[中文]           

Introduction

• My research lies at the intersection of physics-based simulation, computer graphics, robotics, and machine learning. My work centers on fundamental and applied challenges in high-performance fluid simulation via mesoscopic kinetic approaches, encompassing dynamic fluid-solid coupling, boundary-layer modeling, and reduced-order modeling for such systems, to address design validation and optimization, control, and decision-making tasks for aerial, underwater, and surface robotic platforms dominated by fluid-solid interactions. I also develop large-scale parallel computing frameworks to boost the computational throughput of these simulation pipelines, aiming to unlock innovative technologies for fluid-interactive intelligent robotic systems under a unified multi-scale sim2real paradigm.
  
  I have published a series of papers in top-tier journals and conferences spanning computer graphics, computational fluid dynamics, scientific visualization, control and learning, as well as robotics. I serve as the principal investigator (PI) for multiple nationally funded research projects, including the Youth Program and General Program of the National Natural Science Foundation of China, alongside a Sub-project of National Science and Technology Major Project of the Ministry of Science and Technology of China. I have also participated in several regional sponsored initiatives, such as the Basic Research Project under the Science and Technology Innovation Initiative of Shanghai Municipal Science and Technology Commission, as well as Innovation and Technology Fund (ITF) Project in Hong Kong, China, etc..
  　
• Affiliation: Visual & Data Intelligence Center and Automation & Robotics Center @ School of Information Science & Technology
• Ph.D. in Computer Science & Engineering, Department of Computer Science & Engineering, The Chinese University of Hong Kong
• Research Fellow @ School of Computer Science and Engineering, Nanyang Technological University, Singapore
• Assistant Professor @ ShanghaiTech University / Researcher @ Chinese Academy of Science, China
• Associate Professor @ ShanghaiTech University / Researcher @ Chinese Academy of Science, China (Present)
• Members of ACM/IEEE

Please visit FLARE Lab for more information.

Research Interests

• Computational Fluid Dynamics
• Reduced-order Modeling
• Computer Graphics
• Unmanned Fluid-Interactive Systems
• Machine Learning and Optimal Control
• Distributed High-Performance Computing

Collaborations

California Institute of Technology (USA)
Columbia University (USA)
Technical University of Munich (Germany)
Nanyang Technological University (Singapore)
Cranfield University (UK)
Chinese University of Hong Kong, (China)
Hong Kong Polytechnic University (China)
Zhejiang University (China)
West China Medical Center, Sichuan University (China)

Publications

Note: * indicates either students or research staffs supervising/supervised; ^ indicates corresponding author.

Journal papers:

Conference papers:

1. Xu Huang, Xiaozhu Lin*, Xiaopei Liu, Yang Wang^,
   Agile and Controllable Omnidirectional Fast-start Maneuvers of Robotic Fish via Bio-inspired Reinforcement Learning, IEEE International Conference on Robotics and Automation (ICRA 2026), accepted, 2026.

2. Kaitian Chao, Xiaozhu Lin*, Xiaopei Liu, Yang Wang^,
   Learning Flow-Adaptive Dynamic Model for Robotic Fish Swimming in Unknown Background Flow, 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2025), Accepted, 2025.

3. Pavel Kharitenko*, Xiaopei Liu, Yang Wang^,
   A Spatiotemporal Downwash Modeling for Agile Close-Proximity Multirotor Flight, 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2025), Accepted, 2025.

4. Kefei Wu*, Xuming He, Yang Wang, Xiaopei Liu^,
   Multi-Level Progressive Reinforcement Learning for Control Policy in Physical Simulations, IEEE International Conference on Robotics and Automation (ICRA 2024), accepted, 2024.
   　
5. Xiaozhu Lin, Wenbin Song*, Xiaopei Liu, Xuming He, and Yang Wang^,
   Exploring learning-based control policy for fish-like robots in altered background flows，2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023), Accepted, 2023.
   　
6. Yangyang Zhao, Heng Zhang, Xiaopei Liu, and Yang Wang^,
   Iteration Learning Control for Uncertain Nonlinear Systems with Time-Varying Output Constraint, World Congress of the International Federation of Automatic Control (IFAC 2023), accepted, 2023.
   　
7. Wenji Liu*, Kai Bai*, Xuming He, Shuran Song, Changxi Zheng, and Xiaopei Liu^,
   FishGym: A High-Performance Physics-based Simulation Framework for Underwater Robot Learning, IEEE International Conference on Robotics and Automation (ICRA 2022), accepted, 2022. [more]
   　
8. Long Gao*, Xiaocheng Song*, Xiaopei Liu, and Jie Lu^,
   Learning-based Local Path Planning for UAV in Unknown Environments, European Control Conference (ECC 2022), accepted, 2022.
   　
9. Wenbo Wang*, Yuwei Li, Feng Wang, Xiaopei Liu, and Youyi Zheng,
   Using Visualization to Improve Clustering Analysis on Heterogeneous Information Network, International Conference on Information Visualization (ICIV), 2018, accepted.
   　
10. Peng Song, Wooi Boon Goh, William Hutama, Chi-Wing Fu, and Xiaopei Liu,
    A handle bar metaphor for virtual object manipulation with mid-air interaction, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 10:1297-1306, 2012.
    　
11. Huiqiong Wang, Stephen Lin, Xiaopei Liu, and Sing Bing Kang,
    Separating Reflections in Human Iris Images for Illumination Estimation, IEEE International Conference on Computer Vision (ICCV 2005), 2:1691-1698, 2005.

Book Chapters:

1. Xiaopei Liu, Liang Wan, Xuemiao Xu, Tien-Tsin Wong, and Chi-Sing Leung,
   Interactive Image Morphing Using Thin-Plate Spline, Shader X7: Advanced Rendering Techniques, Charles River Media, 2009, 743-752.