip Steps for Decentralized Federated Learning via Gossip Tensor. IEEE Transactions on Neural Networks and Learning Systems (2026).

Li, Gefei^, Riquan Zhang, Qiao Zheng, and Yan Zhong*. Penalized partially linear regression with deep neural networks for high-dimensional learning: G. Li et al. Statistics and Computing 36, no. 2 (2026): 87.

Zheng, Qiao^, Riquan Zhang, and Yan Zhong*. Communication-Effcient Large Precision Matrix Estimation by Distributed Refitted Cross-Validation. Journal of Systems Science and Complexity (2025+).

Zheng, Qiao^, Riquan Zhang, Gefei Li^, and Yan Zhong*. Efficient Distributed Differential Network Estimation. Stat 14, no. 1 (2025): e70049.

Zhong, Yan*, Kejun He, and Gefei Li^. Reduced-Rank Clustered Coefficient Regression for Addressing Multicollinearity in Heterogeneous Coefficient Estimation. Biometrics 80, no. 3 (2024).

(Code: RRCCR: https://github.com/yanzhong07/RRCCR)

Zhong, Yan*, Huiyan Sang, Scott J. Cook, and Paul M. Kellstedt. Sparse spatially clustered coefficient model via adaptive regularization. Computational Statistics & Data Analysis 177 (2023): 107581.

(Code: RSCC: https://github.com/yanzhong07/RSCC)

Zhong, Yan*, and Jianhua Z. Huang. Biclustering via structured regularized matrix decomposition. Statistics and Computing 32, no. 3 (2022): 37.

(Code: BCEL: https://github.com/yanzhong07/BCEL)

Zhong, Yan*, Xiao Huang, Jundong Li, and Xia Hu. Scalable social tie strength measuring. In 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 288-295. IEEE, 2020.

Chang, Xiangyu, Yan Zhong, Yao Wang*, and Shaobo Lin. Unified low-rank matrix estimate via penalized matrix least squares approximation. IEEE Transactions on Neural Networks and Learning Systems 30, no. 2 (2018): 474-485.

Bioinformatics:

Zhong, Yan*, Daniel Osorio, Guanxun Li, Qian Xu, Yongjian Yang, Jianhua Z. Huang, and James J. Cai. scTenifoldNet and scTenifoldKnk: a package suite for single-cell gene regulatory network construction, comparison, and perturbation analysis. Statistical Theory and Related Fields (2025) , 9(4), 357–366.

(R package: scTenifoldKnk: https://cran.r-project.org/web/packages/scTenifoldKnk/index.html)

(R package: scTenifoldNet: https://cran.r-project.org/web/packages/scTenifoldNet/index.html)

Zhong, Yan*, Yuntong Hou^, Yongjian Yang, Xinyue Zheng^, James J Cai*. scPOEM: Robust Co-embedding of Peaks and Genes Revealing Peak-Gene Regulation. Bioinformatics (2025): btaf483.

(R package: scPOEM: https://cran.r-project.org/web/packages/scPOEM/index.html)

(Public Database: https://yanzhong-lab-ecnustat.github.io/web-scPOEM-dataset/)

Zhong, Yan*, Siwei Cui^, Yongjian Yang, and James J. Cai*. Controlled Noise: Evidence of Epigenetic Regulation of Single-Cell Expression Variability. Bioinformatics 40, no. 7 (2024): btae457.

Yang, Yongjian, Guanxun Li, Yan Zhong, Qian Xu, Yu-Te Lin, Cristhian Roman-Vicharra, Robert S. Chapkin*, and James J. Cai*. scTenifoldXct: a semi-supervised method for predicting cell-cell interactions and mapping cellular communication graphs. Cell systems 14, no. 4 (2023): 302-311.

Yang, Yongjian*, Guanxun Li, Yan Zhong, Qian Xu, Bo-Jia Chen, Yu-Te Lin, Robert S. Chapkin, and James J. Cai. Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks. Nucleic Acids Research 51, no. 13 (2023): 6578-6592.

Yang, Yongjian*, Yu-Te Lin, Guanxun Li, Yan Zhong, Qian Xu, and James J. Cai. Interpretable modeling of time-resolved single-cell gene–protein expression with CrossmodalNet. Briefings in Bioinformatics 24, no. 6 (2023): bbad342.

