Statistics-powered AI

主讲人：Chengchun Shi

Chengchun Shi is an Associate Professor in the Department of Statistics at LSE. He works at the interface of RL, LLMs and statistics, with applications to ride-sharing and healthcare. His work brings to light the relevance and significance of statistical learning in AI, and demonstrates the usefulness of RL as a framework for policy evaluation and A/B testing in two-sided marketplaces. Chengchun has published over 50 papers, with majority of them accepted in prestigious statistical journals (JRSSB, JASA, AoS) and top machine learning venues (NeurIPS, ICML, KDD, JMLR). His outstanding contributions have been recognized with esteemed awards such as the Peter Gavin Hall IMS Early Career Prize, IMS Tweedie Award and the Royal Statistical Society Research Prize. He has served as the associate editors of prestigious journals JRSS-B, JASA and AoAS.

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报告信息

时间 

2026年1月9日（周五）

10:00

地点 

中国人民大学中关村校区

明德主楼1016

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报告摘要

We have definitely entered an era of generative artificial intelligence (AI), where large language models (LLMs) are increasingly reshaping our daily lives. Their impact is everywhere -- from education and academia to professional work and everyday life. In this talk, I will present two recent NeurIPS papers on statistics-powered AI, focusing on how statistical methodologies can enhance AI's performance in (1) aligning LLM's model outputs with human feedback, and (2) detecting LLM-generated content with rigorous guarantees. Open-source Python implementations are available at https://github.com/Mamba413/AdaDetectGPT and https://github.com/DRPO4LLM/DRPO4LLM.