个人简介
黄栋，男，1987年生，院长助理，计算机系副主任。2015年6月博士毕业于中山大学，同年加入华南农业大学数学与信息学院，2017年至2018年国家公派新加坡南洋理工大学从事访问学者研究工作。
已发表学术论文50 余篇，其中第一作者或通讯作者论文20余篇、两篇一作论文入选ESI高被引论文（Top 1%）。代表性成果发表在IEEE TKDE（*3）、IEEE TCYB（*4）、IEEE TSMC-S（*1）、ACM TKDD（*1）、KBS（*4）、Information Fusion（*1）、Pattern Recognition（*1）、AAAI（*2）、ICDM（*1）、DASFAA（*3）等国际权威期刊及重要会议上。迄今总IF之和逾100，其中一作IF之和逾60；主持承担了国家自然科学基金项目2项（面上项目与青年项目各1项）、广东省自然科学基金项目2项。目前担任IEEE TPAMI、IEEE TKDE、IEEE TIP、IEEE TCYB、IEEE TNNLS、IEEE TSMC-S、ACM TKDD等40多个SCI期刊审稿人。
欢迎有志于进入机器学习、数据挖掘及大数据分析等领域学习和深入开展学术研究的同学报读研究生，计算机类、数学类专业以及非相关专业但有扎实基础和强烈学习动力的学生皆可。
教育背景
2019年9月-2015年6月（硕博连读）
中山大学 计算机应用技术专业, 获博士学位 （导师: 赖剑煌教授）
2006年9月-2009年7月（本科）
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
2019年1月 ~ 现在
华南农业大学数学与信息学院 副教授
2017年2月 ~ 2019年1月
华南农业大学数学与信息学院 青年副教授
2017年7月 ~ 2018年7月
新加坡南洋理工大学 访问学者(Visiting Fellow)
2015年7月 ~ 2017年2月
华南农业大学数学与信息学院 讲师
奖励情况
2020年 广东省计算机学会优秀论文一等奖
2020年 华南农业大学“教书育人”先进个人
2019年 广东省计算机学会优秀论文一等奖
2019年 广州市智能工程研究会优秀论文奖
2019年 华南农业大学教学成果奖一等奖
2017年 广东省首届计算机科学青年学术秀二等奖
2016年 入选华南农业大学“青年科技人才”培育对象
2016年 入选数学与信息学院年度“十佳科研工作者”
Biography
Dong Huang received his B.S. degree in computer science from South China University of Technology, Guangzhou, China, in 2009, and his M.Sc. and Ph.D. degrees in computer science from Sun Yat-sen University, Guangzhou, in 2011 and 2015, respectively. He joined South China Agricultural University, Guangzhou, in 2015, where he is currently an Associate Professor with the College of Mathematics and Informatics. From Jul. 2017 to Jul. 2018, he was a Visiting Fellow with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. His research interests include data mining and machine learning, and more specifically focus on ensemble clustering, multi-view clustering, and large-scale clustering. He has published more than 50 papers in international journals and conferences, such as IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Cybernetics, IEEE Transactions on Systems, Man, and Cybernetics: Systems, Pattern Recognition, KBS, Neurocomputing, AAAI, and ICDM.
项目列表
[1]
广东省自然科学基金-面上项目（2021A1515012203）. 复杂带缺失多视图数据下的高效集成聚类算法研究. 2021.01-2023.12. 主持
[2]
国家自然科学基金-面上项目（61976097）. 基于异构二部图模型的多源大规模数据聚类集成算法研究. 2020.01-2023.12. 主持
[3]
国家自然科学基金-青年项目（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. 主持
[4]
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, 2016/1~2018/12, 10万元. 2016.06-2019.06. 主持
[5]
华南农业大学. 华南农业大学青年科技人才培育项目, 2017/1~2018/12, 20万元. 2016.04.
