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Yaolei Qi

Ph.D. Student
Southeast University, University of Cambridge
Yaolei710 (at) foxmail.com


Yaolei Qi

I am currently a Ph.D. student in the Department of Computer Science at Southeast University, Nanjing. I am fortunate to be advised by Prof. Guanyu Yang throughout both my master’s and doctoral studies. Prior to this, I completed my bachelor’s degree at Southeast University as well. I am now a visiting student at University of Cambridge supervised by Chao Li.

My research lies at the intersection of Deep Learning and Artificial Intelligence in Medicine – with a special focus on dealing with the tough task in tubular structure analysis that are knowledge-driven and data-efficient. My research interests include medical imaging, weakly-supervised learning, network design, federated learning, foundation model, and computer-assisted diagnosis, etc.

News

Awards

Publications [Google Scholar][DBLP]

  1. ICASSP
    Yuan Zhang, Yaolei Qi, Xiaoming Qi, LLotfi Senhadji, Yongyue Wei, Feng Chen, Guanyu Yang
    IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024.

  2. JBHI
    Xiaoming Qi, Yuting He, Yaolei Qi, Youyong Kong, Guanyu Yang, Shuo Li
    IEEE Journal of Biomedical and Health Informatics, 2023.

  3. ICCV
    Yaolei Qi, Yuting He Xiaoming Qi, Yuan Zhang, Guanyu Yang
    International Conference on Computer Vision (ICCV), 2023.

  4. MICCAI
    Zheng Zhang*, Xiaolei Zhang*, Yaolei Qi, Guanyu Yang (*Equal contribution)
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023.

  5. TIP
    Yaolei Qi*, Han Xu*, Yuting He, Guanyu Li, Zehang Li, Youyong Kong, Jean-Louis Coatrieux, Huazhong Shu, Guanyu Yang, Shengxian Tu (*Equal contribution)
    IEEE Transactions on Image Processing (TIP), Volume 30, 2021.

Invited Talks

Tubular Structure Analysis

Contact

Address: Jiangsu, Nanjing, Sipailou
Lab Location: Sipailou 2
Email: Yaolei710 (at) foxmail.com
Phone: (86) 15051877886



Thanks yaoyao-liu for his very exquisite template.