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导师:陈健


华南理工大学软件学院 教授、博士生导师。

中国计算机学会数据库专业委员会委员、广东省计算机学会数据库分会理事、秘书长、广东省计算机学会计算智能专业委员会委员、广东省计算机学会大数据专业委员会委员。入选2016年“广东特支计划”科技创新青年拔尖人才,入选2010年广东省“千百十工程”培养对象。担任国际权威期刊ACM Transactions on Knowledge Discovery from Data、IEEE Transactions on Parallel and Distributed Systems,IEEE Transactions on Knowledge and Data Engineering、Knowledge and Information Systems、Journal of Big Data Research、电子学报、软件学报审稿人,先后在多个国际国内学术会议如DASFAA,APWeb,WAIM等国际会议担任程序委员会委员。

陈健教授多年来一直专注于数据库、大数据分析、推荐系统方面的应用基础研究,在高维数据空间索引、移动对象轨迹数据流实时分析、复杂类型数据特征选择、基于语义的推荐算法、推荐系统中的隐私保护与攻击防御等问题上做出了有创新性的工作。近五年来,在包括IEEE Transactions on Knowledge and Data Engineering(TKDE),IEEE Transactions on Parallel and Distributed Systems (TPDS),Knowledge and Information Systems (KAIS)、Distributed and Parallel Databases (DAPD)、Journal of Computer Science and Technology(JCST)、Chinese Journal of Electronics(CJE)、International Journal of Computational Science and Engineering、电子学报、软件学报、计算机研究与发展等国内外重要期刊和ICDE(CCF A类)、AAAI (CCF A类)、KDD(CCF A类)、CIKM(CCF B类)等重要国际会议上发表论文40多篇,SCI/EI/ISTP收录30多篇次。出版译著4部,主编丛书1部,获发明专利授权2项,软件著作权18项。

主持了国家自然科学基金、广东省自然科学基金、香港科技创新署粤港合作、广州市科普项目等十多个项目的研究工作,作为合作单位负责人主持过国家自然科学基金、广东省自然科学基金和广东省高等学校自然科学研究重点项目,作为主要成员参与多项国家自然科学基金、国家科技计划项目、广东省自然科学基金、广东省重大科技专项、广东省科技攻关重点项目等十多个项目的研究工作。

2016年1月至2017年1月、2008年1月至2月、6月至8月在加拿大Simon Fraser University计算机科学学院数据挖掘小组做访问教授,与Jian Pei教授在大数据分析与推荐系统方面展开合作。2002年和2006年期间两次访问新加坡国立大学计算学院EC/DB LAB的邀请,在高维数据空间索引和分布式计算方面与Ooi Beng Chin教授进行了相关方向的合作研究

可以招收软件工程专业工学博士/硕士和软件工程专业工程硕士。


近期论文:

