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)

News

• 课题组招收2025年秋季入学研究生（包括直博生、硕士生、申请考核制博士生）名额已满。非常感谢大家对课题组的关注与支持!

• [July, 2024] One paper has been accepted by ACM MM. Congratulations to Yue.

• [July, 2024] Two papers have been accepted by ECCV 2024. Congratulations to Jiajun and Muyang.

• [Jun, 2024] Congratulations to Gui Guan for Excellent Master Thesis of Department of Computer Science and Technology of Nanjing University. (祝贺桂冠获得2024年度南京大学计算机科学与技术系优秀硕士论文奖). Congratulations to Wang Na for Excellent Master Thesis (Nominee) of Department of Computer Science and Technology of Nanjing University. (祝贺王娜获得2024年度南京大学计算机科学与技术系优秀硕士论文提名奖).

• [May, 2024] 史颖欢获得2024年度南京大学青年五四奖章.

• [Apr, 2024] Two papers about Domain Generalization and Semi-Supervised Medical Image Segmentation have been accepted by TKDE and CVPR 2024. Congratulations to Jian and Qinghe.

• [Feb, 2024] One paper has been accepted by TKDE. Congratulations to Zekun.

• [Dec, 2023] One paper has been accepted by TIP. Congratulations to Na.

• [Dec, 2023] Two papers have been accepted by AAAI 2024. Congratulations to Yue and Taicai.

• [Dec, 2023] 课题组9位同学获得多项研究生奖学金, 7位同学获得南京大学优秀研究生荣誉称号.

• [Dec, 2023] 史颖欢获得南京大学首届优秀研究生德育导师称号.

• [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.

Recent Publication

• 史颖欢, 郭金涛, 李泽昆, 祁磊, 高阳. “ 基于可泛化模型的复杂商务场景数据分析. ” 中国科学基金, 2024.

• Yue Duan, Zhangxuan Gu, Zhenzhe Ying, Lei Qi, Changhua Meng, Yinghuan Shi. “ PC2: Pseudo-Classification Based Pseudo-Captioning for Noisy Correspondence Learning in Cross-Modal Retrieval. ” ACM Conference on Multimedia (ACM MM), 2024. [Code]

• Muyang Qiu, Jian Zhang, Lei Qi, Qian Yu, Yinghuan Shi, Yang Gao. “ The Devil is in the Statistics: Mitigating and Exploiting Statistics Difference for Generalizable Semi-supervised Medical Image Segmentation. ” European Conference on Computer Vision (ECCV), 2024. [Code]

• Jiajun Hu, Jian Zhang, Lei Qi, Yinghuan Shi, Yang Gao. “ Learn to Preserve and Diversify: Parameter-Efficient Group with Orthogonal Regularization for Domain Generalization. ” European Conference on Computer Vision (ECCV), 2024.

• Jian Zhang, Lei Qi, Yinghuan Shi, Yang Gao. “ Exploring Flat Minima for Domain Generalization with Large Learning Rates. ” IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024. [Code]

• Qinghe Ma, Jian Zhang, Lei Qi, Qian Yu, Yinghuan Shi, Yang Gao. “ Constructing and Exploring Intermediate Domains in Mixed Domain Semi-supervised Medical Image Segmentation. ” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024. [Code]

• Zekun Li, Lei Qi, Yawen Li, Yinghuan Shi, Yang Gao. “ Open-Domain Semi-Supervised Learning via Glocal Cluster Structure Exploitation. ” IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024. [Code]

• Na Wang, Lei Qi, Jintao Guo, Yinghuan Shi, Yang Gao. “ Learning Generalizable Models via Disentangling Spurious and Enhancing Potential Correlations. ” IEEE Transactions on Image Processing (TIP), 2024. [Code]

• Yue Duan, Zhen Zhao, Lei Qi, Luping Zhou, Lei Wang, Yinghuan Shi. “ Roll With the Punches: Expansion and Shrinkage of Soft Label Selection for Semi-supervised Fine-grained Learning. ” AAAI Conference on Artificial Intelligence (AAAI), 2024. [Code]

• Taicai Chen, Yue Duan, Dong Li, Lei Qi, Yinghuan Shi, Yang Gao. “ PG-LBO: Enhancing High-dimensional Bayesian Optimization with Pseudo-label and Gaussian Process Guidance. ” AAAI Conference on Artificial Intelligence (AAAI), 2024. [Code]

More Papers

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