王昌栋

所属研究所、院系: 
智能科学与技术研究所
职称: 
副教授
E-mail: 
wangchd3@mail.sysu.edu.cn
办公地点: 
A222
教师简介: 

王昌栋,中山大学数据科学与计算机学院副教授,博士生导师。2004年9月至2008年7月在中山大学攻读数学与应用数学专业,并同时攻读计算机科学与技术专业,2008年获得中山大学理学学士学位。2008年9月至2013年7月在中山大学硕博连读,攻读计算机应用技术专业,2013年获得中山大学工学博士学位。2011年曾获首届广州市菁英计划公派留学项目资助,作为联合培养博士生,于2011年12月至2012年11月在美国伊利诺大学-芝加哥校区留学,师从IEEE Fellow Philip S. Yu。

他的研究方向包括数据聚类、社交网络、推荐系统。他以第一作者身份或者指导学生发表了100余篇学术论文,包括IEEE TPAMI、IEEE TKDE、IEEE TCYB、IEEE TNNLS、IEEE TSMC-C、IEEE\ACM TCBB、Pattern Recognition等国际权威刊物和KDD、AAAI、IJCAI、CVPR、CIKM、ICDM、SDM、DASFAA、BIBM等国际权威会议。主持了包括广东省自然科学基金-杰出青年基金、广东特支计划“科技创新青年拔尖人才”、国家重点研发计划项目-子课题、国家自然科学基金-面上项目、国家自然科学基金-青年基金、CCF-腾讯犀牛鸟科研基金等13个项目。在教学方面,他分别获得2013/2015年IBM公司产学合作专业综合改革项目资助建设大数据平台/云计算课程,是全国20门受资助课程之一。

他是人工智能权威期刊Journal of Artificial Intelligence Research(JAIR,CCF B类SCI)的编委(AE),也是十几个国际刊物如IEEE TPAMI、JMLR、IEEE TKDE、IEEE TNNLS、IEEE TCYB、PR等的审稿人,是KDD(2019)、IJCAI(2019)、AAAI(2017、2018、2019、2020)、CIKM (2019)、IEEE ICDM (2014、2015、2016、2018、2019)的程序委员,是中国模式识别与计算机视觉学术会议PRCV 2018的网站主席。他曾参加ICDM2010(澳大利亚悉尼)、ICDM2011(加拿大温哥华)、SDM2013(美国奥斯汀)、ICMLA2014(美国底特律)、IEEE Bigdata2016(美国华盛顿)、DASFAA2018(澳大利亚黄金海岸)、ICDM2018(新加坡)、BIBM2018(西班牙马德里)等国际会议,与学术界同行交流,并16次做ORAL报告。他的ICDM2010论文荣获最佳论文提名奖;他曾获2012年微软亚洲研究院学者奖提名,2014年中国计算机学会优秀博士学位论文提名奖,2015年中国人工智能学会优秀博士学位论文奖,2017年广东特支计划“科技创新青年拔尖人才”,2018年度广东省科学技术奖(自然科学奖)一等奖(第五完成人),2018年度高等学校科学研究优秀成果奖(科学技术)二等奖(第五完成人)。他是中国人工智能学会-模式识别专业委员会委员,中国计算机学会-数据库专业委员会委员,中国计算机学会-计算机视觉专业委员会委员,CCF-YOCSEF广州副主席(2018-2019) ,CCF广州分部副主席(2019.3-2021.3)。

欢迎大二及以上本科生进团队进行科研训练:我们团队只招有激情,有动力,能吃苦的学生!想混学位的,千万别找我!但是你若想在本科生阶段学有所成,欢迎来学习,宝剑锋从磨砺出!!!

欢迎保研学生进团队攻读博士、硕士研究生:我们团队只招有激情,有动力,能吃苦的学生!想混学位的,千万别找我!但是你若想在研究生阶段学有所成,欢迎来学习,宝剑锋从磨砺出!!!

本团队长期招聘科研博士后、特聘(副)研究员。

News:

1. 本团队招聘2020年入学的直博生,欢迎有保研资格的同学提前与我联系:wangchd3@mail.sysu.edu.cn!我们团队只招:有激情,有动力,能吃苦的学生!想混学位的,千万别找我!----我的名额已满,此消息修改为:欢迎报读中山大学数据科学与计算机学院博士研究生!

2. Sept. 27: One paper accepted by IEEE TNNLS (中科院SCI一区)。

3. 2019年9月18日:祝贺我所指导的3名硕士研究生李佩珍(17级学硕)、邓智鸿(18级专硕)、施维(18级专硕)获得国家奖学金!全院二年级(学术型+专业型)+三年级硕士(学术型)约450名学生仅13个名额,其中有3人为我所指导的硕士研究生。

4. 2019年9月15日:祝贺我所指导的9名硕士研究生有7人获得一等奖助金:1)学术型硕士约前30%可以获得一等奖助金,我所指导的所有学术型硕士均拿到一等奖助金,并且名列全班前5!2)专业型硕士一届250多人仅8个一等奖助金名额,其中我所指导的邓智鸿(18级专硕)、施维(18级专硕)分别是全班第1、2名!3)重点说明:另一位2018级专业型硕士,第一作者发表了一篇IEEE ICDM(CCF B类)论文,只能拿二等奖(排名约第10)!竞争激烈,努力加油!

5. Aug. 19, 2019: I start to serve as an Associate Editor in Journal of Artificial Intelligence Research (JAIR), a premier journal in AI (CCF B).

6. Aug. 9, 2019: Three papers (Shi-Ting Zhong, fourth year undergraduate student; Yu-Xuan Ji, first year graduate student; You-Wei Liang, fourth year undergraduate student) accepted by ICDM 2019 (Premier conference in data mining, 18.5%).

