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更新日期：2019年11月21日 姓 名 吴庆耀 性 别 男 出生年月 1984年6月 籍贯 民 族 政治面貌 最后学历 博士研究生 最后学位 技术职称 教授 导师类别 博、硕导 行政职务 副院长 Email qyw@scut.edu.cn 工作单位 软件学院 邮政编码 510006 通讯地址 广州市番禺区广州大学城华南理工大学 单位电话 13822289840 个人主页 http://www.scholat.com/wuqingyao 个人简介 吴庆耀，华南理工大学软件学院副院长、教授、博士生导师，YOCSEF广州委员，珠江科技新星人才计划、广东省教育厅创新青年人才，Elsevier国际期刊Software Impacts副主编。2015年至今在华南理工大学软件学院从事教学和科研工作，2018年通过教授评审后，被聘为教授，博导，2018年至今任华南理工大学软件学院副院长。主要研究方向为跨媒体异构数据智能、计算机视觉与自然语言处理，目前已在相关方向发表近50多篇高水平学术论文。主持国家基金项目2项，广东省重点研发项目1项，广东省科技专项2项，珠江新星项目1项，广东省教育厅青年创新人才项目1项，腾讯犀牛鸟基金项目2项。授权与申请发明专利7项，软件著作权7项；获2018年度广东省自然科学奖二等奖；2016年度深圳市自然科学奖二等奖。 工作经历 2015.03--2019.09  华南理工大学软件学院 副教授2018.09--至今   华南理工大学软件学院 教授 教育经历 2009.09—2014.01   哈尔滨工业大学深圳研究生院 计算机软件与理论 工学博士2007.09—2009.09   哈尔滨工业大学深圳研究生院 计算机科学与技术 工学硕士2003.09—2007.09   华南理工大学 软件工程 工学学士 获奖、荣誉称号 珠江科技新星人才计划、广东省教育厅创新青年人才、广东省自然科学奖二等奖、深圳市科技进步二等奖 社会、学会及学术兼职 Elsevier国际期刊Software Impacts副主编。国际学术会议任职：担任国际会议委员会成员：IJCAI-2019，AAAI-2019，NIPS-2019，NIPS-2018，AAAI-2018，InCoB-2018，InCoB-2017，NIPS-2016，ADMA-2016，GIW-2016。担任国际期刊审稿人：IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Multimedia, IEEE Intelligent Systems, IEEE Transactions on Image Processing, ACM Transactions on Intelligent Systems and Technology, Information Science, Neural Networks, Pattern Recognition, Neurocomputing, Knowledge-Based Systems, IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Transactions on Systems, Man, and Cybernetics--Systems, Bioinformatics, Data Mining and Knowledge Discovery. 研究领域 跨媒体异构数据分析、视觉与自然语言融合、知识图谱挖掘、深度学习应用等 科研项目 2019-2022广东省重点研发项目2019-2022国家自然科学基金面上基金2019-2020 CCF-腾讯犀牛鸟基金滚动项目2016-2018国家自然科学基金青年基金2017-2018广州市珠江新星项目2017-2018广东省科技专项--公益研究与能力建设2017-2018广东省科技专项--协同创新与平台环境建设2017-2018 CCF-腾讯犀牛鸟基金项目2016-2017广东省教育厅青年创新人才2015-2016中央高校基本科研业务杰青项目 发表论文 期刊论文1. Xiaojun Chen, Renjie Chen, Qingyao Wu*, Yixiang Fang, Feiping Nie, Zhexue Huang, "LABIN: Balanced Min Cut for Large-scale Data", IEEE Transactions on Neural Networks and Learning Systems (TNNLS), TNNLS, 2019,  doi: 10.1109/TNNLS.2019.29094252. Hanrui Wu; Yuguang Yan; Yuzhong Ye; Michael K Ng; Qingyao Wu*, "Geometric Knowledge Embedding for Unsupervised Domain Adaptation", Knowledge-Based Systems, in Press3. Mingkui Tan, Yuguang Yan, Jiezhang Cao, Qingyao Wu, "Learning Sparse PCA on Stiefel Manifold via Stabilized ADMM Method", IEEE  Transactions on Knowledge and Data Engineering, in Press4. Runhao Zeng, Chuang Gan, Peihao Chen, Wenbing Huang, Qingyao Wu, Mingkui Tan, "Breaking Winner-takes-all: Iterative-winners-out Networks for Weakly Supervised Temporal Action Localization", IEEE Transactions on Image Processing, in Press5. Fan Lyu, Qi Wu, Fuyuan Hu, Qingyao Wu, Mingkui Tan, Attend and Imagine: Multi-label Image Classification with Visual Attention and Recurrent Neural Networks, to appear in IEEE Transactions on Multimedia, in Press6. Hanrui Wu, Yuguang Yan, Michael Ng, Huaqing Min, Qingyao Wu*, "Online Heterogeneous Transfer Learning by Knowledge Transition", ACM Transactions on Intelligent Systems and Technology, 20197. Yuguang Yan, Qingyao Wu*, Mingkui Tan*, Michael Ng, Huaqing Min, Ivor Tsang, "Online Heterogeneous Transfer by Hedge Ensemble of Offline and Online Decisions", IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 29(7), pp. 3252-3263, 2018 (IF:7.982)8. Qingyao Wu, Hanrui Wu, Xiaoming Zhou, Mingkui Tan, Yonghui Xu, Yuguang Yan, Tianyong Hao, "Online Transfer Learning with Multiple Homogeneous or