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。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五十多篇学术论文,包括IEEE TPAMI、IEEE TKDE、IEEE TSMC-C和Pattern Recognition等国际权威刊物和IEEE ICDM、SIAM SDM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(100万)、国家自然科学基金-青年基金(24.6万)、中山大学科研培育项目-重点培育项目(30万)、广东省自然科学基金-博士启动(10万)、CCF-腾讯犀牛鸟科研基金(10万)、中山大学科研培育项目基金等科研基金(15万),以及相关企业的委托/合作研究项目,作为课题骨干参与了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)。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。

他目前是十几个国际刊物如IEEE TPAMI、IEEE TKDE、IEEE TNNLS、IEEE TSMC-B、PR等的审稿人,是IEEE ICDM 2014、IEEE ICDM 2015、IEEE ICDM 2016、IEEE International Congress of Big Data 2015,AAAI 2016的程序委员。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)等国际会议,与学术界同行交流,并5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”。他是中国人工智能学会-模式识别专业委员会委员。

研究领域: 

数据挖掘、人工智能、大数据分析:

1、推荐算法

2、社交网络社区发现

3、数据聚类

4、基于MapReduce的大数据处理

 

教育背景: 

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

Advisor: Prof. Philip S. Yu.

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

Advisor: Prof. Jian-Huang Lai.

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

Advisor: Prof. Jian-Huang Lai.

-      

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

工作经历: 

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

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

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

海外经历: 

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

 

获奖及荣誉: 
  1. 2016年“广东特支计划”科技创新青年拔尖人才.
  2. 2016年广东省自然科学基金-杰出青年科学基金获得者.
  3. 2015年中国人工智能学会优秀博士学位论文.
  4. 2014年中国计算机学会优秀博士学位论文提名奖.
  5. 2012 Microsoft Research Asia (MSRA) Fellowship Nomination Award.
  6. IEEE ICDM 2010 Honorable Mention Award for the Best Research Paper.
科研项目: 

1)    2016年“广东特支计划”科技创新青年拔尖人才(No. ****) (PI, 300,000RMB)

2)    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) (课题3项目骨干, 18,200,000 RBM)

3)    2016年广东省自然科学基金-杰出青年科学基金(No. 2016A030306014) (PI, 1,000,000 RMB)

4)    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(No. 67000-31620001) (PI, 300,000RMB)

5)    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)(No. 2015B010108001) (Co-PI, 3,000,000 RMB)

6)    2016年国家自然科学基金-青年科学基金(No. 61502543) (PI, 246,000 RMB)

7)    2015年广东省自然科学基金-博士启动项目(No. 2014A030310180) (PI, 100,000 RMB)

8)    2014年CCF-腾讯犀牛鸟科研基金(No. CCF-TencentRAGR20140112) (PI, 100,000 RMB)

9)    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(No. 46000-3161006) (PI, 150,000 RMB)

主要学术兼职: 

1) Reviewer of IEEE Transactions on Cybernetics (previously named IEEE Transactions on Systems, Man, and Cybernetics--Part B:  Cybernetics) (Since Dec. 2011)

2) Reviewer of IEEE Transactions on Neural Networks and Learning Systems (previously named IEEE Transactions on Neural Networks) (Since March 2012)

3) Reviewer of International Journal of Computational Intelligence Systems (Since July 2012)

4) Reviewer of Pattern Recognition (Since Sept. 2012)

5) Reviewer of PLOS ONE (Since Nov. 2012)

6) Editorial Board of Journal of Pattern Recognition and Intelligent Systems (PRIS) (Since March 2013)

7) Reviewer of Neurocomputing (Since May 2013)

8) Reviewer of Journal of Circuits, Systems and Computers (Since July 2013)

9) Advisory Board Member of World Research Journal of Pattern Recognition (from July, 2013 to July 2016)

10) Reviewer of IEEE Transactions on Knowledge and Data Engineering (Since Sept 2013)

11) Reviewer of IEEE Transactions on Pattern Analysis and Machine Intelligence (Since Feb. 2014)

12) Program Committee Member of IEEE ICDM 2014.

13) Technical Committee Member of The 4th IEEE International Congress of Big Data Congress 2015.

14) Program Committee Member of IEEE ICDM 2015.

15) Reviewer of Big Data (Since Oct. 2015).

16) Program Committee Member of IEEE ICDM 2016.

17) SpringerPlus (Since April 2016).

18) Big Data Analytics (Since May 2016).

19) Reviewer of Applied Informatics (Since July 2016).

20) Program Committee Member of AAAI 2017.

21) Reviewer of Physica A (Since Nov. 2016).

22) Reviewer of Pervasive and Mobile Computing (Since Jan. 2017).

23) Program Committee Member of The 8th IEEE International Conference on Big Knowledge (IEEE ICBK) 2017.

