目录
黄栋，华南农业大学数学与信息学院副教授，硕士生导师，院长助理。2015年博士毕业于中山大学计算机应用技术专业，2017-2018年国家公派新加坡南洋理工大学从事访问学者研究工作。现/曾任中国计算机学会（CCF）数字农业分会副秘书长，CCF首届数字农业大会组委会共同主席，CCF青年计算机科技论坛（YOCSEF）广州主席（2022-2023），CCF计算机视觉专委会执委，广东省计算机信息网络安全协会红帽人才专业委员会副秘书长、常务理事。获2019年与2020年广东省计算机学会优秀论文奖一等奖、2020年ACM广州新星奖、2022年广东省人工智能产业协会科学技术奖-青年科技创新奖、2023年广东省人工智能产业协会科学技术奖-自然科学奖二等奖，入选CCF杰出演讲者（2023）以及斯坦福大学发布的全球前2%顶尖科学家榜单（2023）。
致力于人工智能与大数据分析研究，主要研究内容包括复杂大数据聚类（大规模聚类/集成聚类/多视图聚类/深度聚类）、无监督/自监督学习、图神经网络、图像视频分析等。已发表学术论文80余篇，其中第一作者或通讯作者论文40余篇，4篇一作/通讯论文入选ESI高被引论文（Top 1%）。迄今一作和通讯作者论文IF之和逾200，单篇IF>8的期刊论文24篇。主要成果发表在IEEE TKDE、IEEE TNNLS、IEEE TCYB、IEEE TSMC-S、IEEE TBD、IEEE TETCI, ACM TKDD、Information Fusion、Pattern Recognition等国际权威期刊和SIG-KDD、AAAI、ICDM、ACM MM等重要学术会议；主持承担了国家自然科学基金项目（青年项目与面上项目）、广东省自然科学基金项目、广州市科技计划项目等纵向和横向项目多项；相关算法应用于广东省气象大数据实时订正与分析（已在省级气象单位部署应用）和中山大学孙逸仙纪念医院耳科疾病智能诊断系统等。担任IEEE TPAMI、IEEE TKDE、IJCV、Artificial Intelligence、《中国科学: 技术科学》等四十多个国内外重要期刊审稿人。
欢迎有志于进入人工智能、数据挖掘、大数据分析等领域学习与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的学生均可。
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2019年1月 ~ 现在
华南农业大学数学与信息学院 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)
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
2015年7月 ~ 2017年2月
华南农业大学数学与信息学院 讲师
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2009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
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2023年 中国计算机学会（CCF）杰出演讲者
2023年 广东省人工智能产业协会科学技术奖-自然科学奖二等奖
2022年 广东省人工智能产业协会科学技术奖-青年科技创新奖
2020年 ACM广州新星奖（ACM Guangzhou Rising Star Award）
2020年 入选华南农业大学“教书育人”先进个人
2020年 广东省计算机学会优秀论文一等奖
2019年 华南农业大学教学成果奖一等奖
2019年 广东省计算机学会优秀论文一等奖
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中国计算机学会（CCF）数字农业分会 副秘书长
CCF青年计算机科技论坛（YOCSEF）广州主席（2022-2023）
CCF计算机视觉专委会执委
广东省计算机信息网络安全协会红帽人才专业委员会副秘书长、常务理事
中国人工智能学会（CAAI）模式识别专委会委员
中国自动化学会（CAA）模式识别与机器智能专委会委员
担任学术期刊审稿人：
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI)
IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE)
IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS)
IEEE Transactions on Image Processing (IEEE TIP)
IEEE Transactions on Cybernetics (IEEE TCYB)
IEEE Transactions on Systems, Man and Cybernetics: Systems (IEEE TSMC-S)
IEEE Transactions on Fuzzy Systems (IEEE TFS)
IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT)
IEEE Transactions on Multimedia (IEEE TMM)
IEEE Transactions on Services Computing (IEEE TSC)
IEEE Transactions on Big Data (IEEE TBD)
IEEE Transactions on Artificial Intelligence (IEEE TAI)
IEEE Transactions on Emerging Topics in Computational Intelligence (IEEE TETCI)
IEEE Transactions on Emerging Topics in Computing (IEEE TETC)
IEEE Transactions on Network Science and Engineering (IEEE TNSE)
IEEE Transactions on Industrial Informatics (IEEE TII)
IEEE Transactions on Intelligent Transportation Systems (IEEE TITS)
IEEE Journal of Selected Topics in Signal Processing (IEEE JSTSP)
IEEE Computational Intelligence Magazine (IEEE CIM)
IEEE Journal of Biomedical and Health Informatics (IEEE JBHI)
ACM Transactions on Knowledge Discovery from Data (ACM TKDD)
ACM Transactions on Multimedia Computing, Communications, and Applications (ACM TOMM)
International Journal of Computer Vision (IJCV)
Artificial Intelligence (AI)
Information Fusion (IF)
Pattern Recognition (PR)
Bioinformatics
Data Mining and Knowledge Discovery (DMKD)
Knowledge-Based Systems (KBS)
Neural Networks (NN)
Engineering Applications of Artificial Intelligence (EAAI)
Future Generation Computer Systems (FGCS)
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人工智能、大数据分析、深度学习、图神经网络、无监督/自监督学习
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1. 国家自然科学基金-面上项目, "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", 主持.
