I conducted visiting studies at Wilfrid Laurier University in Canada from September 2017 to September 2018. In June 2019, I obtained a PhD in Mathematics from the School of Mathematics at Tianjin University. From July 2019 to December 2024, I taught at the Department of Statistics at the School of Mathematics at Taiyuan University of Technology. I am currently an assistant researcher at the Institute for Statistics and Interdisciplinary Innovation at Southwestern University of Finance and Economics. My main research direction is point process statistical inference and its applications, as well as high-dimensional data analysis.
Li Chenlong
/ Assistant Research Fellow
E-mail：lichenglong AT swufe.edu.cn
Awards and Honors
Research Projects
- 2024.01-2024.12：National Natural Science Foundation of China Tianyuan Fund for Mathematics “Statistical Inference of Microstructure Noise in High Dimensional and High Frequency Financial Data”
- 2019.09-2022.09：Applied Basic Research Programs of Shanxi Province “Non parametric Estimation Theory and Human Behavior Research of Spatiotemporal Self Excitation Point Processes”
Selected Papers
- Li, C., & Hu, Y. (2024+). Analysis of the spatiotemporal velocity of annual precipitation based on random field. Communications in Statistics – Theory and Methods, in press.
- Li, C., & Cui, K. (2024). Multivariate Hawkes processes with spatial covariates for spatiotemporal event data analysis. Annals of the Institute of Statistical Mathematics, 76, 535-578.
- Bian W., Li, C., Hou, H., & Liu X. (2023). Iterative convolutional enhancing self-attention Hawkes process with time relative position encoding. International Journal of Machine Learning and Cybernetics, 14, 2529-2544.
- Bian, W., Li, C., & Hou, H. (2022). Second Prediction of the Deep Point Process Based on Conditional Generative Adversarial Network. Computer Engineering, 48, 127-133.
- Lu, J., Li, C., & Wei, Y. (2022). Wasserstein learning method for self-attention temporal point process generation model. Application Research of Computers, 39, 456-460.
- Xing Y., Li, D., & Li C., (2022). Time series prediction via elastic net regularization integrating partial autocorrelation. Applied Soft Computing, 129, 109640.
- Li, C., Song, Z., & Wang W. (2020). Space-time inhomogeneous background intensity estimators for semi-parametric space-time self-exciting point process models. Annals of the Institute of Statistical Mathematics, 72, 945-967.
- Li, C., Song, Z., Wang, W., & Wang X. (2019). Mining periodic patterns and cascading bursts phenomenon in individual e-mail communication. Journal of Applied Statistics, 46, 2603-2626.
- Li, C., & Su, L. (2017). Extracting harmonic signal from a chaotic background with local linear model. Mechanical Systems and Signal Processing, 84, 499-515.