7. May 10, 2019: One paper (Wu-Dong Xi, fourth year undergraduate student) accepted by IJCAI 2019 (Top conference in AI, Acceptance rate 17.9%).

8. April 30, 2019: One paper (Pei-Zhen Li, second year master student) accepted by KDD 2019 (Top conference in Data Mining, Research track, Oral, Acceptance rate 9.1%).

研究领域: 

数据挖掘、人工智能

1、网络分析(社交网络)

2、数据聚类

3、医学数据处理

4、推荐算法

5、精准教育

欢迎大二及以上本科生进团队进行科研训练;欢迎保研学生进团队攻读博士、硕士研究生;本团队长期招聘科研博士后、特聘(副)研究员。

教育背景: 

1. Visiting student at University of Illinois at Chicago, Jan. 2012-Nov.2012. Advisor: Prof. Philip S. Yu.

2. Combined master’s/PhD program: Ph.D. student in Computer Science, Sun Yat-sen University. Sept. 2010-June 2013. Advisor: Prof. Jian-Huang Lai.

3. Combined master’s/PhD program: M.Sc. in Computer Science, Sun Yat-sen University. Sept. 2008-June 2010. Advisor: Prof. Jian-Huang Lai.

4. B.S. in Applied Mathematics, Sun Yat-sen University. Sept. 2004­-June 2008.

工作经历: 

1. Assistant Professor: School of Mobile Information Engineering, Sun Yat-sen University, July 2013-Dec. 2015.

2. Assistant Professor: School of Data and Computer Science, Sun Yat-sen University, Dec. 2015-July. 2016.

3. Associate Professor: School of Data and Computer Science, Sun Yat-sen University, July. 2016-Now.

海外经历: 

1. Visiting student at University of Illinois at Chicago, Jan. 2012-Nov.2012.

获奖及荣誉: 
  1. 2018年度广东省科学技术奖(自然科学奖)一等奖;视觉鲁棒特征提取与非线性分析;全部完成人:赖剑煌,郑伟诗,谢晓华,阮邦志,王昌栋,朱俊勇,马锦华,黄剑;完成单位:中山大学,香港浸会大学.
  2. 2016年“广东特支计划”科技创新青年拔尖人才.
  3. 2016年广东省自然科学基金-杰出青年科学基金获得者.
  4. 2015年中国人工智能学会优秀博士学位论文.
  5. 2014年中国计算机学会优秀博士学位论文提名奖.
  6. SIAM SDM 2013 Student Travel Award.
  7. 2012 Microsoft Research Asia (MSRA) Fellowship Nomination Award.
  8. IEEE ICDM 2011 Student Travel Award.
  9.  IEEE ICDM 2010 Honorable Mention Award for the Best Research Paper.
  10.  IEEE ICDM 2010 Student Travel Award.
科研项目: 

1)    2019年度中山大学高校基本科研业务费-新兴学科交叉学科资助计划项目,基于脑电数据分析的人工耳蜗术后耳聋患者大脑功能康复系统建立及其临床示范应用,No. ***,2019 .01-2020.12,主持,40万

2)    2019年国家自然科学基金-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,No. 61876193,2019.01-2022.12,主持,65万

3)    2019年国家重点研发计划项目“社区风险监测与防范关键技术研究”课题5 “‘数据-计算’深度交互的社区风险情景计算与预测技术”,No. 2018YFC0809705,2018.07-2021.06,课题5中山大学负责人,69万

4)    2019年“广州市高校创新创业教育项目” 广州市大学生创新创业项目综合信息服务平台建设, No. 2019PT204,2019.01-2020.12,参与方主持,100万

5)    2016年“广东特支计划”科技创新青年拔尖人才,No. 2016TQ03X542,2017.04-2020.04,主持,30万

6)    2016年国家重点研发计划项目“面向大范围场景透彻感知的视觉大数据智能分析关键技术与验证系统”课题3“群体视觉大数据的透彻感知关键技术”,No. 2016YFB1001003,2016.07 -2020.06,课题3项目骨干,1820万

7)    2016年广东省自然科学基金-杰出青年科学基金,大数据非线性聚类方法及其应用,No. 2016A030306014,2016.06.01-2020.06.01,主持,100万

8)    2016年度中山大学高校基本科研业务费青年教师科研资助计划项目-重点培育项目,基于社交网络的大数据推荐算法及其应用,No. 67000-31620001,2016.01-2017.12,主持,30万

9)    2015年度广东省前沿与关键技术创新专项资金-重大科技专项,基于自主分布式数据库的大数据内存计算技术研发及应用,No. 2015B010108001,2013.08-2016.05,高校方主持,300万

10) 2016年国家自然科学基金-青年科学基金,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,No. 61502543,2016.01-2018.12,主持,24.6万

11) 2015年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,No. 2014A030310180,2015.01-2018.01,主持,10万

12) 2014年CCF-腾讯犀牛鸟科研基金,异构社交网络动态社区检测,No. CCF-TencentRAGR20140112,2014.09.20-2015.10.01,主持,10万

13)2013年度中山大学高校基本科研业务费青年教师科研资助计划项目-培育项目,基于计算机视觉技术的商业零售移动大数据采集与分析,No. 46000-3161006,2014.01.01 -2015.12.31,主持,15万

主要学术兼职: 

1)    Associate Editor

-       Journal of Artificial Intelligence Research (JAIR, CCF B, Since Aug. 2019).

2)    Conference Co-Chairs:

-       PRCV 2018, Website Co-chair.

3)    Program Committee Members:

-       IEEE ICDM 2014, 2015, 2016, 2018, 2019.

-       AAAI 2017, 2018, 2019, 2020.

-       KDD 2019.

-       IJCAI 2019.

-       CIKM 2019.