2. 国家自然科学基金-青年项目, "面向多源异构流数据的在线聚类集成算法研究及其应用", 主持.
3. 广东省自然科学基金-面上项目, "复杂带缺失多视图数据下的高效集成聚类算法研究", 主持.
4. 广东省自然科学基金-博士启动项目, "面向大规模数据的集成聚类新方法研究", 主持.
5. 华南农业大学青年科技人才培育项目, “基于集成聚类的图像分割算法研究及其应用”, 主持.
6. 国家自然科学基金-面上项目, “基于相似度学习的异构数据聚类算法研究及其应用”, 合作单位负责人.
7. 国家自然科学基金-青年项目, “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”, 主要参与(3/8) .
8. 广东省自然科学基金-博士启动项目, “多视图聚类新方法及其应用”, 主要参与(3/9).
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——【2024】——
[1] Youwei Liang (指导的本科生), Dong Huang* (黄栋) (corresponding author), Chang-Dong Wang, and Philip S. Yu. Multi-View Graph Learning by Joint Modeling of Consistency and Inconsistency. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2024, 35(2): 2848-2862. (SCI-IF=14.255, 中科院一区)
[2] Jinghuan Lao (指导的研究生), Dong Huang* (黄栋) (corresponding author), Chang-Dong Wang, Jian-Huang Lai. Towards Scalable Multi-view Clustering via Joint Learning of Many Bipartite Graphs. IEEE Transactions on Big Data (IEEE TBD), 2024, 10(1): 77-91. (SCI-IF=7.2, 中科院二区)
[3] Si-Guo Fang (指导的研究生), Dong Huang* (黄栋) (corresponding author), Chang-Dong Wang, and Yong Tang. Joint Multi-view Unsupervised Feature Selection and Graph Learning. IEEE Transactions on Emerging Topics in Computational Intelligence (IEEE TETCI), accepted, 2024. (SCI-IF=5.3, 中科院二区)
[4] Yuankun Xu (指导的研究生), Dong Huang* (黄栋) (corresponding author), Chang-Dong Wang, Jian-Huang Lai. Deep Image Clustering with Contrastive Learning and Multi-scale Graph Convolutional Networks. Pattern Recognition, 2024, 146: 110065. (SCI-IF=8.0, 中科院一区)
[5] Chun-Hong Li (指导的研究生), Dong Huang* (黄栋) (corresponding author), Guang-Yu Zhang, Jinrong Cui. Motorcyclist Helmet Detection in Single Images: A Dual-Detection Frameworkwith Multi-Head Self-Attention. Soft Computing, 2024, 18: 4321–4333. (SCI-IF=4.1)
——【2023】——
[1] Dong Huang (黄栋), Chang-Dong Wang, Jian-Huang Lai. Fast Multi-view Clustering via Ensembles: Towards Scalability, Superiority, and Simplicity. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2023, 35(11): 11388-11402. (SCI-IF=8.9，中科院二区，CCF-A类期刊)
[2] Si-Guo Fang (指导的研究生), Dong Huang* (黄栋) (corresponding author), Xiao-Sha Cai, Chang-Dong Wang, Chaobo He, and Yong Tang. Efficient Multi-view Clustering via Unified and Discrete Bipartite Graph Learning. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), accepted, 2023. (SCI-IF=10.4, 中科院一区) [入选ESI高被引论文(Top 1%)]
[3] Xiaosha Cai (指导的研究生), Dong Huang* (黄栋) (corresponding author), Guang-Yu Zhang, Chang-Dong Wang. Seeking Commonness and Inconsistencies: A Jointly Smoothed Approach to Multi-view Subspace Clustering. Information Fusion, 2023, 91: 364-375. (SCI-IF=18.6, 中科院一区)
