薛澄，副教授，硕导。2017年获得香港理工大学博士学位，期间在美国杜克大学进行学术访问。2019-2023年在香港中文大学和香港理工大学担任博士后、研究助理教授。近期研究方向为：医学影像智能分析，手术机器人，多模态大模型，具身智能等。在医学影像分析领域顶刊和顶会TMI，MIA，MICCAI等发表论文十余篇，长期担任多个国际著名期刊会议的编委和审稿人。主持和参与国自然，国自然专项，重点研发计划课题，江苏省自然科学基金。
1. 招收2026级计算机学院/软件学院硕士研究生，欢迎有自我驱动力的学生报名！
2. 欢迎对AI+医学影像感兴趣的本科生跟组进行全面的科研训练。
3. To date, I have no quotas for oversea students.
医学影像智能分析，多模态大模型，具身智能等
Ph. D., Department of Health Technology and Informatics, Hong Kong Polytechnic University. (2012 - 2017)
Visiting Scholar, Department of Electrical and Computer Engineering, Duke University. (2015-2016)
B. Eng., Department of Mechanical Engineering and Automation, Jilin University. (2008 - 2012)
Tenure-Track Associate Professor, School of Computer Science and Engineering, Southeast University. (2023 - present)
Research Assistant Professor, Department of Health Technology and Informatics, Hong Kong Polytechnic University. (2022)
Postdoctoral Researcher, Department of Computer Science and Engineering, Chinese University of Hong Kong (2017 - 2022)
Cheng Xue, Lequan Yu, Pengfei Chen, Qi Dou, Pheng-Ann Heng. Robust medical image classification from noisy labeled data with global and local representation guided co-training. IEEE Transactions on Medical Imaging 41, no. 6 (2022): 1371-1382. (领域顶刊)
Cheng Xue, Lei Zhu, Huazhu Fu, Xiaowei Hu, Xiaomeng Li, Hai Zhang, Pheng-Ann Heng, Global Guidance Network for Breast Lesion Segmentation in Ultrasound Images, Medical image analysis, 70, 101989. (领域顶刊)
Cheng Xue, Qiao Deng, Xiaomeng Li, Qi Dou, and Pheng-Ann Heng. Cascaded Robust Learning at Imperfect Labels for Chest X-ray Segmentation. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI),pp. 579-588. Springer, Cham, 2020. （领域顶会）
Cheng Xue, Qi Dou, Xueying Shi, Hao Chen, and Pheng-Ann Heng. Robust learning at noisy labeled medical images: Applied to skin lesion classification. In 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI), pp. 1280-1283. IEEE, 2019.
Fuk-hay Tang, Cheng Xue, Maria YY Law, Chui-ying Wong, Tze-hei Cho, and Chun-kit Lai. Prognostic Prediction of Cancer Based on Radiomics Features of Diagnostic Imaging: The Performance of Machine Learning Strategies. Journal of Digital Imaging (2023): 1-10. (JCR Q1)
