官永涛

校长讲座教授
副院长(拓展)

教育背景

德克萨斯农工大学统计学博士
北京大学概率与统计学学士,辅修经济学

研究领域
时空数据分析及其在金融 、社交网络、 流行病学等领域中的应用
电子邮箱
guanyongtao@cuhk.edu.cn
办公室
综合楼C709
个人简介

官永涛是校长讲座教授,美国统计协会会士。曾任美国迈阿密大学赫伯特商学院莱斯利·巴恩斯讲席教授,管理科学系系主任,德勤研究与实践分析所主任。

学术著作

1. Fang, G., Xu, G., Xu, H., Zhu, X., and Guan, Y. (2023+), “Group Network Hawkes Process,” Journal of the American Statistical Association, Theory and Methods, to appear.

2. Xu, G., Zhang, J., Li, Y., and Guan, Y. (2023+), “Bias-correction and Test for Mark-point Dependence with Replicated Marked Point Processes,” Journal of the American Statistical Association, Theory and Methods, to appear.

3. Cai, B., Zhang, J. and Guan, Y. (2023+), “Latent Network Structure Learning from High Dimensional Multivariate Point Processes,” Journal of the American Statistical As[1]sociation, Theory and Methods, to appear.

4. Xu, G., Waagepetersen, R. and Guan, Y. (2023+), “Semi-parametric Goodness-of-Fit Test for Clustered Point Processes with a Shape-Constrained Pair Correlation Function,” Journal of the American Statistical Association, Theory and Methods, to appear.

5. Liang, D., Huang, H., Guan, Y. and Yao, F. (2023+), “Test of Weak Separability for Spatial Functional Field,” Journal of the American Statistical Association, Theory and Methods, to appear.

6. Zhang, J., Cai, B., Zhu, X., Wang, H., Xu, G. and Guan, Y. (2023), “Learning Hu[1]man Activity Patterns using Clustered Point Processes with Active and Inactive States,” Journal of Business and Economics Statistics, 41(2), 388–398.

7. Hessellund, K., Xu, G., Guan, Y. and Waagepetersen, R. (2022), “Semi-parametric Multi[1]nomial Logistic Regression for Multivariate Point Pattern Data,” Journal of the American Statistical Association, Theory and Methods, 117(539), 1500–1515.

8. Moghaddassa, R. and Guan, Y. (2022), “Optimal Frameworks for Detecting Anomalies in Sensor-Intensive Heterogeneous Networks,” INFORMS Journal on Computing, 34(5), 2383–2865.

9. Yin, L., Xu, G., Sang, H. and Guan, Y. (2021), “Row-clustering of a Point Process-valued Matrix,” NeurIPS 2021.

10. Wang, W., Xu, G., Bian, J., Burch, B., Andrade, S., Huang, H., Zhang, J. and Guan, Y. (2020), “Semi-Parametric Modeling of Structured Point Processes Using Multi-Level Log-Gaussian Cox Processes,” Journal of Machine Learning Research, 21(192),1–39.