General

Dr. Shaodong Ma is a Senior Engineer at the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy of Sciences (CAS), and a Master's supervisor at the University of Chinese Academy of Sciences (UCAS).

He earned his Ph.D. (2011) and B.Eng. (2008) from the University of Hull, UK, and completed postdoctoral training there before joining the CAS system. His research spans domain generalization and robust AI for medical imaging, with a strong emphasis on clinical translation and lightweight deployment of ophthalmic AI systems.

Research Areas

Graduate Programs & Research Directions

  • 085500 – Mechanical (Professional Master's Degree)
  • Development and engineering of intelligent medical image analysis systems; lightweight deployment and generalization optimization of AI medical device models; clinical translation and industrialization of intelligent ophthalmic diagnostic equipment.
  • 083100 – Biomedical Engineering (Academic Master's Degree)
  • Domain generalization theory and algorithms for medical imaging; robustness and interpretability in intelligent medical image analysis; multimodal ocular-cerebral imaging intelligence: theoretical modeling and clinical validation.

Education

  • Ph.D., University of Hull, United Kingdom, 2008–2011
  • B.Eng., University of Hull, United Kingdom, 2004–2008


Experience

  • 2026.01–2029.01: Senior Engineer, NIMTE, CAS
  • 2021.07–2025.12: Assistant Researcher, NIMTE, CAS
  • 2017.06–2021.07: Co-founder, Suoqi Intelligent Technology (Beijing) Co., Ltd.
  • 2015.03–2017.04: University-appointed Researcher, Beijing Institute of Technology
  • 2012.07–2014.04: Postdoctoral Researcher, University of Hull, UK


Publications

   
Papers
  1. RSAPower: Random Style Augmentation Driven Structure Perception Network for Generalized Retinal OCT Fluid Segmentation. IEEE Transactions on Medical Imaging, 2025. (6th author)
  2. Robust and accurate corneal interfaces segmentation in 2D and 3D OCT images. Frontiers in Medicine, 2024. (3rd author, Corresponding)
  3. Hybrid graph representation learning for carotid artery stenosis detection based on multimodal retinal OCTA images. IEEE Access, 2024. (5th author, Corresponding)
  4. Rethinking Data Augmentation for Single-source Domain Generalization in OCT Image Segmentation. IEEE Journal of Biomedical and Health Informatics, 2024. (2nd author, Corresponding)
  5. Automated Segmentation of Trigeminal Nerve and Cerebrovasculature in MR-Angiography Images by Deep Learning. Frontiers in Neuroscience, 2022. (4th author, Corresponding)


Research Interests

Research Interests & Graduate Supervision Areas

  1. Theory and algorithms for domain generalization in medical imaging;
  2. Robustness and interpretability in intelligent medical image analysis;
  3. Multimodal ocular-cerebral imaging intelligence: theoretical modeling and clinical validation.


Collaboration

Selected Research Projects (Principal Investigator)

  1. AI-Based Precision Diagnosis and Treatment Decision System for Glaucoma — Municipal Government Task, 2025–2027.
  2. Eye-Brain Linkage Modeling for Early Precision Diagnosis of Neurodegenerative Diseases — Municipal Government Task, 2022–2027.