-       IJCAI 2018 Demo Track, IJCAI 2019 Demo Track.

-       The 8th IEEE International Conference on Big Knowledge (IEEE ICBK) 2017.

-       The 4th IEEE International Congress of Big Data Congress 2015.

4)    Reviewers:

-       IEEE TPAMI, IEEE TCYB, IEEE TKDE, IEEE TNNLS, JMLR, IEEE TII.

-       Pattern Recognition, Neural Networks, Neurocomputing, Knowledge-Based Systems, Information Sciences, KAIS.

-       Many other good journals.....

教授课程: 

1)    2013 IBM Big Data Platform Course (One of the 20 courses supported by IBM in China).

2)    2013 Fall: Linear Algebra (required course, 300 students, 100 students per class, 4 hours per class each week).

3)    2014 Spring: Numerical Analysis (selective course, 300 students, 150 students per class, 3 hours per class each week).

4)    2014 Fall: Cloud Application Development (required course, 300 students, 150 students per class, 4 hours per class each week).

5)    2015 Spring: Data Mining (selective course, 80 students, 2 hours each week).

6)    2015 Spring: Numerical Analysis (selective course, 500 students, 150 students per class, 3 hours per class each week).

7)    2015 Fall: Cloud Application Development (required course, 450 students, 150 students per class, 4 hours per class each week).

8)    2016 Cloud Computing Course (One of the 20 courses supported by IBM in China).

9)    2016 Spring: Data Mining (selective course, 25 students, 2 hours each week).

10) 2016 Spring: Numerical Analysis (selective course, 500 students, 150 students per class, 3 hours per class each week).

11) 2017 Spring: Data Mining (selective course, 120 students, 2 hours each week)

12) 2017 Fall: Cloud Application Development (required course, 300 students, 150 students per class, 4 hours per class each week).

13) 2018 Spring: Data Mining (selective course, 240 students, 120 students per class, 4 hours each week).

14) 2018 Fall: Graduate Student English (selective course for master students, 10 students, 10 students per class, 2 hours per class each week).

15) 2019 Spring: Data Mining and Machine Learning (required course, 60 students, 60 students per class, 3 hours per class each week).

16) 2020 Fall: Data Analysis Application (selective course, 60 students, 60 students per class, 2 hours per class each week).

代表性论著: 

2019:

1) Chang-Dong Wang, Zhi-Hong Deng (Undergraduate), Jian-Huang Lai* and Philip S. Yu. Serendipitous Recommendation in E-commerce using Innovator-Based Collaborative Filtering.  IEEE Transactions on Cybernetics (IF=7.384,中科院分区表1区), Vol. 49, No. 7, pp. 2678-2692, 2019.

2) Ling Huang (Graduate student), Chang-Dong Wang*, Hong-Yang Chao and Philip S. Yu. MVStream: Multi-View Data Stream Clustering. IEEE Transactions on Neural Networks and Learning Systems (IF=11.683, 中科院分区表1区), in press, 2019.

3)Pei-Zhen Li (Graduate student), Ling Huang (Graduate student), Chang-Dong Wang*, Jian-Huang Lai. EdMot: An Edge Enhancement Approach for Motif-aware Community Detection.  In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’19, CCF A, Oral presentation, Acceptance rate 9.1%), Anchorage, Alaska USA, August 4-8, 2019, pp. 479-487.

4) Wu-Dong Xi (Undergraduate), Ling Huang (Graduate student), Chang-Dong Wang*, Yin-Yu Zheng(Undergraduate), Jian-Huang Lai. BPAM: Recommendation Based on BP Neural Network with Attention Mechanism.  In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI’19, CCF A, Acceptance rate 17.9%), Macao, China, August 10-16, 2019, pp. 3905-3911.

5) Dong Huang, 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 (IF=3.438,中科院分区表2), in press, 2019.

6) Zhi-Hong Deng (Graduate student), Ling Huang(Graduate student), Chang-Dong Wang*, Jian-Huang Lai and Philip S. Yu. DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System. In Proc. of the 33rd AAAI Conf. on Artificial Intelligence (AAAI'19, CCF A, Acceptance rate 16.2%, Oral), Honolulu, Hawaii, USA, Jan. 27-Feb. 1, 2019, pp. 61-68.

7) Ling Huang (Graduate student), Chang-Dong Wang* and Hong-Yang Chao. Higher-Order Multi-layer Community Detection. In Proc. of the 33rd AAAI Conf. on Artificial Intelligence (AAAI'19, CCF A类,Poster Session), Honolulu, Hawaii, USA, Jan. 27-Feb. 1, 2019, pp. 9945-9946.

8) Ling Huang (Graduate student), Hong-Yang Chao and Chang-Dong Wang*. Multi-View Intact Space Clustering. Pattern Recognition (IF=4.582,中科院分区表2), Vol. 86, pp. 344-353, 2019.

9) Ling Huang (Graduate student), Chang-Dong Wang* and Hong-Yang Chao. oComm: Overlapping Community Detection in Multi-view Brain Network. IEEE/ACM Transactions on Computational Biology and Bioinformatics (IF=2.428,中科院分区表3区,CCF B类期刊). In press, 2019.

10) He Huang*, Changhu Wang, Philip S. Yu and Chang-Dong Wang. Generative Dual Adversarial Network for Generalized Zero-shot Learning. In Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'2019, CCF A, Acceptance rate 25.2%), Long Beach, CA, USA, June 16- June 20, 2019, pp. 801-810.

11) Shi-Ting Zhong (Undergraduate), Ling Huang (Graduate student), Chang-Dong Wang, and Jian-Huang Lai. Constrained Matrix Factorization for Course Score Prediction. In Proc. of the 19th Int. Conf. on Data Mining (ICDM'19, CCF B类, Acceptance rate 18.5%), Beijing China, Nov. 8-11, 2019, pp. ***-***.