  1. Zeyi Wen, Rao Kotagiri, Bin Li, Jian Chen(通讯作者), Yawen Chen and Rui Zhang. Improving Efficiency of SVM k-fold Cross-validation by Alpha Seeding. In: Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17). (Accepted, CCF A类会议)
  2. Qingyao Wu, Yuguang Yan, Mingkui Tan, Hengjie Song, Jian Chen, Michael K. Ng, Huaqing Min. ML-Forest: A Multi-label Tree Ensemble Method for Multi-Label Classification.IEEE Transactions on Knowledge and Data Engineering. 【Accepted,影响因子2.476, CCF A类期刊】
  3. Jin Huang, Rui Zhang, Rajkumar Buyya, Jian Chen(通讯作者), Yongwei Wu. HEADS-JOIN: Efficient Earth Mover’s Distance Similarity Joins on Hadoop. IEEE Transactions on Parallel and Distributed Systems. 2016, 27(6): 1660 - 1673. 【SCI源刊,影响因子2.661, CCF A类期刊】
  4. Chao Han, Yunkun Tan, Jinhui Zhu, Yong Guo, Jian Chen(通讯作者), Qingyao Wu. Online feature selection of Class Imbalance via PA algorithm. Journal of Computer Science and Technology. 2016, 31(4): 673-682. 【SCI源刊, 影响因子0.475】
  5. Yongxin Liao, Shenxi Yuan, Jian Chen, Qingyao Wu, and Bin Li. Joint Classification with Heterogeneous labels using random walk with dynamic label propagation. In: Proceedings of the 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2016), Auckland, New Zealand, April 19-22, 2016, 3-13. 【EI:20161702311805】
  6. Pengyu Chen(student), Jian Chen, Jin Huang(通讯作者). Multi-user Location-Dependent Skyline Query Based on Dominance Graph. International Journal of Computational Science and Engineering (IJCSE). (Accepted) 【EI源刊】
  7. Jin Huang, Jianzhong Qi, Yabo Xu, Jian Chen. A Privacy-enhancing Model for Location-based Personalized Recommendations. Distributed and Parallel Databases (DAPD). (Online:09 Apr 2014 ) 【SCI源刊】
  8. Jian Chen, Jin Huang, Zeyi Wen, Zhen He, Kerry Taylor, Rui Zhang. Analysis and Evaluation of the Top-k Most Influential Location Selection Query. Knowledge and Information Systems (KAIS). (Accepted) 【SCI源刊, 影响因子2.639, JCR2区】
  9. Jin Huang, Rui Zhang, Rajkumar Buyya and Jian Chen(通讯作者). MELODY-JOIN: Efficient Earth Mover’s Distance Similarity Joins Using MapReduce. In: Proceedings of the 30th International Conference on Data Engineering (ICDE 2014), Chicago, IL, USA April 2014, 808-819.
  10. 黄世平, 黄晋, 陈健(通讯作者), 汤庸. 自动建立信任的防攻击推荐算法研究. 电子学报, 2013 Vol.41 (2): 382-387. 【EI:20131416174642】

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导师:谭明奎


华南理工大学软件学院 教授、博士/硕士研究生导师。

第十三批国家 “青年千人计划”人选。2009年至2014年在新加坡南洋理工大学计算机学院就读博士,2014年至2016年在澳大利亚阿德莱德大学计算机学院供职博士后。研究领域集中于:大数据分析(Big Data Analysis);大规模化 (Large-scale Optimization);深度学习(Deep Learning) ; 机器学习(Machine Learning) ; 压缩传感 (Compressive Sensing);计算机视觉(Computer Vision) 等。

近年来已在International Conference on Machine Learning (ICML)、the Association for the Advance of Artificial Intelligence (AAAI)、International Conference on Computer Vision and Pattern Recognition(CVPR)等国际顶级会议和Journal of Machine Learning Research (JMLR)、Transactions on Neural Networks and Learning Systems (TNNLS) 等国际权威期刊上发表论文20余篇。

可以招收软件工程专业工学博士/硕士和软件工程专业工程硕士。


近期论文:

  1. Qingyao Wu, Mingkui Tan (*Corresponding author), Hengjie Song, Jian Chen, Michael K. Ng. "ML-Forest: A Multi-label Tree Ensemble Method for Multi-Label Classification", accepted by IEEE Transactions on Knowledge and Data Engineering.
  2. Shijie Xiao, Mingkui Tan, Dong Xu, Zhao Yang Dong, "Robust Kernel Low-Rank Representation", IEEE Transactions on Neural Networks and Learning Systems, 2016.
  3. Wei Emma Zhang, Mingkui Tan(*Corresponding author), Quan Z. Sheng and Qinfeng Shi, "Efficient Orthogonal Non-negative Matrix Factorization over Stiefiel Manifold", ACM International Conference on Information and Knowledge Management (CIKM 2016), To Appear, 2016, Oral.
  4. Mingkui Tan, Shijie Xiao, Junbin Gao, Dong Xu, Anton van den Hengel, Qinfeng Shi. "Riemannian Proximal Gradient for Large-scale Trace-norm Minimization", CVPR, 2016.
  5. Wen Li, Dengxin Dai, Mingkui Tan, Dong Xu, and Luc Van Gool, "Fast Algorithms for Linear and Kernel SVM+", CVPR, 2016.
  6. Dong Gong, Mingkui Tan, Yanning Zhang, Anton Van den Hengel, Qinfeng Shi, "Blind Image Deconvolution by Automatic Gradient Activation", CVPR, 2016.
  7. Mingkui Tan, Yan Yan, Li Wang, Ivor W Tsang, Anton van den Hengel,Qinfeng Shi. "Learning Sparse Confidence-Weighted Classifier on Very High Dimensional Data", AAAI, 2016.
  8. Mingkui Tan, Qinfeng Shi, Anton van den Hengel, Chunhua Shen, Junbin Gao, Fuyuan Hu, Zhen Zhang. "Learning Graph Structure for Multi-label Image Classification via Clique Generation", CVPR, 2015
  9. Yan Yan, Mingkui Tan (*Corresponding Author), Ivor W. Tsang, Yi Yang, Chengqi Zhang, Qinfeng Shi. "Scalable Maximum Margin Matrix Factorization by Active Riemannian Subspace Search", International Joint Conference on Artificial Intelligence,IJCAI, 2015
  10. Mingkui Tan, Ivor W. Tsang, Li Wang. "Matching Pursuit LASSO Part I: Sparse Recovery over Big Dictionary", IEEE Transactions on Signal Processing, 63(3), 2015.