[4] Guang-Yu Zhang, Dong Huang* (黄栋) (corresponding author), Chang-Dong Wang. Unified and Tensorized Incomplete Multi-view Kernel Subspace Clustering. IEEE Transactions on Emerging Topics in Computational Intelligence (IEEE TETCI), accepted, 2023. (SCI-IF=5.3, 中科院二区)
[5] Dong Huang (黄栋), Ding-Hua Chen, Xiangji Chen, Chang-Dong Wang, Jian-Huang Lai. DeepCluE: Enhanced Deep Clustering via Multi-layer Ensembles in Neural Networks. IEEE Transactions on Emerging Topics in Computational Intelligence (IEEE TETCI), accepted, 2023. (SCI-IF=5.3, 中科院二区)
[6] Xiaozhi Deng (指导的研究生), Dong Huang* (黄栋) (corresponding author), Ding-Hua Chen, Chang-Dong Wang, Jian-Huang Lai. Strongly Augmented Contrastive Clustering. Pattern Recognition, 2023, 139: 109470. (SCI-IF=8.0, 中科院一区)
[7] Guang-Yu Zhang, Dong Huang* (黄栋) (corresponding author), Chang-Dong Wang. Facilitated Low-rank Multi-view Subspace Clustering. Knowledge-Based Systems, 2023, 260: 110141. (SCI-IF=8.8, 中科院一区)
[8] Hua-Bao Ling (指导的研究生), Dong Huang* (黄栋) (corresponding author), Jinrong Cui, Chang-Dong Wang. HOLT-Net: Detecting Smokers via Human-Object Interaction with Lite Transformer Network. Engineering Applications of Artificial Intelligence, 2023, 126: 106919. (SCI-IF=8.0, 中科院二区)
[9] Ying Zhong (指导的研究生), Dong Huang* (黄栋) (corresponding author), Chang-Dong Wang. Deep Temporal Contrastive Clustering. Neural Processing Letters, 2023, 55: 7869-7885. (SCI-IF=3.1)
[10] Xiaozhi Deng (指导的研究生), Dong Huang* (黄栋) (corresponding author), Chang-Dong Wang. Heterogeneous Tri-stream Clustering Network. Neural Processing Letters, 2023, 55: 6533-6546. (SCI-IF=3.1)
[11] Chang-Dong Wang, Xi-Ran Zhu, Xueqing Zhou, Jiahong Li, Liping Lan, Dong Huang (黄栋), Yiqing Zheng, Yuexin Cai. Cross-subject Tinnitus Diagnosis based on Multi-band EEG Contrastive Representation Learning, IEEE Journal of Biomedical and Health Informatics, 2023, 27(7): 3187-3197. (SCI-IF=7.7, 中科院一区)
[12] Cheng Huang, Jinrong Cui, Yulu Fu, Dong Huang (黄栋), Min Zhao, and Lusi Li. Incomplete multi-view clustering network via nonlinear manifold embedding and probability-induced loss, Neural Networks, 2023, 163: 233-243. (SCI-IF=14.5, 中科院一区)
[13] Bowen Zhu (指导的研究生), Dong Huang* (黄栋) (corresponding author), Jinrong Cui, Guang-Yu Zhang. Deep Attributed Graph Clustering with Graph Attention Network, Proc. of the 15th International Conference on Machine Learning and Computing (ICMLC), 2023.