12) Yu-Xuan Ji (Graduate student), Ling Huang (Graduate student), Heng-Ping He (Graduate student), Chang-Dong Wang*, Guangqiang Xie, Wei Shi (Graduate student), and Kun-Yu Lin (Graduate student). Multi-view Outlier Detection in Deep Intact Space. In Proc. of the 19th Int. Conf. on Data Mining (ICDM'19, CCF B类, Acceptance rate 18.5%), Beijing China, Nov. 8-11, 2019, pp. ***-***.

13) Youwei Liang (Undergraduate), Dong Huang*, and Chang-Dong Wang. Consistency Meets Inconsistency: A Unified Graph Learning Framework for Multi-view Clustering. In Proc. of the 19th Int. Conf. on Data Mining (ICDM'19, CCF B类, Acceptance rate 18.5%), Beijing China, Nov. 8-11, 2019, pp. ***-***.

14) Yi-Ming Wen (Undergraduate), Ling Huang (Graduate student), Chang-Dong Wang*, and Kun-Yu Lin (Graduate student).  Direction Recovery in Undirected Social Networks Based on Community Structure and Popularity. Information Sciences (IF=4.832, 中科院分区表1), Vol. 473, pp. 31-43, 2019.

15) Han Zhang(Undergraduate), Chang-Dong Wang*, Jian-Huang Lai and Philip S. Yu. Community Detection Using Multilayer Edge Mixture Model. Knowledge and Information Systems (IF=2.004,中科院分区表3), Vol. 60, pp. 757-779, 2019.

16) Ling Huang (Graduate student), Zhi-Lin Zhao (Graduate student), Chang-Dong Wang*, Dong Huang and Hong-Yang Chao. LSCD: Low-Rank and Sparse Cross-Domain Recommendation. Neurocomputing (IF=3.317,中科院分区表2区), Vol. 366, pp. 86-96, 2019

17) Qi-Ying Hu (Graduate student), Ling Huang (Graduate student), Chang-Dong Wang* and Hong-Yang Chao. Item Orientated Recommendation by Multi-view Intact Space Learning with Overlapping. Knowledge-Based Systems (IF=4.529, 中科院分区表2), Vol. 164, pp. 358-370, 2019.

18) Ling Huang (Graduate student), Chang-Dong Wang*, Hong-Yang Chao, Jian-Huang Lai and Philip S. Yu. A Score Prediction Approach for Optional Course Recommendation via Cross-User-Domain Collaborative Filtering. IEEE Access (IF=3.557, 中科院分区表2), Vol. 7, pp. 19550-19563, 2019.

19) Pei-Zhen Li (Graduate student), Ling Huang (Graduate student)*, Chang-Dong Wang, Chuan Li, Jian-Huang Lai. Brain Network Analysis for Auditory Disease: A Twofold Study. Neurocomputing (IF=3.317,中科院分区表2区). Vol. 347, pp. 230-239, 2019.

20) Xiuchun Xiao, Neal Xiong*, Jianhuang Lai, Chang-Dong Wang, Zhenan Sun and Jingwen Yan. A Local Consensus Index Scheme for Random-Valued Impulse Noise Detection Systems. IEEE Transactions on Systems Man Cybernetics-Systems (IF=2.35, 中科院分区表3), In press, 2019.

21) Wei Shi (Graduate student), Ling Huang (Graduate student)*, Chang-Dong Wang, Juan-Hui Li (Graduate student), Yong Tang and Cheng-Zhou Fu. Network Embedding via Community Based Variational Autoencoder. IEEE Access (IF=3.557, 中科院分区表2), Vol. 7, pp. 25323-25333, 2019.

22) Juan-Hui Li (Graduate student), Ling Huang (Graduate student)*, Chang-Dong Wang, Dong Huang, Jian-Huang Lai. PartNRL: Partial Nodes Representation Learning in Large-scale Network. IEEE Access (IF=3.557, 中科院分区表2), Vol. 7, pp. 56457-56468, 2019.

23) Kai Wang (Graduate student), Ling Huang (Graduate student)*, Chang-Dong Wang, Yong Tang and Cheng-Zhou Fu. Inter-Intra Information Preserving Attributed Network Embedding. IEEE Access (IF=3.557, 中科院分区表2), Vol. 7, pp. 79463-79476, 2019.

24) Dong Huang, Xiaosha Cai, and Chang-Dong Wang*. Unsupervised Feature Selection with Multi-Subspace Randomization and Collaboration. Knowledge-Based Systems (IF=4.529, 中科院分区表2), in press, 2019.

25) Man-Sheng Chen (Graduate student), Ling Huang (Graduate student), Chang-Dong Wang*, and Dong Huang. Multi-view Spectral Clustering via Multi-view Weighted Consensus and Matrix-decomposition based Discretization. In Proc. of the 24th International Conference on Database Systems for Advanced Applications (DASFAA'19, CCF B), Chiang Mai, Thailand, 22-25 April 2019, pp. 175-190.

26) Weixin Zeng, Xiang Zhao*, Jiuyang Tang, Jinzhi Liao and Chang-Dong Wang. Relevance-Based Entity Embedding. In Proc. of the 24th International Conference on Database Systems for Advanced Applications (DASFAA'19, CCF B), Chiang Mai, Thailand, 22-25 April 2019, pp. 300-304.

27) Guangqiang Xie*, Tianxiang Lan, Xianbiao Hu, Yang Li, Chang-Dong Wang, Yuyu Yin. Mobile Computing During Multi-Agent Systems Convergence Using Consensus Protocol-Based Neighbor Selection Strategy. IEEE Access (IF=3.557, 中科院分区表2区), Vol. 7, pp. 132937-132949, 2019.