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students




导师:吴庆耀


华南理工大学软件学院 副教授、硕士研究生导师。

华南理工大学骨干教师引进人才、华工校内杰出青年项目获得者。广东省教育厅青年创新人才。2013年黑龙江省优秀博士生与哈尔滨工业大学优秀博士生,IEEE Transactions on Neural Networks and Learning Systems (TNNLS)、Knowledge-Based Systems、IEEE Transactions on Image Processing (T-IP)、Knowledge-Based Systems (KBS) 审稿人。

2014年1月至2015年1月在新加坡南洋理工大学从事博士后研究工作。研究领域包括机器学习、数据挖掘、社交网络分析与大数据分析。目前侧重研究高性能大规模机器学习算法和模型,解决大规模数据应用中的机器学习问题。近年已发表论文30余篇,包括国际顶级和权威杂志IEEE Transactions on Neural Networks and Learning Systems (TNNLS)、IEEE Intelligent Systems (IS)、Pattern Recognition (PR)、Knowledge-Based Systems (KBS)、SDM与BMC论文,其中第一作者和通讯作者SCI检索论文10余篇。现主持国家自然科学基金青年项目1项、国家重点实验室开放课题2项、广东省教育厅青年创新人才1项、中央高校杰出青年项目1项。

可以招收软件工程学术型硕士和专业工程硕士。


近期论文:

  1. 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), DOI: 10.1109/TKDE.2017.2669193
  2. Michael K. Ng, Qingyao Wu, Chenyang Shen, "A fast Markov chain based algorithm for MIML learning", Neurocomputing, DOI: 10.1016/j.neucom.2016.08.033, in press
  3. Guohua Wang, Qiong Liu and Qingyao Wu, "Far-infrared pedestrian detection for advanced driver assistance systems using scene context", Optical Engineering, 55(4), pp.043105-043105, 2016 (IF: 0.954)
  4. Yuguang Yan, Qingyao Wu*, Mingkui Tan, Huaqing Min, "Online Heterogeneous Transfer Learning by Weighted Offline and Online Classifiers", In: ECCV-2016 workshop on TASK Transferring and Adapting Source Knowledge in Computer Vision, 2016 (Honorable Mention Paper Award)
  5. Yongxin Liao, Shenxi Yuan, Jian Chen, Qingyao Wu* and Bin Li, "Joint Classification with Heterogeneous labels using random walk with dynamic label propagation", PAKDD, 3-13, 2016
  6. 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, 63:30-40, 2016 (IF: 1.595)
  7. Feng Wu, Qiong Liu, Tianyong Hao, Xiaojun Chen, and Qingyao Wu*, "Online Multi-Instance Multi-Label Learning for Protein Function Prediction", In: IEEE BIBM, 2016 (CCF-B)
  8. 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: 0.672)
  9. 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:2.853)
  10. 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

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