Shang Liu

Ph.D. candidate at Imperial Business School Imperial College London, South Kensington Campus, London, SW7 2AZ, United Kingdom Email: s.liu21@imperial.ac.uk

About me

I am a Ph.D. candidate at Imperial Business School under the advice of Prof. Xiaocheng Li and Prof. Kalyan Talluri.
I am now visiting the Department of Management Science and Engineering at Stanford University, hosted by Prof. Jose Blanchet.
I received my M.Res. degree from Imperial College Business School in 2022. Before joining Imperial College, I received my B.Sc. degree from School of Mathematical Sciences at Peking University in 2021.
Here is my CV.
For those who are interested, my Chinese name is 刘(Liu)上(Shang).
I am on the job market of 2026 now!

Research

My current research interests include:

• Machine Learning, Large Language Models, and Operations Research

Publications

reverse chronological order

1. Wasserstein Distributionally Robust Regret Optimization for Reinforcement Learning from Human Feedback
   by Yikai Wang*, Shang Liu*, Jose Blanchet, [arXiv].

2. Incentivizing High-Quality Human Annotations with Golden Questions
   by Shang Liu, Zhongze Cai, Hanzhao Wang, Zhongyao Ma, Xiaocheng Li, [arXiv].

3. How Humans Help LLMs: Assessing and Incentivizing Human Preference Annotators
   by Shang Liu*, Hanzhao Wang*, Zhongyao Ma, Xiaocheng Li, under major revision at Management Science, [arXiv].

4. Reward Modeling with Ordinal Feedback: Wisdom of the Crowd
   by Shang Liu*, Yu Pan*, Guanting Chen, Xiaocheng Li, ICML 2025, [arXiv].

5. Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantification
   by Shang Liu*, Zhongze Cai*, Guanting Chen, Xiaocheng Li, TMLR, [arXiv].

6. Towards Better Statistical Understanding of Watermarking LLMs
   by Zhongze Cai*, Shang Liu*, Hanzhao Wang*, Huaiyang Zhong, Xiaocheng Li, accepted at Journal of the American Statistical Association, [arXiv].

7. When No-Rejection Learning is Consistent for Regression with Rejection
   by Xiaocheng Li, Shang Liu, Chunlin Sun, Hanzhao Wang, AISTATS 2024, [arXiv].

8. Understanding Uncertainty Sampling
   by Shang Liu, Xiaocheng Li, submitted, reject and resubmission at JMLR, [arXiv].

9. Distribution-Free Model-Agnostic Regression Calibration via Nonparametric Methods
   by Shang Liu*, Zhongze Cai*, Xiaocheng Li, NeurIPS 2023, [arXiv].

10. Maximum Optimality Margin: A Unified Approach for Contextual Linear Programming and Inverse Linear Programming
    by Chunlin Sun*, Shang Liu*, Xiaocheng Li, ICML 2023, [arXiv].

11. Non-stationary Bandits with Knapsacks
    by Shang Liu, Jiashuo Jiang, Xiaocheng Li, NeurIPS 2022, [arXiv].

12. Online Bin Packing with Known T
    by Shang Liu, Xiaocheng Li, under major revision at Mathematics of Operations Research, [arXiv].