黄栋，男，博士，青年副教授，硕士生导师，主要研究方向是数据挖掘与机器学习，具体研究内容包括：数据集成聚类、多视图聚类、支持向量聚类和图像视频分析等。已在IEEE TKDE、IEEE TCYB、PR、Neurocomputing、ESWA、ICPR等国际权威期刊和会议上发表（或录用）学术论文20余篇，其中SCI期刊论文10篇；迄今总IF之和逾40，其中一作IF之和逾25；目前主持国家自然科学基金项目1项、广东省自然科学基金项目1项、华南农业大学青年科技人才培育项目1项，并受邀担任IEEE TKDE、IEEE Access、Neurocomputing、KAIS、NPL、IJPRAI、JMLC等多个SCI期刊审稿人。

欢迎有兴趣从事数据挖掘和大数据分析等领域学习与研究的同学报读研究生！

教育经历：

- 2009年9月 – 2015年6月

中山大学 计算机应用技术专业，硕博连读，获博士学位，导师：赖剑煌教授

- 2006年9月 – 2009年7月

华南理工大学 计算机科学与技术（联合班）专业，于本科第三年提前毕业，获学士学位

工作经历：

- 2017年7月 – 现在.

新加坡南洋理工大学 计算机科学与工程学院，访问学者(Visiting Fellow)

- 2017年2月 – 现在.

华南农业大学 数学与信息学院，青年副教授

- 2015年7月 – 2017年2月.

华南农业大学 数学与信息学院，讲师

主持项目:

1. 国家自然科学基金-青年科学基金项目，61602189，“面向多源异构流数据的在线聚类集成算法研究及其应用”，2017/01-2019/12，20万，在研，主持。

2. 广东省自然科学基金-博士启动项目，2016A030310457，“面向大规模数据的集成聚类新方法研究”，2016/06-2019/06，10万，在研，主持。

3. 华南农业大学青年科技人才培育项目，2017/01 - 2018/12，20万，在研，主持。

参与项目:

1. 国家自然科学基金-青年科学基金项目，61502543，“具有耦合性结构的多视图社交网络社区发现算法研究及其应用”，2016/01－2018/12，24.6万，在研，主要参与（3/8） 

2. 广东省自然科学基金-博士启动项目，2014A030310180，“多视图聚类新方法及其应用”，2015/01－2018/01, 10万，已结题，主要参与（3/9）

期刊论文：

[1] Dong Huang, Chang-Dong Wang and Jian-Huang Lai. Locally Weighted Ensemble Clustering, IEEE Transactions on Cybernetics, 2018, 48(5), pp.1460-1473. (SCI-IF=7.384，一区)

[2] Yuexin Cai^#, Dong Huang^# (co-first author), Yanhong Chen, Haidi Yang, Changdong Wang, Fei Zhao, Jiahao Liu, Yingfeng Sun, Guisheng Chen, Xiaoting Chen, Hao Xiong, Yiqing Zheng. Deviant dynamics of resting state electroencephalogram microstate in patients with subjective tinnitus. Frontiers in Behavioral Neuroscience, in press, 2018. (SCI-IF=3.104，三区)

[3] Dong Huang, Jian-Huang Lai and Chang-Dong Wang. Robust Ensemble Clustering Using Probability Trajectories, IEEE Transactions on Knowledge and Data Engineering, 2016, 28(5), pp. 1312-1326. (SCI-IF=3.438，二区，CCF-A类)

[4] Dong Huang, Jian-Huang Lai and Chang-Dong Wang. Ensemble Clustering Using Factor Graph, Pattern Recognition, 2016, 50, pp.131-142. (SCI-IF=4.582，二区)

[5] Dong Huang, Jian-Huang Lai, Chang-Dong Wang and Pong C. Yuen. Ensembling Over-Segmentations: From Weak Evidence to Strong Segmentation, Neurocomputing, 2016, 207, pp. 416-427. (SCI-IF=3.317，二区)

[6] Dong Huang, Jian-Huang Lai and Chang-Dong Wang. Combining Multiple Clusterings via Crowd Agreement Estimation and Multi-Granularity Link Analysis, Neurocomputing, 2015, 170, pp.240-250. (SCI-IF=3.317，二区)

[7] Chang-Dong Wang, Jian-Huang Lai, Dong Huang, and Wei-Shi Zheng. SVStream: A Support Vector Based Algorithm for Clustering Data Streams, IEEE Transactions on Knowledge and Data Engineering, 2013, 25(6), pp.1410-1424. (SCI-IF=3.438，二区，CCF-A类)

[8] Guang-Yu Zhang, Chang-Dong Wang, Dong Huang, Wei-Shi Zheng, and Yu-Ren Zhou. TW-Co-k-means: Two-level Weighted Collaborative k-means for Multi-view Clustering. Knowledge-Based Systems, 2018, 150, pp.127-138. (SCI-IF=4.529，二区)

[9] Guang-Yu Zhang, Chang-Dong Wang, Dong Huang, and Wei-Shi Zheng. Multi-View Collaborative Locally Adaptive Clustering with Minkowski Distance, Expert Systems With Applications, 2017, 86, pp.307-320. (SCI-IF=3.928，二区)

[10] Chao Chen, Kun-Yu Lin, Chang-Dong Wang, Jian-Bo Liu, and Dong Huang. CCMS: A Nonlinear Clustering Method Based on Crowd Movement and Selection, Neurocomputing, 2017, 269, pp.120-131. (SCI-IF=3.317，二区)

