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, I am broadly interested in medical image analysis, clinical data mining, and also including the other related topics in image processing, computer vision, and machine learning.

In particular, the main goal of our research is to develop the machine learning-based algorithms for the data analysis problems in medical imaging and clinical data. The difficulties in medical data, e.g., complicated connection, unpredictable noise, limited amount and insufficient labeling, pose the considerable challenges for the data analysis. We wish to develop the effective and efficient methods to tackle these challenges. Also, these methods are used to guide the development of the real systems in the clinical scenario.

Chinese Version (中文简介)


  • [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.

  • [Feb, 2022] One paper about DG Classification is accepted by TCSVT 2022.

  • [Dec, 2021] A paper about Self-training and Semi-supervised Learning is accepted as oral by AAAI 2022.

  • [Nov, 2021] 入选中国人工智能学会—华为 MindSpore 学术奖励基金.

  • [Oct, 2021] A talk at "Machine Learning Forum" of NCIIP 2021.

  • [Oct, 2021] A talk at 2021 中国人工智能大会—人工智能核心技术攻坚青年科学家沙龙.

  • [Oct, 2021] One paper about Semi-supervised Segmentation has been accepted by TMI.

  • [Sep, 2021] An invited talk at CAAI-ML Western Forum.

  • [Aug, 2021] One paper about DG Segmentation is accepted by PR.

  • [Aug, 2021] One paper is accepted by NPJ Computational Materials.

  • [Aug, 2021] One paper about UDA Medical Image Segmetation is accepted by TMI.

  • [Jul, 2021] Two papers about Few-shot Segmentation and Style Transfer are accepted by ICCV 2021, both are orals.

  • [Jul, 2021] An invited talk at "Forum of Young Scholars" of CCF-AI 2021.

  • [Jul, 2021] A tutorial of "Effective Medical Image Analysis Models with Efficient Annotations" at ICME 2021.

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