About

I’m a third year Ph.D. candidate at the School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-SZ) supervised by Prof. Guiliang Liu and co-supervised by Prof. Hongyuan Zha.
Before, I received my Bachelor's degree (rank: 1/225) at the School of Computer Science, Northwestern Polytechnical University (NWPU) in 2023. I was honored to be selected as the Graduate Representative and recognized as the Provincial Outstanding Graduate.
My research focuses on:
  • Risk-sensitive / Robust Reinforcement Learning
  • Reinforcement Learning Applications (e.g., Embodied AI, Sports Science)

News

  • [2025.09] One paper was accepted to NeurIPS 2025.
  • [2025.07] One book chapter was published online by Springer Nature in both English and German.
  • [2025.01] Two papers were accepted to ICLR 2025.
  • [2025.01] One paper was accepted to TMLR.
  • [2024.05] One paper was accepted to ICML 2024.
  • [2024.01] Two papers were accepted to ICLR 2024.

Publications

* indicates equal contribution, # indicates project leader

  • A Distributional Approach to Uncertainty-Aware Preference Alignment Using Offline Demonstrations
    Sheng Xu, Bo Yue, Hongyuan Zha, Guiliang Liu
    International Conference on Learning Representations (ICLR), 2025
  • Risk, Reward, and Reinforcement Learning in Ice Hockey Analytics
    Sheng Xu, Oliver Schulte, Yudong Luo, Pascal Poupart, Guiliang Liu
    Book Chapter in Artificial Intelligence and Machine Learning in Sports Science, Springer, 2025
    German Version: Künstliche Intelligenz und maschinelles Lernen in der Sportwissenschaft
  • Uncertainty-aware Preference Alignment for Diffusion Policies
    Runqing Miao*, Sheng Xu*#, Runyi Zhao, Wai Kin Victor Chan, Guiliang Liu
    Annual Conference on Neural Information Processing Systems (NeurIPS), 2025
  • Toward Exploratory Inverse Constraint Inference with Generative Diffusion Verifiers
    Runyi Zhao*, Sheng Xu*, Bo Yue, Guiliang Liu
    International Conference on Learning Representations (ICLR), 2025
  • A Comprehensive Survey on Inverse Constrained Reinforcement Learning
    Guiliang Liu, Sheng Xu, Shicheng Liu, Ashish Gaurav, Sriram Ganapathi Subramanian, Pascal Poupart
    Transactions on Machine Learning Research (TMLR), 2025
  • Robust Inverse Constrained Reinforcement Learning under Model Misspecification
    Sheng Xu, Guiliang Liu
    International Conference on Machine Learning (ICML), 2024
  • Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning
    Sheng Xu, Guiliang Liu
    International Conference on Learning Representations (ICLR), 2024
  • Enhancing Human-AI Collaboration Through Logic-Guided Reasoning
    Chengzhi Cao, Yinghao Fu, Sheng Xu, Ruimao Zhang, Shuang Li
    International Conference on Learning Representations (ICLR), 2024
  • An Improved Lightweight YOLOv5 Model Based on Attention Mechanism for Face Mask Detection
    Sheng Xu, Zhanyu Guo, Yuchi Liu, Jingwei Fan, Xuxu Liu
    International Conference on Artificial Neural Networks (ICANN), 2022 (Oral)

Education

Honors and Awards

  • National Scholarship 2021 & 2022
  • Ph.D. Presidential Fellowship (highest scholarship), 2023-2028
  • Duan Yong Ping Meritorious Research Award, 2024
  • Duan Yong Ping Travel Award, 2024
  • Outstanding Graduate of Shaanxi Province, 2023
  • NWPU Top Undergraduate Student Award (highest honor of undergraduates, only 10 winners), 2022
  • NWPU Top Class Scholarship (highest scholarship, only 10 winners) 2022
  • Modern Scientists Scholarship (top 1%), 2022
  • Huawei Scholarship (top 1%), 2022

Internship

Teaching

  • DDA4230 Reinforcement Learning: Fall 2023 & 2024
    Leading Teaching Assistant x 2
  • DDA2001 Introduction to Data Science: Spring 2024 & 2025
    Leading Teaching Assistant x 1, Teaching Assistant x 1

Service

  • Conference Reviewer: ICLR, ICML, NeurIPS, AAAI, AISTATS
  • Journal Reviewer: Expert Systems With Applications, Pattern Recognition, Applied Intelligence
  • Volunteer: ICML'24