28) Zhi-Ran Sun(Undergraduate), Yue-Xin Cai*, Shao-Ju Wang, Chang-Dong Wang, Yi-Qing Zheng, Yan-Hong Chen and Yu-Chen Chen. Multi-view Intact Space Learning for Tinnitus Classification in Resting State EEG. Neural Processing Letters (IF=1.605,中科院分区表3), Vol. 49, No. 2, pp. 611-624, 2019.

29) Pei-Zhen Li(Graduate student), Yue-Xin Cai*, Chang-Dong Wang, Mao-Jin Liang and Yi-Qing Zheng. Higher-order Brain Network Analysis for Auditory Disease. Neural Processing Letters (IF=1.605,中科院分区表3), Vol. 49, pp. 879-897, 2019.

30) Yuexin Cai, Suijun Chen, Yanhong Chen, Jiahong Li, Chang-Dong Wang, Fei Zhao, Caiping Dang, Jianheng Liang, Nannan He, Maojin Liang and Yiqing Zheng*. Altered Resting-State EEG Microstate in Sudden Sensorineural Hearing Loss Patients with Tinnitus. Frontiers in Neuroscience (IF=3.877, 中科院分区表2), Vol. 13, pp. 1-9, 2019.

31) Kai Wang (Graduate student), Lei Xu (Graduate student), Ling Huang  (Graduate student)*, Chang-Dong Wang and Jian-Huang Lai. SDDRS: Stacked Discriminative Denoising Auto-Encoder based Recommender System. Cognitive Systems Research (IF=1.425,中科院分区表4), Vol. 55, pp. 164-174, 2019.

2018:

1)Dong Huang, Chang-Dong Wang* and Jian-Huang Lai. Locally Weighted Ensemble Clustering. IEEE Transactions on Cybernetics (IF=7.384,中科院分区表1区), Vol. 48, No. 5, pp. 1460-1473, 2018.

2)Juan-Hui Li(Undergraduate), Chang-Dong Wang*, Pei-Zhen Li(Undergraduate) and Jian-Huang Lai. Discriminative Metric Learning for Multi-view Graph Partitioning. Pattern Recognition (IF=4.582,中科院分区表2), Vol. 75, pp. 199-213, 2018.

3) Ling Huang (Graduate student), Chang-Dong Wang* and Hong-Yang Chao. A Harmonic Motif Modularity Approach for Multi-layer Network Community Detection. In Proc. of the 18th Int. Conf. on Data Mining (ICDM'18, CCF B类, Acceptance rate 19.94%), Singapore, Nov. 17-20, 2018, pp. 1043–1048.

4) Ling Huang(Graduate student), Chang-Dong Wang* and Hong-Yang Chao. Overlapping Community Detection in Multi-view Brain Network. In Proc. of the 2018 Int. Conf. on Bioinformatics and Biomedicine (BIBM'18, CCF B类), Madrid, Spain, Dec. 3-6, 2018, pp. 655-658.

5) He Huang, Bokai Cao, Philip S. Yu*, Chang-Dong Wang, and Alex D. Leow. dpMood: Exploiting Local and Periodic Typing Dynamics for Personalized Mood Prediction. In Proc. of the 18th Int. Conf. on Data Mining (ICDM'18, CCF B类, Acceptance rate 19.94%), Singapore, Nov. 17-20, 2018, pp. 157–166.

6) Guang-Yu Zhang(Graduate student), 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 (IF=4.529, 中科院分区表2), Vol. 150, pp. 127-138, 2018.

7) Pei-Zhen Li(Graduate student), Ling Huang(Graduate student), Chang-Dong Wang*, Dong Huang and Jian-Huang Lai. Community Detection Using Attribute Homogenous Motif. IEEE Access (IF=3.557, 中科院分区表2区), Vol. 6, pp. 47707-47716, 2018.

8)Dong Huang*, 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 Cybernetics-Systems (IF=2.35, 中科院分区表3区), In press, 2018.

9)Lei Xu(Undergraduate), Chang-Dong Wang*, Mao-Jin Liang, Yue-Xin Cai and Yi-Qing Zheng. Brain Network Regional Synchrony Analysis in Deafness. Biomed Research International (IF=2.476,中科院分区表3), Vol. 2018, pp. 1-11, 2018.

10)Juan-Hui Li(Graduate student), Chang-Dong Wang*, Ling Huang(Graduate student), Dong Huang, Jian-Huang Lai and Pei Chen. Attributed Network Embedding with Micro-Meso Structure. In Proc. of The 23rd International Conference on Database Systems for Advanced Applications (DASFAA 2018, CCF B类), Gold Coast, Australia, May 21-24, 2018, pp. 20-36.

11)Kun-Yu Lin(Graduate student), Ling Huang(Graduate student), Chang-Dong Wang* and Hong-Yang Chao. Multi-view Proximity Learning for Clustering. In Proc. of The 23rd International Conference on Database Systems for Advanced Applications (DASFAA 2018, CCF B类), Gold Coast, Australia, May 21-24, 2018, pp. 407-423.

12)Zhi-Lin Zhao(Graduate student), Ling Huang(Graduate student), Chang-Dong Wang* and Dong Huang. Low-Rank and Sparse Cross-Domain Recommendation Algorithm. In Proc. of The 23rd International Conference on Database Systems for Advanced Applications (DASFAA 2018, CCF B类), Gold Coast, Australia, May 21-24, 2018, pp. 150-157.

13)Yi-Ming Wen(Undergraduate), Chang-Dong Wang* and Kun-Yu Lin(Graduate student). Direction Recovery in Undirected Social Networks Based on Community Structure and Popularity. In Proc. of The 23rd International Conference on Database Systems for Advanced Applications (DASFAA 2018, CCF B类), Gold Coast, Australia, May 21-24, 2018, pp. 529-537.