Heterogeneous Sources", IEEE Transactions on Knowledge and Data Engineering (TKDE), 29(7), pp.1494-1507, 2017 JULY (IF:3.857)9. Qingyao Wu, Mingkui Tan, Hengjie Song, Jian Chen, Michael K. Ng. "ML-Forest: A Multi-label Tree Ensemble Method for Multi-Label Classification", IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(10), 2016, Oct (IF:2.067) (IF:3.857)10. Qingyao Wu*, Yunming Ye, Haijun Zhang, Tommy W.S.Chow, and Shen-Shyang Ho. "ML-TREE: A Tree-Structure Based Approach to Multi-Label Learning", IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 26(3): 430-443, 2015, Mar. (IF:6.108) (IF:7.982)11. Qingyao Wu, Michael Ng, and Yunming Ye. "Co-Transfer Learning Using Coupled Markov Chains with Restart", IEEE Intelligent Systems, 29(4), pp.26-33, 2014 (IF:4.464)12. Qingyao Wu, Yunming Ye, Yang Liu, and Michael K. Ng. "SNP Selection and Classification of Genome-wide SNP Data Using Stratified Sampling Random Forests", IEEE Transactions on Nanobioscience, 11(3), 216-227, 2012 (IF:1.927)13. Xiaojun Chen, Joshua Z. Huang, Qingyao Wu*, Min Yang "Subspace Weighting Co-Clustering of Gene Expression Data", IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 16(2), 352-364, April 2019 (IF: 2.896)14. Xutao Li, Michael K. Ng, Gao Cong, Yunming Ye, and Qingyao Wu, "MR-NTD: Manifold Regularization Nonnegative Tucker Decomposition for Tensor Data Dimension Reduction and Representation", IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 28(8), 1787-1800, 2017 (IF: 7.982)15. Yonghui Xu, Sinno Pan, Hui Xiong, Qingyao Wu, Yonghua Luo, Huaqing Min, Henjie Song, "A Unified Framework for Metric Transfer Learning", IEEE Transactions on Knowledge and Data Engineering (TKDE), 29(6),1158-1171, 2017 JUNE (IF:3.857)16. Qingyao Wu, Michael Ng, Yunming Ye, Xutao Li, and Yan Li. "Multi-Label Collective Classification via Markov Chain Based Learning Method", Knowledge-Based Systems, 63: 1-14, 2014 (IF: 5.101)17. Qingyao Wu*, Yunming Ye, Haijun Zhang, Michael Ng, Xutao Li, Shen-Shyang Ho. "ForesTexter: An Efficient Random Forest Algorithm for Imbalanced Text Categorization", Knowledge-Based Systems, 67: 105-116, 2014 (IF:5.101)18. Qingyao Wu, Mingkui Tan, Xutao Li, Huaqing Min, Ning Sun*, "NMFE-SSCC: Non-negative matrix factorization ensemble for semi-supervised collective classification", Knowledge-Based Systems, 89 (2015): 160-172. (IF: 5.101)19. Qingyao Wu, Xiaoming Zhou, Yuguang Yan, Hanrui Wu, Huaqing Min, "Online Transfer Learning by Leveraging Multiple Source Domains" Knowledge and Information Systems, 52(3), pp 687-707, 2017, Sep (IF: 2.397)20. Qingyao Wu, Michael Ng, and Yunming Ye. "Markov-MIML: A Markov Chain Based Multi-Instance Multi-Label Learning Algorithm", Knowledge and Information Systems, 37(1): 83-104, 2013 (IF:2. 397) 21. Yonghui Xu, Huaqing Min, Qingyao Wu*, Henjie Song, "Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction", Scientific Reports, 7:41831, 2017 (IF: 4.011)22. Qingyao Wu, Yunming Ye, Shen-Shyang Ho and Shuigeng Zhou. "Semi-Supervised Multi-label Collective Classification Ensemble for Functional Genomics", BMC Genomics, 15 (Suppl 9):S17, 2014 (IF:3.730)23. Xutao Li, Yunming Ye, Michael Ng and Qingyao Wu*. "MultiFacTV: Module Detection from Higher-order Time Series Biological Data", BMC Genomics, 14(S4), 2013 (IF: 3.730)24. Qingyao Wu, Zhenyu Wang, Chunshan Li, Yunming Ye, Yueping Li, and Ning Sun. "Protein functional properties prediction in sparsely-label