Research Interests

I am a Ph.D. student at the Institute of Medical Robotics (IMR), Shanghai Jiao Tong University, under the supervision of Prof. Yun Gu and Prof. Jie Yang. Now I am also a visiting scholar at the Chair for Computer Aided Medical Procedures & Augmented Reality (CAMP), Technical University of Munich, under the supervision of Prof. Nassir Navab. My research lies in the intersection of medical imaging and artificial intelligence, with a particular focus on CT/MRI. I work on medical image computing and cad-assisted intervention. My interests include vertebral shape analysis, implicit and explicit shape priors for volumetric image segmentation, temporal interpolation for pulmonary CT/Cardiac MRI, and test time adaptation for medical segmentation.

My research of interests include:

  • Vertebral shape modeling
  • General segmentation
  • Medical image synthesis
  • Domain adaptation for medical segmentation

News

[Jul 2025] one paper accepted by ICCV 2025.

[Jul 2025] one paper accepted by MICCAI 2025.

[May 2025] one paper early accepted by MICCAI 2025.

[May 2025] one paper accepted by IEEE JBHI.

[Dec 2024] one paper accepted by IEEE TMI.

[Dec 2024] one paper accepted by Frontiers of Medicine.

[Oct 2024] one paper accepted by MICCAI 2024.

[Sep 2024] one paper accepted by IEEE TMI.

[Oct 2023] one paper accepted by MICCAI 2023.

[May 2023] one paper accepted by Medical Physics.

[Dec 2022] one paper accepted by MICCAI workshop - MLMI 2022.

[Mar 2022] one paper accepted by IEEE ISBI 2022.

Education

  • Dec. 2024 - Now: Visiting Scholar at CAMP, Technical University of Munich
  • Sep. 2020 - Now: PhD Candidate at IMR, Shanghai Jiao Tong Univeristy
  • Sep. 2016 - Jun. 2020: Bachelor in Automation at Harbin Institute of Technology

Work Experience

  • Mar. 2021 - Sep. 2021: Medtronic Technology Center, Shanghai
  • Apr. 2022 - May. 2023: OpenMMLab, Shanghai AI Lab

Awards

  • MICCAI 2024 TopCoW challenge: Golden prize for one track, Silver prizes for two tracks
  • MICCAI 2024 LIQA challenge: Best Performance Award