近期论文
查看导师新发文章
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期刊论文
2021
[1] Man-Sheng Chen, Ling Huang, Dong Huang, Jian-Huang Lai. Relaxed Multi-view Clustering in Latent Embedding Space. Information Fusion, 2021, 68, pp.8-21. (SCI-IF=13.669, 一区)
[2] Dong Huang, Chang-Dong Wang, Jian-Huang Lai, Chee-Keong Kwoh. Toward Multi-Diversified Ensemble Clustering of High-Dimensional Data: From Subspaces to Metrics and Beyond. IEEE Transactions on Cybernetics, accepted, 2021. (SCI-IF=11.079，一区)
[3] Dong Huang, Chang-Dong Wang, Hongxing Peng, Jianhuang Lai, Chee-Keong Kwoh. Enhanced Ensemble Clustering via Fast Propagation of Cluster-wise Similarities. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, 51(1), pp.508-520. (SCI-IF=9.309)
2020
[4] Chang-Dong Wang, Wei Shi, Ling Huang, Kun-Yu Lin, Dong Huang, Philip S. Yu. Node Pair Information Preserving Network Embedding Based on Adversarial Networks. IEEE Transactions on Cybernetics, accepted, 2020. (SCI-IF=11.079, 一区)
[5] Man-Sheng Chen, Ling Huang, Chang-Dong Wang, Dong Huang, Philip S. Yu. Multi-view Subspace Clustering with Grouping Effect. IEEE Transactions on Cybernetics, accepted, 2020. (SCI-IF=11.079, 一区)
[6] Dong Huang, Chang-Dong Wang, Jian-Sheng Wu, Jian-Huang Lai, Chee-Keong Kwoh. Ultra-Scalable Spectral Clustering and Ensemble Clustering. IEEE Transactions on Knowledge and Data Engineering, 2020, 32(6), pp.1212-1226. (SCI-IF=4.935, 二区, CCF-A类) [ESI高被引论文（Top 1%）]
[7] 黄宇翔, 黄栋*. 基于集成学习的改进深度嵌入聚类算法. 计算机科学与探索, 2020. (中文核心期刊)
[8] Guang-Yu Zhang, Yu-Ren Zhou, Xiao-Yu He, Chang-Dong Wang, Dong Huang. One-step Kernel Multi-view Subspace Clustering. Knowledge-Based Systems, 2020, 189, pp.105126. (SCI-IF=5.921，二区)
2019
[9] Dong Huang, Xiaosha Cai, Chang-Dong Wang. Unsupervised Feature Selection with Multi-Subspace Randomization and Collaboration. Knowledge Based Systems, accepted, 2019. (SCI-IF=5.921, 二区)
[10] Juan-Hui Li, Ling Huang, Chang-Dong Wang, Dong Huang, Jian-Huang Lai. PartNRL: Partial Nodes Representation Learning in Large-scale Network. IEEE Access, 2019, 7, pp.56457-56468. (SCI-IF=4.098，二区)
[11] Guang-Yu Zhang, Yu-Ren Zhou, Xiao-Yu He, Chang-Dong Wang, Dong Huang. One-step Kernel Multi-view Subspace Clustering. Knowledge Based Systems, accepted, 2019. (SCI-IF=5.101, 二区)
[12] Pei-Zhen Li, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Dong Huang. Community Detection by Motif-aware Label Propagation. ACM Transactions on Knowledge Discovery from Data, accepted, 2019. (SCI-IF=2.538, 三区)
[13] Ling Huang, Zhi-Lin Zhao, Chang-Dong Wang, Dong Huang, Hong-Yang Chao. LSCD: Low-rank and sparse cross-domain recommendation. Neurocomputing, 2019, 366, pp.86-96. (SCI-IF=4.072, 二区)
2018
[14] Dong Huang, Chang-Dong Wang, Jian-Huang Lai. Locally Weighted Ensemble Clustering. IEEE Transactions on Cybernetics, 2018, 48(5), pp.1460-1473. (SCI-IF=11.079，一区) [ESI高被引论文（Top 1%）]
[15] Yuexin Cai#(co-first author), 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, 2018, 12:122. (SCI-IF=3.138，三区)
[16] Guang-Yu Zhang, Chang-Dong Wang, Dong Huang, Wei-Shi Zheng, 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)
[17] Pei-Zhen Li, Ling Huang, Chang-Dong Wang, Dong Huang, Jian-Huang Lai. Community Detection Using Attribute Homogenous Motif. IEEE Access, 2018, 6, pp.47707-47716. (SCI-IF=3.557，二区)
