潘蕊

教授 博士生导师 十大澳门信誉老牌网赌 十大网投正规信誉官网

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，十大澳门信誉老牌网赌，十大网投正规信誉官网，教授

2016.09—2022.12，十大澳门信誉老牌网赌，十大网投正规信誉官网，副教授

2014.06—2016.09，十大澳门信誉老牌网赌，十大网投正规信誉官网，助理教授

主讲课程：

统计建模、统计学、统计学导论

教学奖励：

十大澳门信誉老牌网赌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:

• Gao, Y., Pan, R.^*, Li, F., Zhang, R. and Wang, H. (2024), “Grid point approximation for distributed nonparametric smoothing and prediction”, Journal of Computational and Graphical Statistics, accepted.

• Zhang, Y., Pan, R.^*, Zhu, X., Fang, K. * and Wang, H. (2024), “A latent space model for weighted keyword co-occurrence networks with applications in knowledge discovery in statistics”, Journal of Computational and Graphical Statistics, accepted.

• 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, accepted.

• Zhou, T., Pan, R.#, Zhang, J.*, and Wang, H. (2024), “An attribute-based Node2Vec model for dynamic community detection in co-authorship network,” Computational Statistics, accepted.

• 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.

• 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