14) Yi-Kun Qin, Zhu-Liang Yu*, Chang-Dong Wang, Zheng-Hui Gu and Yuan-Qing Li. A Novel Clustering Method based on Hybrid K-Nearest-Neighbor Graph. Pattern Recognition (IF=4.582,中科院分区表2), Vol. 74, pp. 1-14, 2018.

15)Yuexin Cai, Dong Huang, Yanhong Chen, Haidi Yang, Chang-Dong 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 (IF=3.104, 中科院分区表2区), Vol. 12, pp. 1-9, 2018.

16)Ming-Chuan Tsai(Undergraduate), Yue-Xin Cai*, Chang-Dong Wang, Yiqing Zheng, Jia-Ling Ou and Yanhong Chen. Tinnitus Abnormal Brain Region Detection Based on Dynamic Causal Modeling and Exponential Ranking. Biomed Research International (IF=2.476,中科院分区表3区),, Vol. 2018, pp. 1-10, 2018.

 

2017:

1) Guang-Yu Zhang(Graduate student), Chang-Dong Wang*, Dong Huang and Wei-Shi Zheng. Multi-View Collaborative Locally Adaptive Clustering with Minkowski Metric. Expert Systems with Applications  (IF=3.928,中科院分区表2), Vol. 86, pp. 307-320, 2017.

2) Qi-Ying Hu(Graduate student), Zhi-Lin Zhao(Graduate student), Chang-Dong Wang*, Jian-Huang Lai. An Item Orientated Recommendation Algorithm from the Multi-view Perspective. Neurocomputing (IF=3.317,中科院分区表2). Vol. 269, pp. 261-272, 2017.

3) Chao Chen(Undergraduate), Kun-Yu Lin(Undergraduate), Chang-Dong Wang*, Jian-Bo Liu(Undergraduate), Dong Huang. CCMS: A Nonlinear Clustering Method Based on Crowd Movement and Selection. Neurocomputing (IF=3.317,中科院分区表2). Vol. 269, pp. 120-131, 2017.

4) Zhi-Lin Zhao(Graduate student), Chang-Dong Wang*, Kun-Yu Lin(Graduate student), and Jian-Huang Lai. Missing Value Learning. In Proc. of The 26th ACM International Conference on Information and Knowledge Management (CIKM 2017, CCF B类), Pan Pacific,  Singapore, Nov. 6-10, 2017, pp. 2427-2430.

5) Zhi-Lin Zhao(Graduate student), Chang-Dong Wang*, Yuan-Yu Wan and Jian-Huang Lai. Recommendation in Feature Space Sphere. Electronic Commerce Research and Applications (IF=1.954, 中科院分区表3区), Vol. 26, pp.109-118, 2017.

6) Zhi-Lin Zhao(Graduate student), Ling Huang, Chang-Dong Wang*, Jian-Huang Lai and Philip S. Yu. Low-rank and Sparse Matrix Completion for Recommendation. In Proc. of The 24th International Conference on Neural Information Processing (ICONIP 2017, CCF C类),  Guangzhou, China, Nov. 14-18, 2017, pp. 3-13.

7) Shao-Ju Wang(Undergraduate), Yue-Xin Cai, Zhi-Ran Sun(Undergraduate), Chang-Dong Wang* and Yi-Qing Zheng. Tinnitus EEG Classification Based on Multi-frequency Bands. In Proc. of The 24th International Conference on Neural Information Processing (ICONIP 2017, CCF C类),  Guangzhou, China, Nov. 14-18, 2017, pp. 788-797.

8) Yi-Ning Xu(Undergraduate), Lei Xu(Undergraduate), Ling Huang and Chang-Dong Wang*. Social and Content based Collaborative Filtering for Point-of-Interest Recommendations. In Proc. of The 24th International Conference on Neural Information Processing (ICONIP 2017, CCF C类),  Guangzhou, China, Nov. 14-18, 2017, pp. 46-56.

9) Xiang-Rui Peng(Graduate student), Ling Huang and Chang-Dong Wang*. A Hybrid Approach for Recovering Information Propagational Direction. In Proc. of The 24th International Conference on Neural Information Processing (ICONIP 2017, CCF C类),  Guangzhou, China, Nov. 14-18, 2017, pp. 357-367.

10) Dong Huang, Chang-Dong Wang* and Jian-Huang Lai. LWMC: A locally weighted meta-clustering algorithm for ensemble clustering. In Proc. of The 24th International Conference on Neural Information Processing (ICONIP 2017, CCF C类),  Guangzhou, China, Nov. 14-18, 2017, pp. 167-176.

11) Kun-Yu Lin(Undergraduate), Chang-Dong Wang*, Yu-Qin Meng(Undergraduate), and Zhi-Lin Zhao(Graduate student). Multi-view Unit Intact Space Learning. In Proc. of The 10th International Conference on Knowledge Science, Engineering and Management (KSEM 2017, CCF C类), Melbourne, Australia, Aug. 19-20, 2017, pp. 211-223.

12) Wen-Bin Liang(Undergraduate), Chang-Dong Wang* and Jian-Huang Lai. Weighted Numerical and Categorical Attribute Clustering in Data Streams. In Proc. of 2017 International Joint Conference on Neural Networks (IJCNN 2017, CCF C类), Anchorage, Alaska, USA, May 14-19, 2017, pp. 3066-3072.

13) Qian Zuo(Graduate student), Chang-Dong Wang* and Jian-Huang Lai. Text Clustering using Enhanced PLSA with Word Correlation. In Proc. of 2017 International Joint Conference on Neural Networks (IJCNN 2017, CCF C类), Anchorage, Alaska, USA, May 14-19, 2017, pp. 3216-3223.

