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个人简介

副教授,博士生导师。2017年获得北京大学光华管理学院商务统计与经济计量系博士学位,之后在美国宾夕法尼亚州立大学从事博士后研究工作。研究成果发表于Journal of Econometrics, Annals of Statistics, Journal of the American Statistical Association等国际顶级期刊。2019年获上海市扬帆计划支持,2022年获国家自然科学基金优秀青年基金项目支持。现任STAT期刊副主编。 Education 2017, Ph.D. in Economics (Statistics), Guanghua School of Management, Peking University 2013, B.S. in Applied Mathematics, Department of Mathematics and Computer Science, Sun-Yat Sen University Editorial Services Associate Editor for STAT, 2022-Present Associate Editor for Journal of Data Science, 2022-Present

研究领域

网络时空数据建模、高维数据建模、统计计算等

近期论文

查看导师最新文章 (温馨提示:请注意重名现象,建议点开原文通过作者单位确认)

Ren, Y., Li, Z., Zhu, X., Gao., Y., Wang, H. (2023) “Distributed Estimation and Inference for Spatial Autoregression Model with Large Scale Networks”, Journal of Econometrics, accepted. (Joint work with my students Yimeng Ren and Zhe Li) Fang, G., Xu, G., Xu, H., Zhu, X., Guan, Y. (2023) “Group Network Hawkes Process”, Journal of the American Statistical Association, accepted Zhu, X., Xu, G., Fan, J. (2023) “Simultaneous Estimation and Group Identification for Network Vector Autoregressive Model with Heterogeneous Nodes”, Journal of Econometrics, accepted Wu, S., Li, Z., Zhu, X. (2023) “A Distributed Community Detection Algorithm for Large Scale Networks Under Stochastic Block Models”, Computational Statistics & Data Analysis, 107794. (Joint work with my students Shihao Wu and Zhe Li) Pan, R., Zhu, Y., Guo, B., Zhu, X., Wang, H. (2023) “A Sequential Addressing Subsampling Method for Massive Data Analysis under Memory Constraint”, IEEE Transactions on Knowledge and Data Engineering. Li, X., Zhu, X., Wang, H. (2023) “Distributed Logistic Regression for Massive Data with Rare Events”, Statistica Sinica, accepted Zhang, J., Cai, B., Zhu, X., Wang, H., Xu, G., Guan, Y. (2023) “Learning Human Activity Patterns using Clustered Point Processes with Active and Inactive States”, Journal of Business & Economic Statistics, 41(2), 388-398. Chen, E., Fan, J., Zhu, X. (2023) “Community Network Auto-Regression for High-Dimensional Time Series”, Journal of Econometrics, 235(2), 1239-1256. Ren, Y., Zhu, X., Lu, X., Hu, G. (2022) “Graphical Assistant Grouped Network Autoregression Model: a Bayesian Nonparametric Recourse”, Journal of Business & Economic Statistics, online. (Joint work with my student Yimeng Ren) Gao, Y., Zhu, X., Qi, H., Li, G., Zhang, R., Wang, H. (2022) “An Asymptotic Analysis of Random Partition Based Minibatch Momentum Methods for Linear Regression Models”, Journal of Computational and Graphical Statistics, online. Pan, R., Chang, X., Zhu, X., Wang, H. (2022) “Link prediction via latent space logistic regression model”, Statistics and Its Interface, 15, 267-282. Zeng, Q., Zhu, Y., Zhu, X., Wang, F., Zhao, W., Sun, S., Su, M., Wang, H. (2022) “Improved Naive Bayes with Mislabeled Data”, Statistics and Its Interface, accepted Qi, H., Zhu, X., Wang, H. (2022) “A Random Projection Method for Large-Scale Community Detection”, Statistics and Its Interface, accepted Guo, B., Wang, L., Pan, R., Zhu, X. (2022) “A grouped spatial-temporal model for PM2.5 data and its applications on outlier detection”, Communications in Statistics - Simulation and Computation, online. Zhu, X., Cai, Z., Ma, Y. (2022) “Network functional varying coefficient model”, Journal of the American Statistical Association, 117(540), 2074-2085. Zhu, X., Pan, R., Wu, S., Wang, H. (2022) “Feature Screening for Massive Data Analysis by Subsampling”, Journal of Business & Economic Statistics, 40(4), 1892-1903. Wu, S., Zhu, X., Wang, H. (2021) “Subsampling and Jackknifing: A Practically Convenient Solution for Large Data Analysis with Limited Computational Resources”, Statistica Sinica, accepted Zhu, X., Li, F., Wang, H. (2021) “Least-Square Approximation for a Distributed System”, Journal of Computational and Graphical Statistics, 30(4), 1004-1018. 王菲菲, 朱雪宁, 潘蕊 (2021), “广义网络向量自回归”, 中国科学:数学, 2021, 8:1253-1266. Huang, D., Zhu, X., Li, R., and Wang, H. (2021), “Feature screening for network autoregression model”, Statistica Sinica, 31, 1239-1259. [Supplement] Zhu, X., Pan, R., Zhang, Y., Chen, Y., Mi, W., Wang, H. (2021) “Information diffusion with network structures”, Statistics and Its Interface, 14, 115-129. Huang, D., Zhu, X., Luo, W., Yin, H., Hong, J., Chen, Y., Zhou, J., Wang, H. (2021) “On Identification of High Risk Carriers of COVID-19 Using Masked Mobile Device Data”, Journal of Data Science, 18(5), 849-859. Zhu, X. (2020) “Nonconcave penalized estimation in sparse vector autoregression model,” Electronic Journal of Statistics, 14, 1413-1448. Zhu, X., and Pan, R. (2020), “Grouped network vector autoregression,” Statistica Sinica, 30, 1437-1462. [Code] Zhu, X., Huang, D., Pan, R., and Wang, H. (2020), “Multivariate spatial autoregression for large scale social network,” Journal of Econometrics, 215, 591-606.[Code] Xu, K., Sun, L., Liu, J., Zhu, X., and Wang, H. (2020) “A spatial autoregression model with time-varying coefficients,” Statistics and Its Interface, 13, 261-270. Huang, D., Wang, F., Zhu, X., and Wang, H. (2020), “Two-mode network autoregressive model for large-scale networks,” Journal of Econometrics, 216, 203-219. Zhang, X., Pan, R., Guan, G., Zhu, X., and Wang, H. (2020), “Network logistic regression model”, Statistica Sinica, 30, 673-693. Zhu, X., Chang, X., Li, R., and Wang, H. (2019), “Portal nodes screening for large scale social networks,” Journal of Econometrics, 209, 145-157. Zhu, X., Wang, W., Wang, H., and Hardle, W. (2019), “Network quantile autoregression,” Journal of Econometrics, 212, 345-358. Pan, R., Guan, R., and Zhu, X. (2018), “A latent moving average model for network regression,” Statistics and Its Interface, 11, 641-648. Cai, W., Guan, G., Pan, R., Zhu, X., and Wang, H. (2018), “Network linear discriminant analysis,” Computational Statistics and Data Analysis, 117, 32-44. Zhu, X., Pan, R., Li, G., Liu, Y., and Wang, H. (2017), “Network vector autoregression”, Annals of Statistics, 45, 1096-1123. [Supplement][Code] Zhu, X., Huang, D., Pan, R., and Wang, H. (2016), “An EM algorithm for click fraud detection,” Statistics and Its Interface, 9, 389-394.

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