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Assistant Professor Meng Wang

Assistant Professor Wang Meng

Assistant Professor,
Centre for Innovation & Precision Eye Health
Department of Ophthalmology
Yong Loo Lin School of Medicine

  Email    Google Scholar    Linkedin    Website  

Research Interests and Achievements

Dr. Wang is an Assistant Professor (Tenure-Track) at the Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore. His research focuses on developing trustworthy and clinically applicable artificial intelligence for ophthalmology and broader healthcare, particularly in vision–language models, multimodal learning, and trustworthy AI. He develops scalable and clinician-friendly systems to address key challenges in real-world healthcare, including data heterogeneity, limited annotations, and model reliability.


Dr. Wang has published in leading journals and conferences including Nature Communications, Cell Reports Medicine, npj Digital Medicine, IEEE TPAMI, IEEE TMI, CVPR, and MICCAI. His work has been recognised with multiple international awards and focuses on advancing reliable and clinically deployable AI systems for real-world healthcare.


Selected Publications

  • Wang M, et al. Enhancing diagnostic accuracy in rare and common fundus diseases with a knowledge-rich vision-language model. Nature Communications, 2025, 16(1): 5528.
  • Wang M, et al. Uncertainty-inspired open set learning for retinal anomaly identification. Nature Communications, 2023, 14(1): 6757.
  • Wang M, et al. MsTGANet: Automatic Drusen Segmentation from Retinal OCT Images. IEEE Transactions on Medical Imaging, vol.41, no.2, pp.394-406, 2022.
  • Wang M, et al. Semi-Supervised Capsule cGAN for Speckle Noise Reduction in Retinal OCT Images. IEEE Transactions on Medical Imaging, vol. 40, no. 4, pp. 1168–1183, 2021.
  • Lin T*, Wang M*, et al. Efficiency and safety of automated label cleaning on multimodal retinal images. npj Digital Medicine, 2025, 8(1): 10. *Co-first author.
  • Peng Y*, Lin A*, Wang M*, et al. Enhancing AI reliability: A foundation model with uncertainty estimation for optical coherence tomography-based retinal disease diagnosis. Cell Reports Medicine, 2025, 6(1). *Co-first author.
  • Wang L*, Wang M*, et al. Say no to freeloader: Protecting intellectual property of your deep model. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024, 46(12): 11073-11086. *Co-first author.
  • Wang L*, Wang M*, et al. Vision-language model IP protection via prompt-based learning. Proceedings of the Computer Vision and Pattern Recognition Conference. CVPR 2025: 9497-9506. *Co-first author.
  • Wang L*, Wang M*, et al. Model barrier: A compact un-transferable isolation domain for model intellectual property protection. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. CVPR 2023: 20475-20484. *Co-first author.
  • Wang M, et al. Federated uncertainty-aware aggregation for fundus diabetic retinopathy staging. International Conference on Medical Image Computing and Computer-Assisted Intervention. MICCAI 2023: 222-232.