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 Institute of Mathematical Statistics (IMS) Tweedie Award and the Royal Statistical Society (RSS) Research Prize.

I am looking for PhD students interested in reinforcement learning and large language models (LLMs); see my lecture slides on RL, our AAAI tutorial (Youtube, Bilibili) on RL for two-sided marketplaces, my slides on off-policy evaluation and our review paper.

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

Research

My research is motivated from the following applications:

• LLMs (see our recent paper on fine-tuning);
• Ridesharing (simulated environments for Order Dispatch and Spatio-temporal Policy Evaluation; see also our tutorial (Youtube, Bilibili) and my talk);
• Video-sharing (see our KDD paper for details about our proposal successfully deployed in a widely used mobile app with millions of daily active users)
• Mobile health (some simulated environments for Diabetes and Intern Health);
• Neuroscience (see our paper on using RL for modelling human decision making)
• Precision medicine (a simulated STARD data example).

Some of my recent talks and slides on statistical inference, RL, causal inference, data integration, time series and experimental design:

• StatRL Bilibili, Youtube; Chinese versions: Bilibili, Youtube; slides; the accompanying paper
• CausalRL Youtube, slides; the accompanying paper
• ARMAdesign 2-hour slides, 1-hour slides, 30-minute slides; the accompanying paper
• Pessimistic Data Integration slides; the accompanying paper
• Doubly Inhomogeneous policy learning, policy evaluation.

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

Editorial Service

• 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 (Aug 2023 – present)
• Associate editor, Journal of the Royal Statistical Society, Series B (Jan 2022 – present)
• Associate editor, Journal of Nonparametric Statistics (Jan 2022 – present)