Education
Dr. Lei Xiang holds a Ph.D. in Biomedical Engineering from Shanghai Jiao Tong University (2019). He earned his Master’s degree in System Science from Nanjing University of Information Science & Technology (2015) and a Bachelor’s degree in Systems Engineering from the same university (2012).
Professional Experience
Dr. Xiang is currently the Chief Technology Officer (CTO) at Subtle Medical, Shanghai, a leading company in AI-driven medical imaging solutions. Previously, he worked as a Senior Deep Learning Scientist at Subtle Medical, Menlo Park, USA, where he developed advanced deep learning models for medical image enhancement, focusing on PET, MRI, CT, and SPECT imaging.
He has also gained research experience as an Intern at SenseTime (Shanghai), working on automated pelvis segmentation models, and as a Visiting Scholar at the University of North Carolina at Chapel Hill and Shenzhen Institutes of Advanced Technology.
Research & Publications
Dr. Xiang has an extensive research background in deep learning for medical imaging, with over 13 journal papers and 9 conference papers published in top-tier venues, including Medical Image Analysis, IEEE Transactions on Medical Imaging, Neurocomputing, and Pattern Recognition. His research focuses on multi-modal medical image reconstruction, deep learning-based PET/MRI enhancement, and AI-driven medical diagnostics.
Patents, Honors & Awards
Dr. Xiang holds 10+ international patents, including technologies for SubtlePET, SubtleMR, SubtleSPECT, SubtleCT, and SubtleSpine. He has won numerous prestigious awards, including:
- First Place in the Ultra-low Dose PET Imaging Challenge (UDPET, 2022)
- 1st Rank in the FastMRI Challenge Public Leaderboard (2020)
- 3rd Prize in Spark: “Digital Body” AI Challenge (2020)
- 2nd Rank in the Robotic Scene Segmentation Challenge (2018, MICCAI)
- 1st Prize in the National Postgraduate Mathematic Contest in Modeling (2016)
- Outstanding Graduate Award for both Undergraduate and Graduate studies
Professional Services
Dr. Xiang actively contributes to the AI and medical imaging community as a conference reviewer for major AI and medical imaging conferences, including CVPR, ICCV, MICCAI, MIDL, ECCV, and WACV.
Research Interests
- AI-powered medical image enhancement
- Deep learning for multi-modal fusion in medical imaging
- PET/MRI/CT reconstruction and noise-aware image processing
- Automated diagnostics and segmentation in medical imaging