更新日期：2018年8月31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 副教授 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 **
个人主页 http://www.scholat.com/wuqingyao


个人简介
吴庆耀现担任华南理工大学软件学院副院长、副教授、博士生导师，IEEE，CCF会员，YOCSEF委员，珠江科技新星人才计划、广东省教育厅创新青年人才、深圳市科技进步二等奖获得者。于2007年获得华南理工大学软件工程学士学位，于2009和2013年在哈尔滨工业大学获得计算机科学硕士与博士学位。自2013年12月到2015年3月，在新加坡南洋理工大学从事博士后研究，并于2015年3月全职回国工作，目前主要研究方向为数据挖掘，具体包括跨媒体异构数据分析、视觉与自然语言融合、知识图谱挖掘等，目前已在相关方向发表近50篇高水平学术论文。以第一作者或通讯作者发表的论文包括：IEEE TNNLS(2篇)，IEEE TKDE(2篇)，IEEE/ACM TCBB，IEEE TNB，IEEE IS，Knowledge-based Systems(3篇) )，BMC Genomic(2篇)，KAIS(2篇)，SIGKDD'18，ICML'18， IJCAI'18，AAAI'18，CVPR'18，ACML'18，IJCAI'17，ICDM'17，ECCV'17，SDM'14。
工作经历
2015.03--至今 华南理工大学软件学院 副教授
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、深圳市科技进步二等奖获得者
社会、学会及学术兼职
国际学术会议任职：
担任国际会议委员会成员：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国家自然科学基金面上基金
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广东省公益研究与能力建设专项
2017-2018广东省协同创新与平台环境建设专项
2017-2018 CCF-腾讯犀牛鸟基金项目
2017-2018中央高校基本科研业务重点项目
2016-2017计算机软件新技术国家重点实验室开放课题
2016-2017计算机科学国家重点实验室开放课题
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（*代表通讯作者 #代表共同一作）
1.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)
2.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:2.775)
3.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:2.775)
4.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)
5.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:2.596)
6.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:2.158)
7.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), DOI: 10.1109/TCBB.2017.** (IF: 2.428)
8.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)
9.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:2.775)
10.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: 4.396)
11. 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:4.396)
12.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: 4.396)
13.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: 2.247)
14.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:2.247)
15.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: 4.122)
16.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)
17.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)
18.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)
19.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)
20.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)
21.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, 2015
22.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)
23.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)
24.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)
25.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)
26.Michael K. Ng, Qingyao Wu, Chenyang Shen, "A fast Markov chain based algorithm for MIML learning", Neurocomputing, 216 (5), 763-777, 2016 (IF:3.241)
27.Yunming Ye, Qingyao Wu, K.P.Chow, Lucas C.K. Hui, and S.M. Yiu. "Unknown Chinese Word Extraction based on Variety of Overlapping Strings", Information Processing and Management (IPM), 49(2): 497-512, 2013 (IF:3.444)
28.Tianyong Hao, Wenxiu Xie, Qingyao Wu, Heng Weng, Yingying Qu. Leveraging Question Target Word Features through Semantic Relation Expansion for Answer Type Classification. Knowledge-Based Systems. 133(1), pp.43-52, 2017 (IF: 4.396)
29.Thanh-Tung Nguyen, Joshua Z. Huang, Qingyao Wu, Thuy T. Nguyen and Mark J. Li. "Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests" BMC Genomics, 16(Suppl 2):S5, 2015 (IF: 3.730)

会议论文
1.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), 2018
2.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), 2018
3.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), 2018
4.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), 2018
5.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), 2018
6.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-18), 545-560, 2018
7.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, 3252-3258
8.Chao Han#, Qingyao Wu#, Jiezhang Cao, Michael K. Ng, Mingkui Tan, Jian Chen, "Tensor based Relations Ranking and Collective Classification for Multi-relational Data ", In Proceeding of IEEE Conference on Data Mining (ICDM 2017), 2017 (# co-first authors)
9.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), 2017
10.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)
11.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 Dec
12.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 April
13.Ruichao Shi, Qingyao Wu*, Yunming Ye, and Shen-Shyang Ho. "A Generative Model with Network Regularization for Semi-Supervised Collective Classification", SDM-2014
14.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)
15.Qingyao Wu, Yunming Ye, Xiaofeng Zhang and Shen-Shyang Ho. "Cluster Tree based Multi-Label Classification for Protein Function Prediction". IEEE BIBM-2013,
16.Qingyao Wu, Yunming Ye, Yang Liu, and Michael Ng. "Stratified Random Forest for Genome-wide Association Study", IEEE BIBM-2012, pp.10-15, 2011
17.Xutao Li, Yunming Ye, Qingyao Wu and Michael Ng. "MultiFacTV: Finding Modules from Higher-order Gene Expression Profiles with Time Dimension", IEEE BIBM-2012, pp. 53-58, 2012
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