About Me

Hi, I am Yinghuan. I received my B.Sc. and Ph.D. degree both in Computer Science at Nanjing University in 2007 and 2013, respectively. Currently, I am an Associate Professor in the Department of Computer Science and Technology at Nanjing University, and a member of the National Key Laboratory for Novel Software Technology. Also, I am a member of the Reasoning and Learning Research Group, led by Prof. Yang Gao.

In 2011-2012, I visited the IDEA Lab of the University of North Carolina at Chapel Hill (UNC) under the support from the China Scholarship Council (CSC), and worked with Prof. Dinggang Shen. In 2016, I returned to the IDEA Lab for a three months visiting. Also, I spent two months in 2014 as a Visiting Scholar at the Data Science Lab of the University of Technology, Sydney (UTS), working with Prof. Longbing Cao.

Currently, our interests lie broadly in machine learning, pattern recognition, computer vision, and medical image analysis.

Specifically, we have been focusing on developing theories, models, and methods for semi-supervised learning, weakly-supervised learning, domain adaptation, and domain generalization. Our goal is to create efficient and effective solutions to these challenges. We have also been developing machine learning-based tools to help address data analysis problems in medical imaging and clinical data. We hope that these tools can contribute towards building real-world systems for use in clinical scenarios.

Chinese Version (中文简介)


  • 目前课题组招收2024年入学研究生名额已经用完, 感谢各位同学对课题组的关注.

  • [Sept, 2023] Three papers have been accepted by TOMM, TPAMI, and NeurIPS 2023.

  • [July, 2023] We have 7 papers accepted by ICCV 2023. Congratulations to Jian, Zekun, Jintao, Lihe, Yue, Guan, Xiran and all the collaborators.

  • [May, 2023] Congratulations to Lihe and Ziqi for Excellent Master Thesis (Nominee) of Department of Computer Science and Technology of Nanjing University. (祝贺丽鹤、子奇获得2023年度南京大学计算机科学与技术系优秀硕士论文提名)

  • [May, 2023] To serve as Area Chair of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.

  • [Apr, 2023] 获评中国人工智能学会—华为 MindSpore 学术奖励基金优秀结题项目.

  • [Feb, 2023] Three papers about DG Classification, Semi-supervised Learning and Barely-supervised Medical Image Segmentation have been accepted by CVPR 2023.

  • [Sep, 2022] One paper about Barely Supervised Medical Image Segmentation has been accepted by TMI.

  • [Sep, 2022] One paper about Barely-supervised Learning has been accepted by NeurIPS 2022.

  • [Mar, 2022] 智能重症可解释评估模型 TSOFA 已上线( A Time-Incorporated SOFA-Based Explainable Machine Learning Model for Mortality Prediction)与中国人民解放军东部战区总院重症医学科合作

  • [Mar, 2022] Three papers about Semi-supervised Learning and DG Segmentation are accepted by CVPR 2022.

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