[11] 黄栋, 王昌栋, 赖剑煌, 梁云, 边山, 陈羽. 基于决策加权的聚类集成算法. 智能系统学报, 2016, 11(3), pp.418-425. (核心) 

会议论文：

[1] Dong Huang, Chang-Dong Wang, and Jian-Huang Lai. LWMC: A Locally Weighted Meta-Clustering Algorithm for Ensemble Clustering, Proc. of International Conference on Neural Information Processing (ICONIP), 2017. (EI)

[2] Dong Huang, Chang-Dong Wang, Ling Huang, and Yanhan Zeng. Improving Evidence Accumulation Clustering by k Nearest Neighbors, Proc. of International Conference on Data Mining, Communications and Information Technology (DMCIT), 2017. (EI)

[3] Dong Huang, Chang-Dong Wang, Jian-Huang Lai, Yun Liang, Shan Bian, and Yu Chen. Ensemble-Driven Support Vector Clustering: From Ensemble Learning to Automatic Parameter Estimation, Proc. of International Conference on Pattern Recognition (ICPR), 2016. (EI)

[4] Dong Huang, Jian-Huang Lai and Chang-Dong Wang. Exploiting the Wisdom of Crowd: A Multi-granularity Approach to Clustering Ensemble, Proc. of International Conference on Intelligence Science and Big Data Engineering (IScIDE), 2013, pp.112-119. (EI)

[5] Dong Huang, Jian-Huang Lai and Chang-Dong Wang. Incremental Support Vector Clustering with Outlier Detection, Proc. of International Conference on Pattern Recognition (ICPR), 2012. (EI)

[6] Dong Huang, Jian-Huang Lai and Chang-Dong Wang. A Novel Keyframe Extracting Method Based on Adaptive Preselecting and Affinity Propagation, Proc. of National Conference on Image and Graphics (NCIG, In Chinese), 2010, pp.426-429.

[7] Juan-Hui Li, Chang-Dong Wang, Ling Huang, Dong Huang, Jian-Huang Lai, and Pei Chen. Attributed Network Embedding with Micro-Meso Structure. Proc. of International Conference on Database Systems for Advanced Applications (DASFAA), 2018. (EI)

[8] Zhi-Lin Zhao, Ling Huang, Chang-Dong Wang, and Dong Huang. Low-rank and Sparse Cross-Domain Recommendation Algorithm. Proc. of International Conference on Database Systems for Advanced Applications (DASFAA), 2018. (EI)

[9] Mei Li, Dong Huang, Bin Wei, and Chang-Dong Wang. Event Recommendation via Collective Matrix Factorization with Event-User Neighborhood, Proc. of International Conference on Intelligence Science and Big Data Engineering (IScIDE), 2017. (EI)

[10] Yue Ding, Ling Huang, Chang-Dong Wang, Dong Huang. Community Detection in Graph Streams by Pruning Zombie Nodes, Proc. of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2017. (EI)

[11] Guang-Yu Zhang, Dong Huang, Chang-Dong Wang and Wei-Shi Zheng. Weighted Multi-view On-line Competitive Clustering, Proc. of IEEE International Conference on Big Data Computing Service and Applications (BigDataService), 2016. (EI)

[12] Zhi-Lin Zhao, Chang-Dong Wang, Yuan-Yu Wan, Jian-Huang Lai and Dong Huang. FTMF: Recommendation in Social Network with Feature Transfer and Probabilistic Matrix Factorization, Proc. of International Joint Conference on Neural Networks (IJCNN), 2016. (EI)

[13] Chao Chen, Kun-Yu Lin, Chang-Dong Wang, and Dong Huang. CSBD: A Nonlinear Clustering Method Based on Cluster Shrinking and Border Detection, Proc. of International Workshop on Network Computing and Data Management (in conjunction with ISPA 2016), 2016. (EI)

[14] Xiang-You Peng, Yu-Bo Yang, Chang-Dong Wang, Dong Huang, and Jian-Huang Lai. An Efficient Parallel Nonlinear Clustering Algorithm using MapReduce, Proc. International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics (ParLearning), 2016. (EI)

[15] Chang-Dong Wang, Jian-Huang Lai and Dong Huang. Incremental Support Vector Clustering, Proc. of International Conference on Data Mining Workshops (ICDM Workshops), 2011. (EI)

[16] Chang-Dong Wang, Jian-Huang Lai and Dong Huang. Kernel-Based Clustering with Automatic Cluster Number Selection, Proc. of International Conference on Data Mining Workshops (ICDM Workshops), 2011. (EI)

Dong Huang

Ph. D.  

Associate Professor

College of Mathematics and Informatics,

South China Agricultural University                         

Tel: 020-85280320-610

E-Mail: huangdong06@163.com

Research interests:

My research interests focus on data mining and pattern recognition, particularly in ensemble clustering, streaming data clustering, support vector clustering, and image and video analysis.

Education:

- Sep. 2009 – Jun. 2015.

M.Sc. and Ph.D. in Computer Science, Sun Yat-sen University.

Advisor: Prof. Jian-Huang Lai.

- Sep. 2006 - Jun. 2009.

B.S. in Computer Science, South China University of Technology.

Work experience:

- Jul. 2015 – Feb. 2017.

Assistant Professor with the College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China.

- Feb. 2017 – Present.

Associate Professor with the College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China.