Welcome!
I am a Ph.D. student in Computer Science at Hong Kong Baptist University, advised by Prof. Xiaoqing Guo in the UltraVision+ Lab.
My research focuses on artificial intelligence for medical imaging, with a particular interest in 3D ultrasound reconstruction, neural rendering, and Gaussian Splatting.
My current research focuses on 3D reconstruction from 2D ultrasound sequences. I am interested in using AI to build spatial-aware medical image representations. My long-term interest is to integrate medical image reconstruction, 3D representation learning, and human-AI interaction to support more efficient clinical workflows, such as helping clinicians understand scanned regions, assess spatial coverage, and improve the efficiency and reliability of clinical practice.
Before starting my Ph.D., I worked on accelerated MRI reconstruction and diffusion-based medical image reconstruction at the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences. I received my B.Eng. degree in Biomedical Engineering from Shenzhen University.
These Days
🎉 UltraVoxelGS was accepted to NeurIPS 2026.
🎉 Guided MRI Reconstruction via Schrödinger Bridge was published in IEEE Transactions on Medical Imaging.
Started my Ph.D. journey in Computer Science at Hong Kong Baptist University.
Presented our work on accelerated quantitative T1ρ mapping as an Oral at ISMRM 2025.
Graduated from Shenzhen University with a B.Eng. in Biomedical Engineering.
Worked as a Research Assistant at the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences.
Visited the Lauterbur Research Center for Biomedical Imaging as an undergraduate researcher.
Featured Publications
View all publications →Guided MRI Reconstruction via Schrödinger Bridge
IEEE Transactions on Medical Imaging, 2026
View publication →High-Frequency Space Diffusion Models for Accelerated MRI
IEEE Transactions on Medical Imaging, 2024
View publication →SPIRiT-Diffusion: Self-Consistency Driven Diffusion Model for Accelerated MRI
IEEE Transactions on Medical Imaging, 2024
View publication →Still learning, still wandering.