14) Yue Ding(Undergraduate), Ling Huang, Chang-Dong Wang*, Dong Huang. Community Detection in Graph Streams by Pruning Zombie Nodes. In Proc. of the 21st Pacific Asia Conference on Knowledge Discovery and Data Mining 2017 (PAKDD’17, CCF C类), Jeju Island, Korea, May 23-26, 2017, pp. 574-585.

15) Ling Huang (Graduate student), Hong-Yang Chao* and Chang-Dong Wang. Multi-View Intact Space Clustering. In Proc. of the 4th Asian Conference on Pattern Recognition (ACPR), Nanjing, China, Nov. 26-29, 2017, pp. 500-505.

 

2016:

1) Chang-Dong Wang, Jian-Huang Lai* and Philip S. Yu. Multi-View Clustering Based on Belief Propagation. IEEE Transactions on Knowledge and Data Engineering (IF=3.438,中科院分区表2), Vol. 28, No. 4, pp. 1007-1021, April, 2016.

2) Dong Huang, Jian-Huang Lai* and Chang-Dong Wang. Robust Ensemble Clustering Using Probability Trajectories. IEEE Transactions on Knowledge and Data Engineering (IF=3.438,中科院分区表2), Vol. 28, No. 5, pp. 1312-1326, May, 2016.

3) Yu-Meng Xu(Graduate student), Chang-Dong Wang* and Jian-Huang Lai. Weighted Multi-view Clustering with Feature Selection. Pattern Recognition (IF=4.582,中科院分区表2), Vol. 53, pp. 25-35, 2016.

4) Dong Huang, Jian-Huang Lai* and Chang-Dong Wang. Ensemble Clustering Using Factor Graph. Pattern Recognition (IF=4.582,中科院分区表2), Vol. 50, pp. 131-142, 2016.

5) Dong Huang, Jian-Huang Lai* and Chang-Dong Wang. Ensembling Over-Segmentations: From Weak Evidence to Strong Segmentation. Neurocomputing (IF=3.317,中科院分区表2), Vol. 207, pp. 416-427, 2016.

6) Zhi-Lin Zhao(Undergraduate), Chang-Dong Wang* and Jian-Huang Lai. AUI&GIV: Recommendation with Asymmetric User Influence and Global Importance Value. PLoS ONE (IF=3.234,中科院分区表3区), Vol. 11, No. 2, pp. e0147944, 2016.

7) Wen-Kai Huang(Undergraduate), Chang-Dong Wang*, Shao-Shu Huang(Undergraduate), Zheng Li(Undergraduate), Jian-Huang Lai and Ling Huang. Long-Term Revenue Maximization Pricing Scheme for Cloud. Computer Systems Science & Engineering (IJCSSE) (IF=0.52, 中科院分区表4), pp. 5-13, 2016.

8) 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. In Proc. of 2016 International Conference on Pattern Recognition (ICPR 2016, CCF C类), Cancun, Mexico, Dec. 4-8, 2016, pp. 444-449.

9) Juan-Hui Li(Undergraduate), Pei-Zhen Li(Undergraduate), Chang-Dong Wang* and Jian-Huang Lai. Community Detection in Complicated Network based on the Multi-view Weighted Signed Permanence. In Proc. of the 14th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA 2016, CCF C类), Tianjin, China, Aug. 23-26, 2016, pp. 1589-1596.

10) Xun Wang(Undergraduate), Chang-Dong Wang* and Jian-Huang Lai. Modularity Optimization by Global-Local Search. In Proc. of 2016 International Joint Conference on Neural Networks (IJCNN 2016, CCF C类), Vancouver, Canada, July 24-29, 2016, pp. 840-846.

11) Zhi-Lin Zhao(Undergraduate), Chang-Dong Wang*, Yuan-Yu Wan(Undergraduate), Jian-Huang Lai and Dong Huang. FTMF: Recommendation in Social Network with Feature Transfer and Probabilistic Matrix Factorization. In Proc. of 2016 International Joint Conference on Neural Networks (IJCNN 2016, CCF C类), Vancouver, Canada, July 24-29, 2016, pp. 847-854.

12) Da-Chuan Zhang(Graduate student), Mei Li(Graduate student) and Chang-Dong Wang*. Point of Interest Recommendation with Social and Geographical Influence. In Proc. of 2016 IEEE International Conference on Big Data (IEEE BigData 2016), Washington D.C., USA, Dec. 5-8, 2016, pp. 1070-1075.

13) Yao-Ming Yang(Graduate student), Chang-Dong Wang* and Jian-Huang Lai. An Efficient Parallel Topic-Sensitive Expert Finding Algorithm Using Spark. In Proc. of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), Washington D.C., USA, Dec. 5-8, 2016, pp. 3556-3562.

 

2015:

1) Cheng-Xu Ye, Wu-Shao Wen* and Chang-Dong Wang. Chinese-Tibetan Bilingual Clustering Based on Random Walk. Neurocomputing (IF=3.317,中科院分区表2), Vol. 158, pp. 32–41, 2015.

2) Dong Huang, Jian-Huang Lai* and Chang-Dong Wang. Combining Multiple Clusterings via Crowd Agreement Estimation and Multi-Granularity Link Analysis. Neurocomputing (IF=3.317,中科院分区表2), Vol. 170, pp. 240-250, 2015.

3) Qi-Ying Hu(Undergraduate), Chang-Dong Wang*, Jia-Xin Hong(Undergraduate), Meng-Zhe Hua(Undergraduate) and Di Huang(Undergraduate). Traveller: A Novel Tourism Platform for Students Based on Cloud Data. In Proc. of 11th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2015, CCF C类), Wuhan, China, Nov. 10-11, 2015, pp. 26-35.