2017
[18] Guang-Yu Zhang, Chang-Dong Wang, Dong Huang, 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)
[19] Chao Chen, Kun-Yu Lin, Chang-Dong Wang, Jian-Bo Liu, Dong Huang. CCMS: A Nonlinear Clustering Method Based on Crowd Movement and Selection. Neurocomputing, to appear, 2017. (SCI-IF=3.317, 二区)
2016
[20] Dong Huang, Jian-Huang Lai, Chang-Dong Wang, Pong C. Yuen. Ensembling Over-Segmentations: From Weak Evidence to Strong Segmentation. Neurocomputing, 2016, 207, pp.416-427. (SCI-IF=3.317, 二区)
[21] 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. (中文核心)
[22] Dong Huang, Jian-Huang Lai, 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)
[23] Dong Huang, Jian-Huang Lai, Chang-Dong Wang. Ensemble Clustering Using Factor Pattern Recognition, 2016, 50, pp.131-142. (SCI-IF=4.582, 二区)
2015
[24] Dong Huang, Jian-Huang Lai, 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)
2013
[25] Chang-Dong Wang, Jian-Huang Lai, Dong Huang, 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)
会议论文
2021
[1] Youwei Liang, Dong Huang*. Large Norms of CNN Layers Do Not Hurt Adversarial Robustness. The 35th AAAI Conference on Artificial Intelligence (AAAI), 2021. (Acceptance rate 1692/9034=18.73%)
2020
[2] Xiaosha Cai, Dong Huang*. Subspace-Weighted Consensus Clustering for High-Dimensional Data. The 16th International Conference on Advanced Data Mining and Applications (ADMA), 2020
[3] Xiaosha Cai, Dong Huang*, Chang-Dong Wang, Chee-Keong Kwoh. Spectral Clustering by Subspace Randomization and Graph Fusion for High-Dimensional Data. The 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2020. (Acceptance rate 21%)
[4] Zijing Ma, Shuangjuan Li, Dong Huang. Exact algorithms for barrier coverage with line-based deployed rotatable directional sensors. IEEE Wireless Communications and Networking Conference (WCNC), 2020
[5] Man-Sheng Chen, Ling Huang, Chang-Dong Wang, Dong Huang. Multi-view Clustering in Latent Embedding Space. Proc. of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020. (Acceptance rate 20.6%)
2019
[6] Youwei Liang, Dong Huang*, Chang-Dong Wang. Consistency Meets Inconsistency: A Unified Graph Learning Framework for Multi-view Clustering. Proc. of the 19th IEEE International Conference on Data Mining (ICDM), 2019. (Acceptance rate 18.5%)
[7] Man-Sheng Chen, Ling Huang, Chang-Dong Wang, Dong Huang. Multi-view Spectral Clustering via Multi-view Weighted Consensus and Matrix-Decomposition Based Discretization. International Conference on Database Systems for Advanced Applications (DASFAA), 2019
[8] Nannan He, Dong Huang*. Meta-Cluster Based Consensus Clustering with Local Weighting and Random Walking. Proc. of International Conference on Intelligence Science and Big Data Engineering (IScIDE), 2019
[9] Jianheng Liang, Dong Huang*. Laplacian-Weighted Random Forest for High-Dimensional Data Classification. Proc. of IEEE Symposium Series on Computational Intelligence (SSCI), 2019
[10] Shasha Xu, Dong Huang*. Ensemble-Initialized k-Means Clustering. International Conference on Machine Learning and Computing (ICMLC), 2019
[11] Mansheng Chen, Dong Huang*, Mingkai He, Chang-Dong Wang. Ensemble Clustering by Noise-Aware Graph Decomposition. International Conference on Information Technology: IoT and Smart City (ICIT), 2019
