嘉  宾：毛小介 副教授 清华大学
主持人：韩雪雯 助理教授 上海交通大学安泰经济与管理学院
时  间：2026年5月20日（周三）14:00-15:30
地  点：上海交通大学徐汇校区安泰楼A511

内容简介:
This talk introduces the Double/Debiased Machine Learning (DML) framework, showcasing its power to address the challenges of empirical model specifications. DML synergistically combines the flexibility of machine learning techniques with the rigor of semiparametric statistic theory, enabling flexible modeling of complex functions alongside valid statistical inference. The talk aims to provide an accessible and comprehensive overview of DML's core principles and illustrate DML through applications in several empirical settings. Comparative simulations and real-data analyses demonstrate DML's improved performance over traditional parametric and semiparametric methods. Finally, we highlight potential pitfalls in applying DML and offer some guidelines for empirical  researchers.

演讲人简介：
毛小介，清华大学经济管理学院管理科学与工程系副教授。2016年获武汉大学数理经济与数理金融专业学士学位，2021年获得美国康奈尔大学统计与数据科学专业博士学位。主要研究方向为因果推断、数据驱动的决策理论与方法、统计机器学习。相关研究成果发表于Management Science、Operations Research、Information Systems Research、Journal of Machine Learning Research、Journal of the Royal Statistical Society Series B、NeurIPS、ICML、COLT等运筹管理、统计学与机器学习领域的知名学术期刊和会议。

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