About

(i), I am an associate professor of data science at London School of Economics and Political Science (LSE).

(ii) Pior to (i), I was an assistant professor of data science at LSE.

(iii) Prior to (ii), I was a Ph.D. student in Statistics at North Carolina State University (NCSU). I work with Dr. Wenbin Lu and Dr. Rui Song.

(iv) Prior to (iii), I obtained a B.S. in Statistics from Zhejiang University in July 2014.

(v) Prior to (iv), I graduated from Ningbo Xiaoshi High School in July 2010.

I was honoured to receive the Peter Gavin Hall Institute of Mathematical Statistics (IMS) Early Career Prize, IMS Tweedie Award and the Royal Statistical Society (RSS) Research Prize.

I am looking for students interested in LLMs (see our short course slides), reinforcement learning (see my lecture slides) and statistics.

My email c.shi7@lse.ac.uk. My GitHub.

News

• Sep 2026:
  • New paper Can Tabular Foundation Models Amortize Statistical Inference?
  • Two papers accepted to NeurIPS, one paper to JASA, one to EMNLP, one to Sinica, one to AOAS and one to JMLR.
  • Two plenary talks in Brazil.
• Aug 2026: Talks on Demystifying LLM through U-statistics theory at JSM and Beijing Technology and Business University.
• July 2026: Talks on Demystifying LLM through U-statistics theory at CUHK-Shenzhen, ZJU, JCSDS and Second Interdisciplinary Conference on Statistics and Management Science.
• June 2026:
  • Three papers on LLM and A/B testing accepted to SATI-X.
  • Talks on Demystifying LLM through U-statistics theory at Oxford, IMS-Asia Pacific Rim Meeting, University of Macau, SUFE, Fudan, ECNU, Tongji University, SUIBE and Xiamen University.
• May 2026: Gold Reviewer Award, ICML 2026

Research

My research is motivated from the following applications:

• Large language models:
  • Reasoning: Demystify GRPO (slides); KAE; Fin-R1
  • RLHF: DRPO (slides, talk); VRPO (talk); Dual active learning
  • AI-content detection: AdadetectGPT (talk); L2D; StatDetectLLM (have a try); DID; Change-point-based detection
• Ridesharing (see our AAAI tutorial (Youtube, Bilibili) and my talk; see also some simulated environments for Order Dispatch and Spatio-temporal Policy Evaluation);
• Video-sharing (see our KDD paper successfully deployed in a widely used mobile app with millions of daily active users)
• Mobile health (some simulated environments for Diabetes and Intern Health);
• Psychology (see our paper on using RL for modelling human decision making).

Some of my recent talks and slides on AI, RL, statistical inference, causal inference and experimental design:

• Stats-powered AI Youtube, Bilibili;
• StatRL Bilibili, Youtube; Chinese versions: Bilibili, Youtube; slides; the accompanying paper and its Chinese version
• CausalRL Youtube, slides; the accompanying paper
• ARMAdesign 2-hour slides, 1-hour slides, 30-minute slides; the accompanying paper
• OPE my slides and our review paper.

A summary of my past research: Statistical Methods in Reinforcement Learning (partly supported by EPSRC)

Editorial Service

• Action Editor, TMLR
• Area Chair, NeurIPS
• Area Chair, STAI-X
• Associate editor, Statistical Learning and Data Science (from Nov 2025)
• Associate editor, Annals of Applied Statistics (from Feb 2025)
• Associate editor, Journal of the American Statistical Association, A&CS (from Sep 2024)
• Associate editor, Journal of the American Statistical Association, T&M (from Aug 2023)
• Associate editor, Journal of the Royal Statistical Society, Series B (Jan 2022 – Dec 2025)
• Associate editor, Journal of Nonparametric Statistics (Jan 2022 – present)