PPI networks through Regularized non-negative matrix factorization", BMC Systems Biology, 9 (Suppl 1):S9, 2015 (IF:2.050)25. Qingyao Wu, Yunming Ye, Michael Ng, Shen-Shyang Ho and Ruichao Shi. "Collective prediction of protein functions from protein-protein interaction networks", BMC Bioinformatics, 15(S9), no. Suppl 2, 2014 (IF:2.213)26. Renjie Chen, Ning Sun, Xiaojun Chen, Min Yang and Qingyao Wu*, "Supervised Feature Selection With a Stratified Feature Weighting Method", IEEE Access, 6 (2018): 15087-15098 (IF:3.557)27. Qingyao Wu, Jian Chen, Shen-Shyang Ho, Xutao Li, Huaqing Min, Chao Han, "Multi-Label Regularized Generative Model for Semi-Supervised Collective Classification in Large-Scale Networks", Big Data Research, 2 (4), 187-201, 201528. Chao Han, Yunkun Tan, Jinhui Zhu, Yong Guo, Jian Chen, Qingyao Wu*, "Online feature selection of Class Imbalance via PA algorithm" Journal of Computer Science and Technology (JCST), 31(4): 673-682, 2016 (IF: 0.878)29. Chao Han, Jian Chen, Qingyao Wu*, Shuai Mu, Huaqing Min, "Sparse Markov Chain based Semi-Supervised Multi-Instance Multi-Label Method for Protein Function Prediction", Journal of Bioinformatics and Computational Biology (JBCB), 13(05), 2015. (IF: 0.991)30. Yonghui Xu, Huaqing Min, Hengjie Song and Qingyao Wu*, " Multi-Instance Multi-Label Distance Metric Learning for Genome-Wide Protein Function Prediction", Computational Biology and Chemistry, 11(5):891-902, 2016 (IF: 1.412)31. Yunming Ye, Qingyao Wu, Joshua Zhexue Huang, Michael K. Ng and Xutao Li. "Stratified Sampling for Feature Subspace Selection in Random Forest for High Dimensional Data", Pattern Recognition (PR), 46(3): 769-787, 2013 (IF:3.962) 会议论文1. Chi Zhang, Guosheng Lin, Fayao Liu, Jiushuang Guo, Qingyao Wu, Rui Yao, "Pyramid Graph Networks with Connection Attentions for Region-Based One-Shot Semantic Segmentation", ICCV 20192. Min Yang, Lei Chen, Xiaojun Chen, Qingyao Wu, Wei Zhou, Ying Shen, "Knowledge-enhanced Hierarchical Attention for Community Question Answering with Multi-task and Adaptive Learning", IJCAI 20193. Shihao Zhang, Yuguang Yan, Pengshuai Yin, Zhen Qiu, Wei Zhao, Guiping Cao, Wan Chen, Jin Yuan, Risa Higashita, Qingyao Wu, Mingkui Tan, Jiang Liu. “Guided M-Net for High-resolution Biomedical Image Segmentation with Weak Boundaries and Noise. OMIA. 2019 (best paper)4. Yifan Zhang, Hanbo Chen, Ying Wei, Peilin Zhao, Jiezhang Cao, Mingkui Tan, Qingyao Wu, Xinjuan Fan, Xiaoying Lou, Hailing Liu, Jinlong Hou, Xiao Han, Jianhua Yao, Junzhou Huang, "From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification", MICCAI 20195. Shihao Zhang, Huazhu Fu, Yuguang Yan, Yubing Zhang, Qingyao Wu, Ming Yang, Mingkui Tan, Yanwu Xu, "Attention Guided Network for Retinal Image Segmentation", MICCAI 20196. Pengshuai Ying#, Qingyao Wu#, Mingkui Tan, Ming Yang, Yubing Zhang, Huaqing Min, Yanwu Xu, "PM-NET: Pyramid Multi-Label Network for Optic Disc and Cup Segmentation", MICCAI 20197. Yuguang Yan, Mingkui Tan, Yanwu Xu, Jiezhang Cao, Michael K. Ng, Huaqing Min, Qingyao Wu*, Oversampling for Imbalanced Data via Optimal Transport, Association for the Advancement of Artificial Intelligence (AAAI-19), 20198. Zhuangwei Zhuang, Mingkui Tan, Bohan Zhuang, Jing Liu, Yong Guo, Qingyao Wu, Junzhou Huang, Jinhui Zhu "Discrimination-aware Channel Pruning for Deep Neural Networks", Thirty-second Conference on Neural Information Processing Systems (NIPS), 20189. Junhong