2018
[12] Zhi-Lin Zhao, Ling Huang, Chang-Dong Wang, Dong Huang. Low-rank and Sparse Cross-Domain Recommendation Algorithm. Proc. of International Conference on Database Systems for Advanced Applications (DASFAA), 2018. (EI indexed)
[13] Juan-Hui Li, Chang-Dong Wang, Ling Huang, Dong Huang, Jian-Huang Lai, Pei Chen. Attributed Network Embedding with Micro-Meso Structure. Proc. of International Conference on Database Systems for Advanced Applications (DASFAA), 2018. (EI indexed)
2017
[14] Dong Huang, Chang-Dong Wang, Jian-Huang Lai. LWMC: A Locally Weighted Meta-Clustering Algorithm for Ensemble Clustering. Proc. of International Conference on Neural Information Processing (ICONIP), 2017. (EI indexed)
[15] Mei Li, Dong Huang, Bin Wei, 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 indexed)
[16] Dong Huang, Chang-Dong Wang, Ling Huang, Yanhan Zeng. Improving Evidence Accumulation Clustering by k Nearest Neighbors. Proc. of International Conference on Data Mining, Communications and Information Technology (DMCIT), 2017. (EI indexed)
[17] 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 indexed)
2016
[18] Dong Huang, Chang-Dong Wang, Jian-Huang Lai, Yun Liang, Shan Bian, Yu Chen. Ensemble-driven support vector clustering: From ensemble learning to automatic parameter estimation. Proc. of International Conference on Pattern Recognition (ICPR), 2016. (EI indexed)
[19] Chao Chen, Kun-Yu Lin, Chang-Dong Wang, 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 indexed)
[20] Guang-Yu Zhang, Dong Huang, Chang-Dong Wang, Wei-Shi Zheng. Weighted Multi-view On-line Competitive Clustering. Proc. of IEEE International Conference on Big Data Computing Service and Applications (BigDataService'16), 2016. (EI indexed)
[21] Xiang-You Peng, Yu-Bo Yang, Chang-Dong Wang, Dong Huang, Jian-Huang Lai. An Efficient Parallel Nonlinear Clustering Algorithm using MapReduce. Proc. of International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics (ParLearning'16), 2016. (EI indexed)
[22] Zhi-Lin Zhao, Chang-Dong Wang, Yuan-Yu Wan, Jian-Huang Lai, Dong Huang. FTMF: Recommendation in Social Network with Feature Transfer and Probabilistic Matrix Factorization. Proc. of International Joint Conference on Neural Networks (IJCNN'16), 2016. (EI indexed)
2013
[23] Dong Huang, Jian-Huang Lai, 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. (EI indexed)
2012
[24] Dong Huang, Jian-Huang Lai, Chang-Dong Wang. Incremental Support Vector Clustering with Outlier Detection. Proc. of International Conference on Pattern Recognition (ICPR), 2012. (EI indexed)
2011
[25] Chang-Dong Wang, Jian-Huang Lai, Dong Huang. Kernel-Based Clustering with Automatic Cluster Number Selection.. Proc. of International Conference on Data Mining Workshops (ICDM Workshops), 2011. (EI indexed)
[26] Chang-Dong Wang, Jian-Huang Lai, Dong Huang. Incremental Support Vector Clustering. Proc. of International Conference on Data Mining Workshops (ICDM Workshops), 2011. (EI indexed)
2010
[27] Dong Huang, Jian-Huang Lai, Chang-Dong Wang. A Novel Keyframe Extracting Method Based on Adaptive Preselecting and Affinity Propagation. Proc. of National Conference on Image and Graphics (NCIG2010, In Chinese).
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