 

2014:

1) Chang-Dong Wang, Jian-Huang Lai* and Philip S. Yu. NEIWalk: Community Discovery in Dynamic Content-based Networks. IEEE Transactions on Knowledge and Data Engineering (IF=3.438,中科院分区表2), Vol. 26, No. 7, pp. 1734-1748, July, 2014.

2) Qing-Song Zeng, Jian-Huang Lai* and Chang-Dong Wang. Multi-Local Model Image Set Matching Based on Domain Description. Pattern Recognition (IF=4.582,中科院分区表2), Vol. 47, No. 2, pp. 697-704, 2014.

3) Xiu-Chun Xiao, Jian-Huang Lai* and Chang-Dong Wang. Parameter Estimation of the Exponentially Damped Sinusoids Signal Using a Specific Neural Network. Neurocomputing (IF=3.317,中科院分区表2), Vol. 143, pp. 331-338, 2014.

4) Dong-Wei Chen, Jian-Qiang Sheng, Jun-Jie Chen and Chang-Dong Wang*. Stability-Based Preference Selection in Affinity Propagation. Neural Computing and Applications (IF=1.168,中科院分区表3), Vol. 25, pp. 1809-1822, 2014.

 

2013:

1) Chang-Dong Wang, Jian-Huang Lai*, Ching Y. Suen and Jun-Yong Zhu. Multi-Exemplar Affinity Propagation. IEEE Transactions on Pattern Analysis and Machine Intelligence (IF=8.329,中科院分区表1), Vol. 35, No. 9, pp.2223-2237, Sept. 2013.

2) 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 (IF=3.438,中科院分区表2), Vol. 25, No. 6, pp. 1410-1424, June, 2013.

3) Chang-Dong Wang and Jian-Huang Lai*. Position Regularized Support Vector Domain Description. Pattern Recognition (IF=4.582,中科院分区表2), Vol. 46, pp. 875-884, 2013.

4) Chang-Dong Wang, Jian-Huang Lai* and Philip S Yu. Dynamic Community Detection in Weighted Graph Streams. In Proc. of 2013 SIAM Int. Conf. on Data Mining (SDM’13,CCF B), Austin, Texas, USA, May 2-4, 2013, pp. 151-161.

 

2012:

1) Chang-Dong Wang, Jian-Huang Lai* and Jun-Yong Zhu. Graph-Based Multiprototype Competitive Learning and its Applications. IEEE Transactions on Systems, Man, and Cybernetics Part C: Applications & Reviews (IF=2.02, 中科院分区表2), Vol. 42, No. 6, pp. 934-946, Nov. 2012.

2) Chang-Dong Wang, Jian-Huang Lai* and Jun-Yong Zhu. Conscience Online Learning: An Efficient Approach for Robust Kernel-Based Clustering. Knowledge and Information Systems (IF=2.004,中科院分区表2), Vol. 31, No. 1, pp. 79-104, 2012.

3) Jun Tan, Jian-Huang Lai*, Chang-Dong Wang, Wen-Xiao Wang and Xiao-Xiong Zuo. A New Handwritten Character Segmentation Method Based on Nonlinear Clustering. Neurocomputing (IF=3.317,中科院分区表2), Vol. 89, pp. 213-219, 2012.

4) Dong Huang, Jian-Huang Lai* and Chang-Dong Wang. Incremental Support Vector Clustering with Outlier Detection. In Proc. of the 21st Int. Conf. on Pattern Recognition (ICPR'12, CCF C类), Tsukuba, Japan, Nov. 11-15, 2012. pp. 2339-2342.

 

2011:

1) Chang-Dong Wang and Jian-Huang Lai*. Energy Based Competitive Learning. Neurocomputing (IF=3.317,中科院分区表2), Vol. 74, pp. 2265-2275, 2011.

2) Chang-Dong Wang, Jian-Huang Lai* and Dong Huang. Kernel-Based Clustering with Automatic Cluster Number Selection. In Proc. of the ICDM 2011 Workshop on The 6th Workshop on Optimization Based Techniques for Emerging Data Mining Problems, Vancouver, Canada, Dec. 11-14, 2011, pp. 293-299.

3) Chang-Dong Wang, Jian-Huang Lai* and Dong Huang. Incremental Support Vector Clustering. In Proc. of the ICDM 2011 Workshop on Large Scale Visual Analytics, Vancouver, Canada, Dec. 11-14, 2011, pp. 839-846.

4) Chang-Dong Wang, Jian-Huang Lai* and Wei-Shi Zheng. Message-Passing for the Traveling Salesman Problem. In CVPR 2011 Workshop on Inference in Graphical Models with Structured Potentials, Colorado Springs, USA, June 20-25, 2011.

5) Jian-Sheng Wu, Jian-Huang Lai* and Chang-Dong Wang. A Novel Co­clustering method with Intra-Similarities. In ICDM 2011 Workshop on The 6th Workshop on Optimization Based Techniques for Emerging Data Mining Problems, Vancouver, Canada, Dec. 11-14, 2011, pp. 300-306.

 

2010:

1) Chang-Dong Wang, Jian-Huang Lai* and Jun-Yong Zhu. A Conscience On­line Learning Approach for Kernel-Based Clustering. In Proc. of the 10th Int. Conf. on Data Mining (ICDM'10, CCF B), Sydney, Australia, Dec. 14-17, 2010, pp. 531–540. (Regular paper, acceptance rate 72/797=9%). This paper is selected as a honorable mention for the "Best Research Paper" award, ranking the 4th among 155 accepted papers.

 

Book Chapters:

1) Chang-Dong Wang and Jian-Huang Lai*. Nonlinear Clustering: Methods and Applications, in Book “Unsupervised Learning Algorithms”, edited by M. Emre Celebi and Kemal Aydin. Springer, 2016, pp. 253-302