Ph.D. Statistics, Texas A&M University
B.S. Probability & Statistics, Minor in Economics, Peking University

Prof. Yongtao Guan is Presidential Chair Professor, Fellow of American Statistical Association. He was Leslie O. Barnes Professor and Chair of Management Science,  University of Miami Herbert Business School, Director of Deloitte Institute for Research and Practice in Analytics (DIRPA).

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.