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Zekun Li (李泽昆)

Ph.D. Student
Nanjing University
lizekun (at) smail.nju.edu.cn


Short Bio

Currently, I am a Ph.D. student of Department of Computer Science and Technology, Nanjing University. I consider myself extremely fortunate to be pursuing my Ph.D. degree under the supervision of Prof. Yinghuan Shi. Prior to this, I obtained my bachelor’s degree from Nanjing University in 2020.

My research interests primarily focus on machine learning and computer vision. More specifically, I am dedicated to developing efficient and robust learning methods for real-world vision applications.

Affiliations: National Key Laboratory for Novel Software Technology, National Institute of Healthcare Data Science, Reasoning and Learning Research Group.

News

Publications

  1. Open-Domain Semi-Supervised Learning via Glocal Cluster Structure Exploitation
    Zekun Li, Lei Qi, Yawen Li, Yinghuan Shi, Yang Gao
    IEEE Transactions on Knowledge and Data Engineering (TKDE), In Press.
    Paper Code

  2. IOMatch: Simplifying Open-Set Semi-Supervised Learning with Joint Inliers and Outliers Utilization
    Zekun Li, Lei Qi, Yinghuan Shi, Yang Gao
    IEEE/CVF International Conference on Computer Vision (ICCV), 2023.
    Paper Code Poster Slides   Oral Presentation (152/8260=1.8%)

  3. A novel multiple instance learning framework for COVID-19 severity assessment via data augmentation and self-supervised learning
    Zekun Li, Wei Zhao, Feng Shi, Lei Qi, Xingzhi Xie, Ying Wei, Zhongxiang Ding, Yang Gao, Shangjie Wu, Jun Liu, Yinghuan Shi, Dinggang Shen
    Medical Image Analysis (MedIA), Volume 69, 2021.
    Paper



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