[14] 劳景欢 (指导的研究生), 黄栋* (通讯作者), 王昌栋, 赖剑煌. 基于视图互信息加权的多视图集成聚类算法. 计算机应用, 2023, 43(6): 1713-1718. (中文核心)
[15] 刘津铭 (指导的研究生), 蔡跃新, 曾俊波, 唐小武, 区永康, 叶伟杰, 叶鸿生, 熊彬彬, 黄栋* (通讯作者). 基于眼动轨迹分析的BPPV诊断算法研究. 计算机与数字工程, 2023, 51(1): 142-147. (中文核心)
——【2022】——
[1] Dong Huang (黄栋), Chang-Dong Wang, Jian-Huang Lai, and Chee-Keong Kwoh. Toward Multidiversified Ensemble Clustering of High-Dimensional Data: From Subspaces to Metrics and Beyond. IEEE Transactions on Cybernetics (IEEE TCYB), 2022, 52(11), pp.12231-12244. (SCI-IF=19.118, 中科院一区)
[2] Man-Sheng Chen, Ling Huang, Chang-Dong Wang, Dong Huang (黄栋) and Philip S. Yu. Multiview Subspace Clustering with Grouping Effect, IEEE Transactions on Cybernetics (IEEE TCYB), 2022, 52(8), pp.7655-7668. (SCI-IF=19.118, 中科院一区)
[3] Chang-Dong Wang, Wei Shi, Ling Huang, Kun-Yu Lin, Dong Huang (黄栋) and Philip S. Yu. Node Pair Information Preserving Network Embedding Based on Adversarial Networks, IEEE Transactions on Cybernetics (IEEE TCYB), 2022, 52(7):5908-5922. (SCI-IF=19.118, 中科院一区)
[4] Man-Sheng Chen, Chang-Dong Wang, Dong Huang (黄栋), Jian-Huang Lai, and Philip S. Yu. Efficient Orthogonal Multi-view Subspace Clustering, Proc. of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022. (CCF-A类会议)
[5] Man-Sheng Chen, Tuo Liu, Chang-Dong Wang, Dong Huang (黄栋), Jian-Huang Lai. Adaptively-weighted Integral Space for Fast Multiview Clustering, Proc. of the 30th ACM International Conference on Multimedia (ACM MM), 2022. (CCF-A类会议)
[6] Guang-Yu Zhang, Xiao-Wei Chen, Yu-Ren Zhou, Chang-Dong Wang, Dong Huang (黄栋), Xiao-Yu He. Kernelized multi-view subspace clustering via auto-weighted graph learning, Applied Intelligence, 2022, 52, pp.716-731. (SCI-IF=5.019, 中科院三区)
[7] Man-Sheng Chen, Jia-Qi Lin, Xiang-Long Li, Bao-Yu Liu, Chang-Dong Wang, Dong Huang (黄栋), Jian-Huang Lai. Representation Learning in Multi-view Clustering: A Literature Review, Data Science and Engineering, 2022, 7, pp.225–241.
[8] Ding-Hua Chen (指导的研究生), Dong Huang* (黄栋) (corresponding author), Haiyan Cheng and Chang-Dong Wang. D-TRACE: Deep Triply-Aligned Clustering. Proc. of the 31st International Conference on Artificial Neural Networks (ICANN), 2022.
[9] Man-Sheng Chen, Chang-Dong Wang, Dong Huang (黄栋), Jian-Huang Lai . Coupled Learning for Kernel Representation and Graph Tensor in Multi-view Subspace Clustering, in proceedings of the 5th Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 2022.
——【2021】——
[1] Dong Huang (黄栋), Chang-Dong Wang, Hongxing Peng, Jianhuang Lai, and Chee-Keong Kwoh. Enhanced Ensemble Clustering via Fast Propagation of Cluster-wise Similarities, IEEE Transactions on Systems, Man, and Cybernetics: Systems (IEEE TSMC-S), 2021, 51(1), pp.508-520. (SCI-IF=11.471, 中科院一区) [入选ESI高被引论文(Top 1%)]
[2] Youwei Liang (指导的本科生), Dong Huang* (黄栋) (corresponding author). Large Norms of CNN Layers Do Not Hurt Adversarial Robustness, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2021. (CCF-A类会议)
[3] Hua-Bao Ling (指导的研究生), Dong Huang* (黄栋) (corresponding author). Single-Image Smoker Detection by Human-Object Interaction with Post-Refinement, Proc. of the 28th International Conference on Neural Information Processing (ICONIP), 2021.
