教授 博士生导师 中央财经大学

邮箱：panrui_cufe@126.com

教育背景

2004.09—2008.06，中国人民大学统计学院，经济学学士

2008.06—2014.01，北京大学光华管理学院，商务统计与经济计量系，经济学博士

工作经历

2022.12—至今，中央财经大学，统计与数学学院，教授

2016.09—2022.12，中央财经大学，统计与数学学院，副教授

2014.06—2016.09，中央财经大学，统计与数学学院，助理教授

主讲课程

统计建模、统计学、统计学导论

教学奖励

中央财经大学第十二届青年教师教学基本功比赛二等奖

首届中国高校财经慕课联盟“同课异构”课程思政教学竞赛一等奖

第四届全国应用统计专业学位研究生教育教学成果奖

研究兴趣

网络结构数据的统计建模

时空数据的统计分析

论文发表

Pan, R., Gao, Y.* and Wang, H. (2026), “A latent space model for link prediction in statistical citation network”, Journal of Multivariate Analysis, 212, 105555.

Shi, J., Gao, Y.*, Pan, R. and Wang, H. (2026), “A latent factor model for high-dimensional binary data”, Journal of Multivariate Analysis, 212, 105554.

Ding, Y., Zhu, X., Pan, R.* and Zhang, B.* (2025), “Network vector autoregression with time-varying nodal influence”, Computational Economics, 66(5), 4161—4187.

Zhang, Y., Pan, R.*, Wang, F., Fang, K.* and Wang, H. (2025), “Network embedding for bipartite networks with applications in interlocking directorates in Chinese companies”, Computational Statistics, 40(8), 4331—4366.

Liu, K., Zhang, Y.*, Pan, R.*, Gao, T. and Wang, H. (2025), “Academic Literature Recommendation in Large-scale Citation Networks Enhanced by Large Language Models”, Scientometrics, 130(9), 5143—5169.

Deng, T., Gao, T.*, Xia, C. and Pan, R.* (2025), “Overlapping Community Detection in Statistical Keyword Co-occurrence Network by Mixed-SCORE”, IEEE Access, 13, 151289—151303.

Zhang, Y., Pan, R.*, Zhu, X., Fang, K.* and Wang, H. (2025), “A latent space model for weighted keyword co-occurrence networks with applications in knowledge discovery in statistics”, Journal of Computational and Graphical Statistics, 34(3), 779—794.

Gao, Y., Pan, R.*, Li, F., Zhang, R. and Wang, H. (2025), “Grid point approximation for distributed nonparametric smoothing and prediction”, Journal of Computational and Graphical Statistics, 34(3), 824—836.

Zhou, T.,Pan, R.#, Zhang, J.*, and Wang, H. (2025), “An attribute-based Node2Vec model for dynamic community detection in co-authorship network,” Computational Statistics, 40,177-204.

Li, X., Gao, Y.*, Chang, H., Huang, D., Ma, Y.,Pan, R., et al. (2024), “A selective review on statistical methods for massive data computation: distributed computing, subsampling, and minibatch techniques,” Statistical Theory and Related Fields, 8(3), 163—185.

Pan, R.,Liu, T., and Ma, L. (2024), “A Graph Attention Recurrent Neural Network Model for PM2.5 Prediction: A Case Study in China from 2015 to 2022”, Atmosphere, 15, 799.

Guo, B., Wang, L.,Pan, R.^*,and Zhu, X. (2024), “A grouped spatial-temporal model for PM2.5 data and its applications on outlier detection,” Communications in Statistics – Simulation and Computation, 53(5), 2565—2577.

Gao, T.,Pan, R.,Zhang, J.^*, and Wang, H. (2024), “Community detection in temporal citation network via a tensor-based approach,” Statistics and Its Interface, 17(2), 145—158.

Gao, T., Liu, J.,Pan, R.^*,and Wang, H. (2024), “Citation counts prediction of statistical publications based on multi-layer academic networks via neural network model,” Expert Systems with Applications, 238, 121634.

Ding,Y.,Pan, R.^*, Zhang, Y., and Zhang, B. (2023), “A matrix completion bootstrap method for estimating scale-free network degree distribution,” Knowledge-Based Systems,277,110803.

Pan, R., Zhu, Y.^*, Guo, B., Zhu, X., and Wang, H. (2023), “A sequential addressing subsampling method for massive data analysis under memory constraint,” IEEE Transactions on Knowledge and Data Engineering, 35(9), 9502-9513.

Zhang, Y.,Pan, R.^*, Wang, H., and Su, H. (2023), “Community Detection in Attributed Collaboration Network for Statisticians,” Stat, 12(1), e507.

Pan, R., Ren, T.^*, Guo, B., Li, F., Li, G., and Wang, H. (2022), “A note on distributed quantile regression by pilot sampling and one-step updating,” Journal of Business and Economics Statistics, 40(4), 1691—1700.

Zhu, X., Wu, S.^*,Pan, R., and Wang, H. (2022), “Feature screening for massive data analysis by subsampling,” Journal of Business and Economics Statistics, 40(4), 1892—1903.

Song, X., Zhang, Y.^*,Pan, R.^*, and Wang, H. (2022), “Link prediction for statistical collaboration networks incorporating institutes and research interests,” IEEE Access, 10,104954—104965.

Pan, R., Chang, X.^*, Zhu, X., and Wang, H. (2022), “Link prediction via latent space logistic regression model,” Statistics and Its Interface, 15(3), 267—282.

