Speaker |
Chengchun Shi |
|---|---|
Affiliation |
London School of Economics and Political Science |
Date |
Wednesday, 29 October 2025 |
Time |
12:30-13:30 |
Location |
Ground floor lecture theatre, Sainsbury Wellcome Center, 25 Howland St, W1T 4JG |
Link |
https://ucl.zoom.us/j/99748820264 |
Event series |
Jump Trading/ELLIS CSML Seminar Series |
Abstract |
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. |
Biography |
He is an Associate Professor of Data Science at the London School of Economics and Political Science (LSE). Before his current position, he served as an Assistant Professor of Data Science at LSE. He received his Ph.D. in Statistics from North Carolina State University, where he worked with Dr. Wenbin Lu and Dr. Rui Song. His research excellence has been recognized with several prestigious awards, including the Peter Gavin Hall Institute of Mathematical Statistics (IMS) Early Career Prize, the IMS Tweedie Award, and the Royal Statistical Society (RSS) Research Prize. |