[4] Chun-Hong Li (指导的研究生), Dong Huang* (黄栋) (corresponding author). Detecting Helmets on Motorcyclists by Deep Neural Networks with a Dual-Detection Scheme, Proc. of the 28th International Conference on Neural Information Processing (ICONIP), 2021.
[5] Xiaosha Cai (指导的研究生), Dong Huang* (黄栋) (corresponding author). Link-based Consensus Clustering with Random Walk Propagation, Proc. of the 28th International Conference on Neural Information Processing (ICONIP), 2021.
[6] Juan-Hui Li, Ling Huang, Chang-Dong Wang, Dong Huang (黄栋), Jian-Huang Lai, Pei Chen. Attributed Network Embedding with Micro-Meso Structure, ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 2021, 15(4), pp.1-26. (SCI-IF=4.157, 中科院三区)
[7] Man-Sheng Chen, Ling Huang, Dong Huang, and Jian-Huang Lai. Relaxed Multi-view Clustering in Latent Embedding Space, Information Fusion, 2021, 68, pp.8-21. (SCI-IF=17.564, 中科院一区)
[8] Guang-Yu Zhang, Yu-Ren Zhou, Chang-Dong Wang, Dong Huang (黄栋), and Xiao-Yu He. Joint representation learning for multi-view subspace clustering, Expert Systems With Applications, 2021, 166, pp.113913. (SCI-IF=8.665, 中科院一区)
[9] Guang-Yu Zhang, Xiaowei Chen, Yu-Ren Zhou, Chang-Dong Wang, Dong Huang (黄栋). Consistency- and Inconsistency-aware Multi-view Subspace Clustering, in proceedings of the 26th International Conference on Database Systems for Advanced Applications (DASFAA), 2021.
[10] 黄宇翔 (指导的研究生), 黄栋 (通讯作者), 王昌栋, 赖剑煌. 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, 2021, 15(10): 1949-1957. (中文核心)
——【2020 & Before】——
[1] Dong Huang (黄栋), Chang-Dong Wang, Jian-Sheng Wu, Jian-Huang Lai, and Chee-Keong Kwoh. Ultra-Scalable Spectral Clustering and Ensemble Clustering. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2020, 32(6), pp.1212-1226. (SCI-IF=9.235，中科院二区，CCF-A类期刊) [入选ESI高被引论文(Top 1%)]
[2] Dong Huang (黄栋), Chang-Dong Wang and Jian-Huang Lai. Locally Weighted Ensemble Clustering, IEEE Transactions on Cybernetics (IEEE TCYB), 2018, 48(5), pp.1460-1473. (SCI-IF=19.118, 中科院一区) [入选ESI高被引论文(Top 1%)]
[3] Youwei Liang (指导的本科生), Dong Huang* (黄栋) (corresponding author), Chang-Dong Wang. Consistency Meets Inconsistency: A Unified Graph Learning Framework for Multi-view Clustering, Proc. of IEEE International Conference on Data Mining (ICDM), 2019. (CCF-B类会议)
[4] Dong Huang (黄栋), Xiaosha Cai, and Chang-Dong Wang. Unsupervised Feature Selection with Multi-Subspace Randomization and Collaboration, Knowledge-Based Systems, 2019, 182, pp.104856. (SCI-IF=8.139, 中科院一区)
[5] Yuexin Cai#, Dong Huang# (黄栋) (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=3.617，中科院三区)
[6] Dong Huang (黄栋), Jian-Huang Lai and Chang-Dong Wang. Robust Ensemble Clustering Using Probability Trajectories, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2016, 28(5):1312-1326. (SCI-IF=9.235, 中科院二区, CCF-A类期刊)
[7] Dong Huang (黄栋), Jian-Huang Lai and Chang-Dong Wang. Ensemble Clustering Using Factor Graph, Pattern Recognition, 2016, 50, pp.131-142. (SCI-IF=8.518, 中科院一区)
[8] Dong Huang (黄栋), 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=5.779, 中科院二区)
[9] Dong Huang (黄栋), 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=5.779, 中科院二区)
[10] Xiaosha Cai (指导的研究生), Dong Huang* (黄栋) (corresponding author). Subspace-Weighted Consensus Clustering for High-Dimensional Data, Proc. of International Conference on Advanced Data Mining and Applications (ADMA), 2020.
