李霓
发布时间:2024-11-05

教师姓名
李霓,女,统计学博士,副教授,硕士生导师。
Email:lini@hainnu.edu.cn
研究方向:数理统计(生存分析),数据科学(机器学习)
教育经历
2006.08-2011.05密苏里大学(University of Missouri)统计系,统计学博士
2006.08-2009.05密苏里大学(University of Missouri)统计系,统计学硕士
2002.09-2006.07清华大学数学科学系,理学学士
科研与学术工作经历
2017.01至今,海南师范大学,数学与统计学院,副教授
2012.06-2016.12,海南师范大学,数学与统计学院,讲师
2011.06-2012.05,耶鲁大学,生物统计系,博士后
教学情况
主讲的本科生课程:概率统计,多元统计分析,统计计算与软件,机器学习,数学建模,
主讲的研究生课程:高等数理统计,统计学基础,多元统计分析,生存分析
教学获奖:指导全国大学生数学建模竞赛获全国二等奖1项(2019年)、全省一等奖1项(2019年)、全省二等奖6项(2021年1项、2022年2项、2023年2项、2024年1项),全省三等奖10项(2018年2项、2020年1项、2021年4项、2022年1项、2024年2项)。指导美国大学生数学建模竞赛获H奖4项(2022年1项、2024年2项、2025年1项)、S奖5项(2021年1项、2022年2项、2023年1项、2025年1项)。指导亚太地区大学生数学建模竞赛获三等奖2项(2020年1项、2023年1项)、S奖2项(2022年1项、2023年1项)。
承担的主要项目
国家自然科学基金委员会,地区科学基金项目, 12461049,区间删失与混合区间删失数据的变量选择及相关问题研究, 2025-01-01至2028-12-31, 27万元,在研,主持
国家自然科学基金委员会,地区科学基金项目, 11861030,复发事件数据的删失分位数回归研究, 2019-01-01至2022-12-31, 39万元,结题,主持
国家自然科学基金委员会,青年科学基金项目, 11401146,复发事件过程中混杂偏倚的调整和统计分析, 2015-01-01至2017-12-31, 23万元,结题,主持
代表性研究成果
(注释:包括论文、专著、教材、科技奖励、专利等)
Faysal Satter; Yichuan Zhao; Ni Li; Empirical likelihood inference for the panel count data with informative observation process,Statistical Papers, 2024, 65(5): 3039-3061.
Qingxin Liu; Ni Li; Heming Jia; Qi Qi; Laith Abualigah ; A chimp-inspired remora optimization algorithm for multilevel thresholding image segmentation using cross entropy,Artificial Intelligence Review, 2023, 56(1): 159-216.
Yuan Jiang; Ni Li; Heping Zhang; Identifying genetic variants for addiction via propensity score
adjusted generalized Kendall's Tau,Journal of the American Statistical Association, 2014, 109(507): 905-930.
Ni Li; Hui Zhao; Jianguo Sun; Semiparametric transformation models for panel count data
with correlated observation and follow-up times,Statistics in Medicine, 2013, 32(17): 3039-3054.
Ni Li; Liuquan Sun; Jianguo Sun ; Semiparametric transformation models for panel count data with dependent observation process,Statistics in Biosciences, 2010, 2(2): 191-210.
会议报告
1. Ni Li ; An IPW Additive Model for Panel Count Data with Dependent Observation Process and Terminal Event, 2023 ICSA China Conference, Chengdu, Sichuan, 2023-6-30至2023-7-3 (Invited talk)
2. Ni Li ; Semiparametric Model Statistical Inference for Panel Count Data with Adjusting by Propensity Scores, 2022 ICSA China Conference, Xi'an University of Finance and Economics, 2022-7-1至2022-7-4 (Invited talk)
3. Ni Li ; Inverse Probability Weighting Methods for The Analysis of Panel Count Data with Informative Observation Times, 2nd International Conference on Econometrics and Statistics (EcoSta 2018), City University of Hong Kong, 2018-6-19至2018-6-21 (Invited talk)
4. Ni Li ; The Statistical Analysis of Recurrent Event Process with Adjusting for Confounding Effects of Dependent Observation Process, 2017 ICSA China Conference with the Focus on Lifetime Data Science, Beihua University, Jilin, China, 2017-7-2至2017-7-5 (Invited talk)
5. Ni Li ; Semiparametric Analysis of Recurrent Event Data with Cure Rate, 2015 ICSA China Statistics Conference , Fudan University, Shanghai, China, 2015-7-6至2015-7-7 (Invited talk)
6. Ni Li ; Semiparametric transformation models for panel count data with correlated observation and follow-up times, The IMS-China International Conference on Statistics and Probability, Chengdu, Sichuan, 2013-6-30至2013-7-4 (Invited talk)
7. Ni Li; Liuquan Sun; Jianguo Sun ; Semiparametric Transformation Models for Joint Analysis of Observation and Recurrent Event Processes, ENAR 2011 Spring Meeting, Miami, FL, 2011-3-20至2011-3-23 (Contributed talk)
8. Ni Li(1/1); Jiann-Ping Hsu Pharmaceutical and Regulatory Sciences Student Paper Award, International Chinese Statistical Association, 2010 (科研奖励)
9. Ni Li; Liuquan Sun; Jianguo Sun ; Semiparametric Analysis of Panel Count Data with Dependent Observation Process, The 2010 ICSA Symposium, Indianapolis, IN, 2010-6-20至2010-6-23 (Contributed talk)
10. Ni Li; Liuquan Sun; Jianguo Sun ; Semiparametric Transformation Models for Panel Count Data with Dependent Observation Process, ENAR 2010 Spring Meeting, New Orleans, LA, 2010-3-20至2010-3-24 (Contributed talk)