Short Bio
I am a postdoctoral researcher and assistant researcher in the School of Mechanical Engineering at Zhejiang University, working with Prof. Jianrong Tan. My research focuses on robot learning, human–robot collaboration, and human–cyber–physical systems, with particular interests in generative models for human motion prediction and robot policy learning in smart manufacturing. I received my Ph.D. in Mechanical Engineering from Zhejiang University in 2026, under the supervision of Yixiong Feng and Bingtao Hu. From November 2024 to October 2025, I was a visiting researcher at KTH Royal Institute of Technology, working with Lihui Wang and Xi Vincent Wang. I have co-authored more than 30 journal and conference papers, with work appearing in IEEE Trans. Ind. Inform., Robot. Comput.-Integr. Manuf., Adv. Eng. Inform., and Engineering, among others. Since 2026, I have served as a young editorial board member of Computer Integrated Manufacturing Systems, AI Plus, and Intelligent and Sustainable Manufacturing. I served on the local organising committee of the 74th CIRP General Assembly and as a session chair at IFAC MIM in 2025, and regularly review for journals and conferences in robotics and smart manufacturing.
News
- New work on one-step human motion prediction under occlusions in IEEE Transactions on Industrial Informatics.
- Paper on generative AI for industrial robots accepted in Engineering.
- Paper on human–robot collaborative assembly accepted in CIRP Annals.
Selected Publications
† Equal contribution.
Full list: Publications / Google Scholar
- Efficient one-step human motion prediction under occlusions via constrained MeanFlow
- A two-stage framework for learning human-to-robot object handover policy from 4D spatiotemporal flow
- FineMLD: A fine-grained motion latent diffusion for human motion prediction in Human–robot Collaboration
- Brain-inspired generative AI revives legacy industrial robots toward sustainable automation
- Fatigue delamination shape prognostics in composites using numerical simulation-assisted transfer learning
- Human-robot handover task intention recognition framework by fusing human digital twin and deep domain adaptation