[11] Xiaosha Cai (指导的研究生), Dong Huang* (黄栋) (corresponding author), Chang-Dong Wang, Chee-Keong Kwoh. Spectral Clustering by Subspace Randomization and Graph Fusion for High-Dimensional Data, Proc. of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2020.
[12] Jianheng Liang (指导的研究生), Dong Huang* (黄栋) (corresponding author). Laplacian-Weighted Random Forest for High-Dimensional Data Classification, Proc. of IEEE Symposium Series on Computational Intelligence (SSCI), 2019.
[13] Nannan He (指导的研究生), Dong Huang* (黄栋) (corresponding author). Meta-Cluster Based Consensus Clustering with Local Weighting and Random Walking, Proc. of International Conference on Intelligence Science and Big Data Engineering (IScIDE), 2019.
[14] Shasha Xu (指导的研究生), Dong Huang* (黄栋) (corresponding author). Ensemble-Initialized k-Means Clustering, Proc. of International Conference on Machine Learning and Computing (ICMLC), 2019.
[15] Mansheng Chen (指导的本科生), Dong Huang* (黄栋) (corresponding author), Mingkai He, Chang-Dong Wang. Ensemble Clustering by Noise-Aware Graph Decomposition, Proc. of International Conference on Information Technology: IoT and Smart City (ICIT), 2018.
[16] Dong Huang (黄栋), 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.
[17] Dong Huang (黄栋), 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.
[18] Dong Huang (黄栋), 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, in proceedings of International Conference on Pattern Recognition (ICPR), 2016.
[19] Dong Huang (黄栋), Jian-Huang Lai and Chang-Dong Wang. Exploiting the Wisdom of Crowd: A Multi-granularity Approach to Clustering Ensemble, in proceedings of International Conference on Intelligence Science and Big Data Engineering (IScIDE), 2013, pp.112-119.
[20] Dong Huang (黄栋), Jian-Huang Lai and Chang-Dong Wang. Incremental Support Vector Clustering with Outlier Detection, in proceedings of International Conference on Pattern Recognition (ICPR), 2012.
[21] Dong Huang (黄栋), Jian-Huang Lai and Chang-Dong Wang. A Novel Keyframe Extracting Method Based on Adaptive Preselecting and Affinity Propagation, in proceedings of National Conference on Image and Graphics (NCIG, In Chinese), 2010, pp.426-429.
[22] Pei-Zhen Li, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Dong Huang (黄栋). Community Detection by Motif-aware Label Propagation, ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 2020, 14(2), pp.1-19. (SCI-IF=4.157, 中科院三区)
[23] Man-Sheng Chen, Ling Huang, Chang-Dong Wang, Dong Huang (黄栋). Multi-view Clustering in Latent Embedding Space, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2020. (CCF-A类会议)
[24] Guang-Yu Zhang, Yu-Ren Zhou, Xiao-Yu He, Chang-Dong Wang, Dong Huang (黄栋). One-step Kernel Multi-view Subspace Clustering, Knowledge-Based Systems, 2020, 189, pp.105126. (SCI-IF=8.139，中科院一区)
[25] Ling Huang, Zhi-Lin Zhao, Chang-Dong Wang, Dong Huang (黄栋), Hong-Yang Chao. LSCD: Low-rank and sparse cross-domain recommendation, Neurocomputing, 2019, 366, pp.86-96. (SCI-IF=5.779, 中科院二区)
[26] Guang-Yu Zhang, Chang-Dong Wang, Dong Huang (黄栋), 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=8.139，中科院一区)
[27] Guang-Yu Zhang, Chang-Dong Wang, Dong Huang (黄栋), and Wei-Shi Zheng. Multi-View Collaborative Locally Adaptive Clustering with Minkowski Distance, Expert Systems With Applications, 2017, 86, pp.307-320. (SCI-IF=8.665, 中科院一区)
[28] Chao Chen, Kun-Yu Lin, Chang-Dong Wang, Jian-Bo Liu, and Dong Huang (黄栋). CCMS: A Nonlinear Clustering Method Based on Crowd Movement and Selection, Neurocomputing, 2017, 269, pp.120-131. (SCI-IF=5.779, 中科院二区)
[29] Chang-Dong Wang, Jian-Huang Lai, Dong Huang (黄栋) and Wei-Shi Zheng. SVStream: A Support Vector Based Algorithm for Clustering Data Streams, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDD), 2013, 25(6), pp.1410-1424. (SCI-IF=9.235, 中科院二区, CCF推荐A类期刊)
[30] Zijing Ma, Shuangjuan Li, Dong Huang (黄栋). Exact algorithms for barrier coverage with line-based deployed rotatable directional sensors, in proceedings of IEEE Wireless Communications and Networking Conference (WCNC), 2020.