Osorio, Daniel, Yan Zhong, Guanxun Li, Qian Xu, Yongjian Yang, Yanan Tian, Robert S. Chapkin, Jianhua Z. Huang*, and James J. Cai*. scTenifoldKnk: an efficient virtual knockout tool for gene function predictions via single-cell gene regulatory network perturbation. Patterns 3, no. 3 (2022).

(R package: scTenifoldKnk: https://cran.r-project.org/web/packages/scTenifoldKnk/index.html)

Xu, Qian, Guanxun Li, Daniel Osorio, Yan Zhong, Yongjian Yang, Yu-Te Lin, Xiuren Zhang, and James J. Cai*. scInTime: a computational method leveraging single-cell trajectory and gene regulatory networks to identify master regulators of cellular differentiation. Genes 13, no. 2 (2022): 371.

Osorio, Daniel, Yan Zhong, Guanxun Li, Jianhua Z. Huang*, and James J. Cai*. scTenifoldNet: a machine learning workflow for constructing and comparing transcriptome-wide gene regulatory networks from single-cell data. Patterns 1, no. 9 (2020).

(R package: scTenifoldNet: https://cran.r-project.org/web/packages/scTenifoldNet/index.html)

Osorio, Daniel, Xue Yu, Yan Zhong, Guanxun Li, Erchin Serpedin, Jianhua Z. Huang*, and James J. Cai*. Single-cell expression variability implies cell function. Cells 9, no. 1 (2019): 14.

Aviation safety and QAR data analysis

Zhong, Yan, Xiaoyan Lu, Xinbin Zhao, Yi Wang, and Fang Fang*. Landing Tail-Strike Risk Pattern Identification and Prediction Based on Functional QAR Data. Aerospace 13, no. 6 (2026): 553.

Zhong, Yan, Xinyi Peng, Xinyi Xiong, Fang Fang*, and Xinbin Zhao. Identification of Airspeed Safety Envelope for Long Landing. Journal of Aerospace Information Systems (2026): 1-12.

Zhong, Yan*, Tong Liu, Fang Fang, Jia Ge, Bohao Xu, and Xinbin Zhao. Hard Landing Pattern Recognition and Precaution With QAR Data by Functional Data Analysis. IEEE Transactions on Aerospace and Electronic Systems 60, no.4 (2024): 5101-5113.

Other statistical applications

Zhong, Yan, Ami Wang, Rick Aalbers, Killian J McCarthy*, and Ruling Zhang*.Keeping things cordial: Competition, cooperation and coopetition in venture capital syndicates. Journal of Business Research 201 (2025): 115638.

Zhang, Xiao, Yan Zhong, Farid Saad, Karim Sultan Haider, Ahmad Haider, Angela G. Clendenin, and Xiaohui Xu*. Testosterone therapy may reduce prostate cancer risk due to testosterone deficiency at a young age via stabilizing serum testosterone levels. The Aging Male 23, no. 2 (2020): 112-118.

Zhang, Xiao, Yan Zhong, Farid Saad, Karim Haider, Ahmad Haider, and Xiaohui Xu*. Clinically occult prostate cancer cases may distort the effect of testosterone replacement therapy on risk of PCa. World Journal of Urology 37 (2019): 2091-2097.

Zhang, Xiao, Xiaohui Xu*, Yan Zhong, Melinda C. Power, Brandie D. Taylor, and Genny Carrillo. Serum folate levels and urinary arsenic methylation profiles in the US population: NHANES, 2003–2012. Journal of Exposure Science & Environmental Epidemiology 29, no. 3 (2019): 323-334.

Lu, Xiaoling*, Bharatendra Rai, Yan Zhong, and Yuzhu Li. Cluster-based smartphone predictive analytics for application usage and next location prediction. International Journal of Business Intelligence Research (IJBIR) 9, no. 2 (2018): 64-80.

Xu, Xiaohui*, Xiao Zhang, Yan Zhong, Farid Saad, Maria J. Perez-Patron, Karim Haider, and Ahmad Haider. Dynamic patterns of testosterone levels in individuals and risk of prostate cancer among hypogonadal men: a longitudinal study. The Journal of Urology 199, no. 2 (2018): 465-473.

TBA