General

Cheng Li is an Associate Professor at the Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences. She received her Ph.D. from Nanyang Technological University (NTU), Singapore, in April 2017 and joined SIAT in November of the same year. Her research focuses on deep learning, medical imaging, medical image analysis, and multi-modal fusion. She has published over 50 academic papers in high-impact journals such as the Nature series and IEEE Transactions.

Research Areas

Deep learning, Medical image analysis, Multi-modal fusion

Education

  1. Aug. 2012 – Apr. 2017, Ph.D. in Environmental Life Sciences, Nanyang Technological University, Singapore
  2. Sept 2008 - Jul 2012, Bachelor in Mechanical Engineering, University of Science and Technology of China, China

Experience

  1. Jan. 2026 - present, Associate Professor,  Paul C. Lauterbur Research Center, SIAT, Chinese Academy of Sciences
  2. Aug. 2020 - Dec. 2025, Assistant Professor,  Paul C. Lauterbur Research Center, SIAT, Chinese Academy of Sciences
  3. Nov. 2017 - Aug. 2020, PostDoc, Paul C. Lauterbur Research Center, SIAT, Chinese Academy of Sciences

Publications

  1. Cheng Li, Weijian Huang, Hao Yang, Jiarun Liu, Yong Liang, Shanshan Wang*. Medical vision-language modeling with semantic interaction and adaptive refinement prompting for bias mitigation, IEEE Journal of Biomedical and Health Informatics, 2025 (Early Access). (JCR-1, IF=6.8)
  2. Weijian Huang, Cheng Li*, Yousuf Babiker M. Osman, Shanshan Wang*. A lightweight network with uncertainty-guided latent space refinement for multi-modal brain tissue and tumor extraction, IEEE Transactions on Computational Biology and Bioinformatics, 2025 (Early Access). (JCR-1, IF=3.4)
  3. Ruoyou Wu, Cheng Li, Juan Zou, Xinfeng Liu, Hairong Zheng, Shanshan Wang*. Generalizable reconstruction for accelerating MR imaging via federated learning with neural architecture search, IEEE Transactions on Medical Imaging, 44(1): 106-117, 2025. (JCR-1, IF=9.8)
  4. Alou Diakite, Cheng Li, Yousuf Babiker M. Osman, Zan Chen, Yiang Pan, Jiawei Zhang, Tao Tan, Hairong Zheng, Shanshan Wang*. Dual-uncertainty guided multimodal MRI-based visual pathway extraction, IEEE Transactions on Biomedical Engineering, 72(6): 1993-2000, 2025. (JCR-1, IF=4.5)
  5. Yousuf Babiker M. Osman, Cheng Li, Nazik Elsayed, Alou Diakite, Shuqiang Wang, Shanshan Wang*. Enhancing semi-supervised learning for fine-grained 3D cerebrovascular segmentation with cross-consistency and uncertainty estimation, Medical Physics, 52:e70018, 2025. (JCR-1, IF=3.9)
  6. Nazik Elsayed#, Yousuf Babiker M. Osman#, Cheng Li#, Jiarun Liu, Weixin Si, Jiong Zhang, Shanshan Wang*. Automating vessel segmentation in the heart and brain: A trend to develop multi-modality and label-efficient deep learning techniques, Biomedical Signal Processing and Control, 109: 108028, 2025. (JCR-2, IF=4.9)
  7. Weijian Huang#, Cheng Li#, Hong-Yu Zhou, Hao Yang, Jiarun Liu, Yong Liang, Hairong Zheng, Shaoting Zhang, Shanshan Wang*. Enhancing representation in radiography-reports foundation model: A granular alignment algorithm using masked contrastive learning, Nature Communications, 15:7620, 2024. (JCR-1, IF=16.1)
  8. Weijian Huang#, Cheng Li#, Hao Yang, Jiarun Liu, Yong Liang, Hairong Zheng, Shanshan Wang*. Enhancing the vision-language foundation model with key semantic knowledge-emphasized report refinement, Medical Image Analysis, 97: 103299, 2024. (JCR-1, IF=11.9)
  9. Yousuf Babiker M Osman#, Cheng Li#, Weijian Huang, Shanshan Wang*. Collaborative learning for annotation-efficient volumetric MR image segmentation, Journal of Magnetic Resonance Imaging, 60(4): 1604-1614, 2024. (JCR-1, IF=4.4)
  10. Yousuf Babiker M Osman#, Cheng Li#, Weijian Huang, Shanshan Wang*. Sparse annotation learning for dense volumetric MR image segmentation with uncertainty estimation, Physics in Medicine and Biology, 2023, 69(1): 015009. (JCR-1, IF=3.4)
  11. Cheng Li, Wen Li, Chenyang Liu, Hairong Zheng, Jing Cai, Shanshan Wang*. Artificial intelligence in multiparametric magnetic resonance imaging: A review, Medical Physics, 2022, 49(10): e1024-e1054. (JCR-1, IF=3.9)
  12. Diping Song#, Fei Li#, Cheng Li#, Jian Xiong, Junjun He, Xiulan Zhang*, Yu Qiao*. Asynchronous feature regularization and cross-modal distillation for OCT based glaucoma diagnosis, Computers in Biology and Medicine, 2022, 151: 106283. (JCR-1, IF=6.7)
  13. Shanshan Wang#*, Cheng Li#*, Rongpin Wang#, Zaiyi Liu, Meiyun Wang, Hongna Tan, Yaping Wu, Xinfeng Liu, Hui Sun, Rui Yang, Xin Liu, Jie Chen, Huihui Zhou, Ismail Ben Ayed, Hairong Zheng*. Annotation-efficient deep learning for automatic medical image segmentation. Nature Communications, 2021, 12: 5915. (JCR-1, IF=16.1)
  14. Cheng Li, Jingxu Xu, Qiegen Liu, Yongjin Zhou, Lisha Mou, Zuhui Pu, Yong Xia, Hairong Zheng, Shanshan Wang*. Multi-view mammographic density classification by dilated and attention-guided residual learning, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021, 18(3): 1003-1013. (JCR-1, IF=3.4)
  15. Hui Sun#, Cheng Li#, Boqiang Liu, Zaiyi Liu, Meiyun Wang, Hairong Zheng, David Dagan Feng, Shanshan Wang*. AUNet: Attention-guided dense-upsampling networks for breast mass segmentation in whole mammograms, Physics in Medicine and Biology, 2020, 65(5): 055005. (JCR-1, IF=3.4)