李树威
系 所：统计系，邮箱：[email protected]
个人简历
李树威, 统计学博士, 现任色漫网
教授、统计系主任兼支部书记。2017年6月博士毕业于吉林大学统计系。主要研究方向为生物统计、大数据处理及机器学习，在Biometrika、Biometrics、Statistics in Medicine、Statistica Sinica、Journal of Computational and Graphical Statistics等期刊上发表论文30余篇。主持国家自然科学基金面上项目、国家自然科学基金青年项目、广东省自然科学基金面上项目、广州市科技局项目等。现任中国现场统计研究会资源与环境分会理事、广东省现场统计学会常务理事等。
工作经历
2025年7月至今 色漫网
教授
2020年1月 - 2025年7月 色漫网
副教授
2017年6月 - 2020年1月 色漫网
讲师
研究方向
生存分析、大数据分析、深度学习等
教学方向
统计学、回归分析、多元统计、机器学习、生存分析
部分教研科研项目
1.国家自然科学基金面上项目，12471251， 基于协变量潜在特征的区间删失数据的统计分析，2025.01-2028.12，主持
2.国家自然科学基金青年基金项目，11901128，带有治愈亚组的区间删失数据的统计分析及其应用，2020.01.01-2022.12.31，主持
3.广东省自然科学基金面上项目，2022A1515011901，分组检测的当前状态数据的统计推断及其在疾病发病风险评估中应用，2022.01.01-2024.12.31，主持
4. 教育部产学合作协同育人项目，202102191038，分布式计算平台Hadoop和Spark的师资培训和相关课程改革, 2021.07-2022.06，主持
5.广州市科技创新发展专项资金项目 (第一批) 市校联合项目基础与应用基础研究项目，202102010512，左截断区间删失生存数据的统计推断及其在癌症筛查研究中的应用，2021.04.01-2023.03.31，主持
部分科研论文 (corresponding author*)
1. Fang, L., Hu. T., Li, S.*, Wang, L., McMahan, C. S., and Tebbs, J. M. (2025+). Probit time-to-event regression for misclassified group testing data. Statistica Sinica, accepted.
2. Huang, P., Li, S.*, and Song, X*. (2025). Additive hazards regression analysis of massive interval-censored data via data splitting. The American Statistician, 79(2), 145-155.
3. Li, H., Li, S.*, Sun, L., and Song, X*. (2025). Semiparametric structural equation models with interval-censored data. Structural Equation Modeling: A Multidisciplinary Journal, 32, 14-25.
4. Huang, P., Li, S.*, and Song, X*. (2024). Distributed additive hazards regression analysis of multi-site current status data without using individual-level data. Statistics and Computing, 34, article number: 208.
5. Li, H., Li, S.*, Sun, L., and Song, X. (2024). Factor-augmented transformation models for interval-censored failure time data. Biometrics, 80, article number: ujae078.
6. Yuan, C., Zhao. S., Li, S.*, and Song, X*. (2024). Sieve maximum likelihood estimation of partially linear transformation models with interval-censored data. Statistics in Medicine, 43, 5765-5776.
7. Li, S., Hu. T., Wang, L., McMahan, C. S., and Tebbs, J. M. (2024). Regression analysis of group-tested current status data. Biometrika, 111, 1047-1061.
8. Deng, Y., Li, S.*, Sun, L., and Song, X. (2024). Semiparametric probit regression model with general interval-censored failure time data. Journal of Computational and Graphical Statistics, 33, 1413-1423.
9. Feng, F., Wang, P., Li, S.*, Sun, J. and Ke, C. (2023). Semiparametric regression analysis of length-biased and partly interval-censored data with application to an AIDS cohort study. Statistics in Medicine, 42, 2293-2310.
10. Fang, L., Li, S.*, Sun, L., and Song, X. (2023). Semiparametric probit regression model with misclassified current status data. Statistics in Medicine, 42, 4440-4457.
11. Li, S., and Peng, L. (2023). Instrumental variable estimation of complier causal treatment effect with interval-censored data. Biometrics, 79, 253-263.
12. Sun, L., Li, S.*, Wang, L., Song, X., and Sui, X. (2022). Simultaneous variable selection in regression analysis of multivariate interval-censored data. Biometrics, 78, 1402-1413.
13. Li, S., Tian, T., Hu, T., and Sun, J. (2021). A simulation-extrapolation approach for regression analysis of misclassified current status data with the additive hazards model. Statistics in Medicine, 40, 6309 - 6320.
14. Sun, L., Li, S.*, Wang, L., and Song, X. (2021). A semiparametric mixture model approach for regression analysis of partly interval-censored data with a cured subgroup. Statistical Methods in Medical Research, 30, 1890 - 1903.
15. Li, S., Wu, Q, and Sun, J. (2020). Penalized estimation of semiparametric transformation models with interval-censored data and application to Alzheimer’s disease. Statistical Methods in Medical Research, 29, 2151-2166.
16. Li, S., Hu, T., Zhao, S., and Sun, J. (2020). Regression analysis of multivariate current status data with semiparametric transformation frailty models. Statistica Sinica, 30, 1117-1134.
17. Sun, L., Li, S.*, Wang, L., and Song, X. (2019). Variable selection in semiparametric nonmixture cure model with interval-censored failure time data: an application to the prostate cancer screening study. Statistics in Medicine, 16, 3026-3039.
18. Li, S., Hu, T., Zhao, X., and Sun, J. (2019). A class of semiparametric transformation cure models for interval-censored failure time data. Computational Statistics and Data Analysis, 133, 153-165.
19. Li, S., Hu, T., Wang, P., and Sun, J. (2018). A class of semiparametric transformation models for doubly censored failure time data. Scandinavian Journal of Statistics, 45, 682–698.
20. Li, S., Hu, T., Wang, P., and Sun, J. (2017). Regression analysis of current status data in the presence of dependent censoring with applications to tumorigenicity experiments. Computational Statistics and Data Analysis, 110, 75–86.