[31] Zi-Hua Li, Ling Huang, Kai Wang, Chang-Dong Wang, Wei Shi, and Dong Huang (黄栋). Network embedding with class discriminability, in proceedings of ACM Turing Celebration Conference, 2019.
[32] Man-Sheng Chen, Ling Huang, Chang-Dong Wang, and Dong Huang (黄栋). Multi-view Spectral Clustering via Multi-view Weighted Consensus and Matrix-Decomposition Based Discretization, in proceedings of International Conference on Database Systems for Advanced Applications (DASFAA), 2019.
[33] Juan-Hui Li, Chang-Dong Wang, Ling Huang, Dong Huang (黄栋), 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.
[34] Zhi-Lin Zhao, Ling Huang, Chang-Dong Wang, and Dong Huang (黄栋). Low-rank and Sparse Cross-Domain Recommendation Algorithm. Proc. of International Conference on Database Systems for Advanced Applications (DASFAA), 2018.
[35] Mei Li, Dong Huang (黄栋), 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.
[36] Yue Ding, Ling Huang, Chang-Dong Wang, Dong Huang (黄栋). Community Detection in Graph Streams by Pruning Zombie Nodes, Proc. of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2017.
[37] Guang-Yu Zhang, Dong Huang (黄栋), Chang-Dong Wang and Wei-Shi Zheng. Weighted Multi-view On-line Competitive Clustering, in proceedings of IEEE International Conference on Big Data Computing Service and Applications (BigDataService), 2016.
[38] Zhi-Lin Zhao, Chang-Dong Wang, Yuan-Yu Wan, Jian-Huang Lai and Dong Huang (黄栋). FTMF: Recommendation in Social Network with Feature Transfer and Probabilistic Matrix Factorization, in proceedings of International Joint Conference on Neural Networks (IJCNN), 2016.
[39] Chao Chen, Kun-Yu Lin, Chang-Dong Wang, and Dong Huang (黄栋). 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.
[40] Xiang-You Peng, Yu-Bo Yang, Chang-Dong Wang, Dong Huang (黄栋) and Jian-Huang Lai. An Efficient Parallel Nonlinear Clustering Algorithm using MapReduce, International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics (ParLearning), 2016.
[41] 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): 418-425. (中文核心)
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SCAU DELTA Lab隶属于华南农业大学数学与信息学院，其含义为Lab for Data-cEntric Learning Technology and Applications（中文名：数据科学与机器学习实验室），研究兴趣涉及人工智能、数据挖掘、大数据分析及其他相关领域，主要研究内容包括复杂数据聚类、自监督学习、图神经网络、视觉数据分析、医学数据分析、深度学习及其应用等。
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近几年团队学生读博深造情况
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一. 指导的研究生：
（1）凌华保：2020级专硕，2023年赴中山大学攻读博士学位；
（2）蔡晓莎：2019级学硕，2022年赴中山大学攻读博士学位。
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二. 指导的本科生：
（1）梁有为：2021年赴美国加州大学圣迭戈分校（UCSD）攻读博士学位（全额奖学金）；
（2）陈曼笙：中山大学计算机学院2022级博士研究生。
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