About Me
I’m an PhD candidate under the supervision of Professor Jun Liu and Professor Steven Wang at the Centre for Robotics and Automation of CityU. Additionally, I collaborate with Prof. Yixuan Yuan, Prof. Jianqin Yin and Prof. Zhuoran Zhang. Previously, I received my B.Eng. in Mechanical Engineering from the South China University of Technology, where I worked with Professor Zhenping Wan.
My research focuses on applying deep learning to improve medical imaging and robotic surgical precision. I am particularly interested in foundation models and use multimodal inputs to systematically analyse medical subjects. My work includes developing non-invasive sperm detection frameworks for in vitro fertilization. Additionally, I work with real-time image analysis to enhance medical interventions. To address hardware limitations, I design lightweight neural networks that reduce computational demands, making advanced AI more accessible in resource-constrained settings.
I am currently exploring opportunities in the academic job market for faculty positions or postdoctoral roles.
Recent Work
SvANet: Early detection of mild syndromes is crucial for effective patient treatment. We have proposed a novel framework to examine infected areas with an area ratio of less than 1%. Check out the open-access publication, code, and data at the links below!
MobileViM: A Light-weight and Dimension-independent Vision Mamba for 3D Medical Image Analysis. We propose a novel 3D image analysis algorithm designed for rapid and cost-effective applications. Check out the open-access resources at the links below.
Latest Updates
- 06/2025: I submitted my PhD thesis.
- 03/2025: Submitted a paper to IJCV.
- 10/2024: Submitted a paper to JBHI.
- 09/2024: Submitted a paper to TNNLS.
- 08/2024: A paper was accepted to EAAI.
- 07/2024: A paper on cell detection using density map was accepted to IEEE JBHI.
- 06/2024: A paper on non-invasive sperm analysis was accpeted to IEEE TASE.
- 06/2024: Presented a poster at ISBI2024 in Athens, Greece.
- 06/2024: Gave an oral presentation at ICRA2024 in Yokohama, Japan.
- 04/2024: A paper on self-supervised learning was accpeted to Neural Networks.
- 03/2024: A paper on cell counting was accpeted to IEEE TASE.
- 02/2024: A paper was accpeted to ISBI2024.
- 01/2024: A paper was accpeted to ICRA2024.
- 08/2023: A paper on light-weight transformer for skin cancer detection was accpeted to IEEE JBHI.