Huang, Mingkui Tan, Yuguang Yan, Chunmei Qing, Qingyao Wu, Zhuliang Yu, Dong Xu "Cartoon-to-Photo Facial Translation with Generative Adversarial Networks", ACML, 201810. Jiezhang Cao#, Yong Guo#, Qingyao Wu#, Chunhua Shen, Mingkui Tan*, "Adversarial Learning with Local Coordinate Coding", Proceedings of the 35th International Conference on Machine Learning (ICML 2018), 201811. Yifan Zhang, Peilin Zhao, Jiezhang Cao, Wenye Ma, Junzhou Huang, Qingyao Wu*, Mingkui Tan "Online Adaptive Asymmetric Active Learning for Budgeted Imbalanced Data", ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2018), 201812. Yuguang Yan, Wen Li, Hanrui Wu, Huaqing Min, Mingkui Tan*, Qingyao Wu*, "Semi-Supervised Optimal Transport for Heterogeneous Domain Adaptation", Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI-2018), 201813. Chaorui Deng, Qi Wu, Qingyao Wu*, Fuyuan Hu, Fan Lyu, Mingkui Tan*, "Visual Grounding via Accumulated Attention", In Proceeding of IEEE Conference on Computer Vision and Pattern Recognition (CVPR-2018), 201814. Yong Guo#, Qingyao Wu#, Jian Chen, Mingkui Tan, "Memorized Batch Normalization for Training Deep Neural Networks", Association for the Advancement of Artificial Intelligence (AAAI-18), 201815. Renjie Chen, Xiaojun Chen, Guowen Yuan, Wenya Sun and Qingyao Wu, "A Stratified Feature Ranking Method for Supervised Feature Selection", Association for the Advancement of Artificial Intelligence (AAAI-18), 2018 (Student Abstract Paper)16. Jiezhang Cao#, Qingyao Wu#, Yuguang Yan, Li Wang, Mingkui Tan, "On the Flatness of Loss Surface for Two-layered ReLU Networks", the 9th Asian Conference on Machine Learning (ACML-17), 545-560, 201717. Yuguang Yan, Wen Li, Michael Ng, Mingkui Tan, Hanrui Wu, Huaqing Min, Qingyao Wu*, "Learning Discriminative Correlation Subspace for Heterogeneous Domain Adaptation", Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-2017), 2017, 3252-325818. Chao Han#, Qingyao Wu#, Jiezhang Cao, Michael K. Ng, Mingkui Tan, Jian Chen, "Tensor based Relations Ranking for Multi-relational Collective Classification", In Proceeding of IEEE Conference on Data Mining (ICDM 2017), 2017 (# co-first authors)19. Xiaojun Chen, Guowen Yuan, JianZhe Zhang, Joshua Zhexue Huang, Qingyao Wu, A Self-Balanced Min-Cut Algorithm for Image Clustering, IEEE International Conference on Computer Vision (ICCV 2017), 201720. Yuguang Yan, Qingyao Wu*, Mingkui Tan, Huaqing Min, "Online Heterogeneous Transfer Learning by Weighted Offline and Online Classifiers", ECCV-2016 workshop on TASK Transferring and Adapting Source Knowledge in Computer Vision, 2016 (Honorable Mention Paper Award)21. Feng Wu, Qiong Liu*, Tianyong Hao, Xiaojun Chen, and Qingyao Wu*, "Online Multi-Instance Multi-Label Learning for Protein Function Prediction", IEEE BIBM-2016, 780-785, 2016 Dec22. Yongxin Liao, Shenxi Yuan, Jian Chen, Qingyao Wu* and Bin Li, "Joint Classification with Heterogeneous labels using random walk with dynamic label propagation", V9651, pp 3-13, PAKDD-2016, 2016 April23. Ruichao Shi, Qingyao Wu*, Yunming Ye, and Shen-Shyang Ho. "A Generative Model with Network Regularization for Semi-Supervised Collective Classification", SDM-201424. Michael Ng, Qingyao Wu and Yunming Ye. "Co-Transfer Learning via Joint Transition Probability Graph Based Method". SIGKDD-2012 Workshop on CDKD, pp.1-9, 2012 (Selected Best Paper to IEEE IS Special Issue) 教学活动 《计算机网络》本科生专业必修课《机器学习》本科生专业选修课《机器学习》研究生专业选修课