Gao, T., Zhang, Y., Wang, S., Yang, Y., and Pan, R.^*(2021), “Community Detection for Statistical Citation Network by D-SCORE,” Statistics and Its Interface, 14(3), 279—294.

Zhu, X.,Pan, R.^*, Zhang, Y., Chen, Y.,Mi, W.,and Wang, H. (2021), “Information Diffusion withNetworkStructures,”Statistics and Its Interface,14(2), 115—129.

Zhu, X.,Huang, D.^*,Pan, R., and Wang, H. (2020), “Multivariate Spatial Autoregressive Modelfor Large Scale Social Networks,”Journal of Econometrics,215(2), 591—606.

Zhu, X., and Pan, R.^*(2020),“Grouped Network Vector Autoregression,”Statistica Sinica,30(3), 1437—1462.

Ma, Y.,Pan, R.^*, Zou, T., and Wang, H. (2020), “A Naive Least Squares Method for Spatial Autoregression with Covariates,” Statistica Sinica,30(2), 653—672.

Zhang, X.,Pan, R., Guan, G.^*, Zhu, X., and Wang, H. (2020), “Logistic Regressionwith Network Structure,” Statistica Sinica,30(2), 673—693.

Zhou, J., Li, D.^*,Pan, R., and Wang, H. (2020),“Network GARCH Model,”Statistica Sinica,30(3),1723—1740.

Cheng, H., Li, S., Ning, Y., Chen, X.,Pan, R., and Zhang, Z. (2020), “Analysis on utilization of Beijing local roads using taxi GPS data,” Physica A, 545, 123570.

Xu, K., Wang, J.^*,Pan, R., and Wang, H. (2019),“Photographic Diary: A New Estimation Approach to PM2.5 Monitoring,”Statistics and Its Interface,12, 387—395.

Zhang, Y., Fan, J.,Pan, R.^*, and Huang, L. (2019),“Usage Based Insurance with pointof interestdata,”Statistics and Its Interface, 12, 345—353.

Chen, Y.,Pan, R.^*, Guan, R., and Wang, H. (2019),“A case study for Beijing Point of Interest Data Using Group Linked Cox Process,”Statistics and Its Interface, 12, 331—344.

Cai, W., Guan, G.,Pan, R.^*, Zhu, X., and Wang, H. (2018), “Network Linear Discriminant Analysis,” Computational Statistics and Data Analysis, 117, 32—44.

Pan, R., Guan, R.^*, Zhu, X., and Wang, H. (2018), “A Latent Moving Average Model for Network Regression,”Statistics and Its Interface, 11(4), 641—648.

Zhu, X.,Pan, R.^*, Li, G., Liu, Y., and Wang, H. (2017), “Network Vector Autoregression,” Annals of Statistics, 45(3), 1096—1123.

Lan, W.,Pan, R., Luo, R.^*, and Cheng Y. (2017),“High Dimensional Cross-Sectional Dependence Test under Arbitrary Serial Correlation,”Science China: Mathematics, 60, 345—360.

Pan, R., Wang, H.^*, and Li, R. (2016),“Ultrahigh-Dimensional Multiclass Linear Discriminant Analysis by Pairwise Sure Independence Screening,”Journal of the American Statistical Association, 111(513), 169--179.

Zhu, X., Huang, D.^*,Pan, R., and Wang, H. (2016),“An EM algorithm for click fraud detection,”Statistics and Its Interface, 9, 389-394.

Pan, R.^*, and Wang, H. (2015),“A Note on Testing Conditional Independence for Social Network Analysis,”SCIENCE CHINA： Mathematics, 58(6), 1179-1190.

Pan,R., Wang, H.^*, and Tsai, C. (2011),“Regression Analysis of Asymmetric Pairs in Large-Scale Network Data,”Communications in Statistics: Simulation and Computation, 40:10, 1540-1547.

Li, J., Pan, R., and Wang, H. (2010),“Selection of Best Keywords: A Poisson Regression Model,”Journal of Interactive Advertising, 11(1), 27-35.

高天辰, 张妍, 潘蕊（2024）. 统计学科大规模多层学术网络数据集——网络构建、描述分析与实际应用. 经济管理学刊, 3(4)，237—260.

张妍，潘蕊，方匡南（2023），基于合作者网络社区发现的学科主题分析—以国际统计学期刊为例，经济管理学刊，2(2)，219—240.

王菲菲，朱雪宁^*，潘蕊（2021），广义网络向量自回归，中国科学：数学，51（8），1253--1266.

潘蕊，周静^*，关蓉（2017），“网络中意见领袖对客户间接价值的影响，” 《商业研究》，59(9)，28—32.

著作

潘蕊 著，《数据思维实践》，北京大学出版社，2018年.

潘蕊 张妍 高天辰 著，《网络数据分析与应用》，北京大学出版社，2022年.

科研课题

《大规模复杂网络结构数据的潜在空间模型：理论与应用研究》，国家自然科学基金面上项目，课题负责人，2025.01-2028.12

《大规模网络结构数据的统计建模：理论与应用研究》，国家自然科学基金面上项目，课题负责人，2020.01-2023.12

《含网络结构的离散选择模型：理论及应用研究》，国家自然科学基金青年项目，课题负责人，2017.01—2019.12

《奥迪用户价值体系的数据管理与描述分析》，横向课题，课题主持人，2014.12-2015.12