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【主 题】 On Statistical Learning for Individualized Decision Making with Complex Data.

【报告人】 史成春助教授


【时 间】 2020年19   10:00-11:00

【地 点】 上海财经大学统计与管理学院大楼1208会议室

 In this talk, I will present my research on individualized decision making with modern complex data. In precision medicine, individualizing the treatment decision rule can capture patients' heterogeneous response towards treatment. In finance, individualizing the investment decision rule can improve individual's financial well-being. In a ride-sharing company, individualizing the order dispatching strategy can increase its revenue and customer satisfaction. With the fast development of new technology, modern datasets often consist of massive observations, high-dimensional covariates and are characterized by some degree of heterogeneity.  The talk is divided into two parts. In the first part, I will focus on the data heterogeneity and introduce a new maximin-projection learning for recommending an overall individualized decision rule based on the observed data from different populations with heterogeneity in optimal individualized decision making.  In the second part, I will briefly summarize the statistical learning methods I've developed for individualized decision making with complex data.

嘉宾简介】史成春博士,英国伦敦政治经济学院(London School of Economics)统计系助理教授。在进入LSE之前,史成春博士在2019年获得了美国北卡州立大学(North Carolina State University)统计学博士。他的研究领域包括个性化决策 (individualized decision making), 复杂数据(complex data)主要是高维数据,大数据,异质性数据的统计分析。凭借相关研究成果,史成春博士获得了包括北卡州立大学Paige Plagge Award,以及 Institute of Mathematical Statistics (IMS) Travel Award等许多国际奖项。近年来,他在Annals of Statistics, Journal of American Statistical Association, Journal of the Royal Statistical Society, Series B, Journal of Machine Learning Research等统计学顶级期刊上以第一作者身份发表了10多篇文章。