报告题目：Optimization and Statistics meets in AI age

报告人: Ran Chen （陈然）( Washington University in St. Louis)

时间：2025年6月23日（周一）下午3:30-5:00

地点：理科楼B201

报告摘要：In the age of AI, statistics and optimization—two longstanding fields—are receiving renewed attention as they form the foundation of modern intelligent systems. At the same time, the boundary between them is becoming increasingly blurred, as they are often intertwined in real-world problems. Sometimes, statistics is the goal and optimization the tool—statistical methods depend on solving optimization problems efficiently. Other times, optimization is the goal and statistics the tool—as we aim to recover the optimizer and optimum of an unknown function from noisy observations. In this talk, I will present work in both directions. The first part explores the tradeoff between optimization runtime and statistical accuracy; the second focuses on estimation and inference of the minimizer and minimum of convex functions.

报告人简介：Ran Chen is an Assistant Professor of Statistics and Data Science at Washington University in St. Louis. Prior to joining WashU, she was a postdoctoral researcher at the Laboratory for Information and Decision Systems (LIDS) at MIT. She received her Ph.D. in Statistics and Data Science from the Wharton School at the University of Pennsylvania, and her B.S. in Pure and Applied Mathematics from Tsinghua University. Her research includes reinforcement learning, data-driven decision-making, optimization, statistical machine learning, high-dimensional statistics, and nonparametric statistics, covering theoretical, methodological, and applied aspects, with applications primarily in business (revenue management in particular) and healthcare.

邀请人：杨瑛