Professor

Medical AI ReSearch (MARS) Group
Life Sciences Institute   生命科学研究院
Guangxi Medical University   广西医科大学

Email: leeyuexiang@163.com

Biography

Yuexiang LI currently works in Life Sciences Institute, Guangxi Medical University (GXMU) as a full professor. He is the academic leader of the discipline of artificial intelligence, and leads the Medical AI ReSearch (MARS) group in the university. Prof. Li graduated from the University of Nottingham, United Kingdom with a Ph.D., and has been engaged in research on intelligent analysis and processing of medical images (including microscopic images, pathological slices and multimodal medical images) for more than ten years. Before joining GXMU, he worked in Tencent Jarvis Lab as a senior researcher and got excellent connections to industry. Prof. Li has published multiple academic papers in top medical image processing journals (e.g., TMI, MIA) and top conferences (e.g., AAAI, ECCV, MICCAI). He is also the reviewer for TPAMI, TMI, MICCAI and the program chair for world-wide conferences.

Openings

I am always looking for talented and self-motivated students to join my research group to work in the fields of medical image analysis/computer vision/pattern recognition.

2024 硕士/博士招生中，欢迎生物医学工程/医学相关专业考生报考！

Multiple positions of research assistant and postdoctoral fellow are now available (should be in the fields related to bio-medical engineering/computer science/electronic engineering).

招聘多名研究助理和博士后，待遇从优（博士后年薪25w起），优秀者可获事业编制！（有意者可电邮垂询）

News

Education & Experience

Selected Journal Paper [For full list, please refer to Google Scholar / ResearchGate]

  1. Anomaly detection via gating highway connection for retinal fundus images
    Wentian Zhang#, Haozhe Liu#, Jinheng Xie, Yawen Huang, Yu Zhang, Yuexiang Li*, Raghavendra Ramachandra, Yefeng Zheng Pattern Recognition, 2023. (IF: 8.000)

  2. Unsupervised domain adaptation for medical image segmentation by disentanglement learning and self-training
    Qingsong Xie#, Yuexiang Li#, Nanjun He*, Munan Ning, Kai Ma, Guoxing Wang et al., IEEE Transactions on Medical Imaging (IEEE TMI), 2022. (IF: 11.037)

  3. Beyond mutual information: Generative adversarial network for domain adaptation using information bottleneck constraint
    Jiawei Chen#, Ziqi Zhang#, Xinpeng Xie#, Yuexiang Li*, Tao Xu, Kai Ma, and Yefeng Zheng, IEEE Transactions on Medical Imaging (IEEE TMI), 2021. (IF: 11.037)

  4. DICDNet: Deep interpretable convolutional dictionary network for metal artifact reduction in CT images
    Hong Wang, Yuexiang Li*, Nanjun He, Kai Ma, Deyu Meng*, and Yefeng Zheng, IEEE Transactions on Medical Imaging (IEEE TMI), 2021. (IF: 11.037)

  5. Anomaly detection for medical images using self-supervised and translation-consistent features
    He Zhao, Yuexiang Li*, Nanjun He, Kai Ma, Leyuan Fang, Huiqi Li* et al., IEEE Transactions on Medical Imaging (IEEE TMI), 2021. (IF: 11.037)

Selected Conference Paper [For full list, please refer to Google Scholar / ResearchGate]

  1. Dynamically masked discriminator for GANs
    Wentian Zhang#, Haozhe Liu#, Bing Li*, Jinheng Xie, Yawen Huang, Yuexiang Li*, Yefeng Zheng, Bernard Ghanem, Neural Information Processing Systems (NeurIPS), 2023. (CCF-A)

  2. AdaptiveMix: Improving GAN training via feature space shrinkage
    Haozhe Liu#, Wentian Zhang#, Bing Li*, Haoqian Wu, Nanjun He, Yawen Huang, Yuexiang Li*, Bernard Ghanem, Yefeng Zheng, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. (CCF-A)

  3. Combating mode collapse in GANs via manifold entropy estimation
    Haozhe Liu, Bing Li*, Haoqian Wu, Hanbang Liang, Yawen Huang, Yuexiang Li*, Bernard Ghanem, Yefeng Zheng, AAAI Conference on Artificial Intelligence (AAAI), 2023. (CCF-A)

  4. Adaptive convolutional dictionary network for CT metal artifact reduction
    Hong Wang, Yuexiang Li*, Deyu Meng*, and Yefeng Zheng, International Joint Conference on Artificial Intelligence (IJCAI), 2022. (CCF-A)

  5. A multi-task network with weight decay skip connection training for anomaly detection in retinal fundus images
    Wentian Zhang#, Xu Sun#*, Yuexiang Li#, Haozhe Liu, Nanjun He, Feng Liu* et al., International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), 2022. (CCF-B)

Recent Interns @ Tencent

Teaching

Grants

  1. Participant, Technical Innovation 2030-"New Generation Artificial Intelligence" Project, 5,000,000, 2020-2024
  2. Principle Investigator, Natural Science Foundation of China, 240,000, 2018-2021
  3. Principle Investigator, Postdoctoral Science Foundation of China, 50,000, 2017-2018
  4. Principle Investigator, Nanning City Science and Technology Bureau, 200,000, 2017-2018

Award

  1. First Prize, Cerebral Aneurysm Detection Challenge @ MICCAI, 2020
  2. First Prize, Angle Closure Glaucoma Evaluation Challenge @ MICCAI, 2019
  3. First Prize, HEp-2 Indirect Immuno-Fluorescence Contest @ ICPR, 2016

Professional Services

Collaborators

Last updated by Yuexiang LI on Oct, 2023.

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