24) Reviewer of Information Sciences (Since March 2017).

25) Reviewer of Knowledge-Based Systems (Since March 2017).

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)

代表性论著: 

Publications (sorted by acceptance date):

  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=2.29), Vol. 28, No. 4, pp. 1007-1021, April, 2016.
  2. 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=2.29), Vol. 26, No. 7, pp. 1734-1748, July, 2014.
  3. 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= 5.694), Vol. 35, No. 9, pp.2223-2237, Sept. 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’13CCF B), Austin, Texas, USA, May 2-4, 2013, pp. 151-161.
  5. Chang-Dong Wang and Jian-Huang Lai. Position Regularized Support Vector Domain Description. Pattern Recognition (IF=2.584), Vol. 46, pp. 875-884, 2013.
  6. 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=2.29), Vol. 25, No. 6, pp. 1410-1424, June, 2013.
  7. 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), Vol. 42, No. 6, pp. 934-946, Nov. 2012.
  8. 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=2.639), Vol. 31, No. 1, pp. 79-104, 2012.
  9. Chang-Dong Wang and Jian-Huang Lai. Energy Based Competitive Learning, Neurocomputing (IF=2.005), Vol. 74, pp. 2265-2275, 2011.
  10. 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. ISBN: 978-3-319-24209-5.  Switzerland. Springer, 2016, pp. 253-302.

 

Corresponding Authors’ Publications (*Undergraduate student, #Graduate student):

  1. Dong Huang, Chang-Dong Wang and Jian-Huang Lai. Locally Weighted Ensemble Clustering. IEEE Transactions on Cybernetics, In press, 2017.
  2. Wen-Bin Liang*, 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.
  3. Qian Zuo#, 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.
  4. Yue Ding*, 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.***-***.
  5. Qi-Ying Hu#, Zhi-Lin Zhao#, Chang-Dong Wang, Jian-Huang Lai. An Item Orientated Recommendation Algorithm from the Multi-view Perspective. Neurocomputing (IF=2.005), in press 2016.
  6. 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 (IF=2.005), in press 2016.
  7. Da-Chuan Zhang#, Mei Li# 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.
  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. ***-***.
  9. Juan-Hui Li*, Pei-Zhen Li*, 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*, 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*, Chang-Dong Wang, Yuan-Yu Wan*, 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. Zhi-Lin Zhao*, Chang-Dong Wang and Jian-Huang Lai. AUI&GIV: Recommendation with Asymmetric User Influence and Global Importance Value. PLoS ONE (IF=3.234), Vol. 11, No. 2, pp. e0147944, 2016.
  13. Yu-Meng Xu#, Chang-Dong Wang and Jian-Huang Lai. Weighted Multi-view Clustering with Feature Selection. Pattern Recognition (IF=2.584), Vol. 53, pp. 25-35, 2016.
  14. Wen-Kai Huang*, Chang-Dong Wang, Shao-Shu Huang*, Zheng Li*, Jian-Huang Lai and Ling Huang. Long-Term Revenue Maximization Pricing Scheme for Cloud. Computer Systems Science & Engineering (IJCSSE) (IF=0.52), pp. 5-13, 2016.
  15. Qi-Ying Hu*, Chang-Dong Wang, Jia-Xin Hong*, Meng-Zhe Hua* and Di Huang*, 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.
  16. Han Zhang*, Chang-Dong Wang and Jian-Huang Lai. Topic Detection in Instant Messages. in Proc. of the 13th Int. Conf. on Machine Learning and Applications (ICMLA’14),  Detroit, MI USA, Dec. 3-6, 2014, pp. 219-224.

Co-authored Papers (sorted by acceptance date,* corresponding author):

  1. Dong Huang, Jian-Huang Lai* and Chang-Dong Wang. Ensembling Over-Segmentations: From Weak Evidence to Strong Segmentation, Neurocomputing (IF=2.005), Vol. 207, pp. 416-427, 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=2.29), Vol. 28, No. 5, pp. 1312-1326, May, 2016.
  3. Dong Huang, Jian-Huang Lai* and Chang-Dong Wang, Ensemble Clustering Using Factor Graph, Pattern Recognition (IF=2.584), Vol. 50, pp. 131-142, 2015.
  4. Cheng-Xu Ye, Wu-Shao Wen* and Chang-Dong Wang. Chinese-Tibetan Bilingual Clustering Based on Random Walk. Neurocomputing (IF=2.005), Vol. 158, pp. 32–41, 2015.
  5. 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), Vol. 25, pp. 1809-1822, 2014.
  6. 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=2.005), Vol. 143, pp. 331-338, 2014.
  7. Dong Huang, Jian-Huang Lai* and Chang-Dong Wang. Combining Multiple Clusterings via Crowd Agreement Estimation and Multi-Granularity Link Analysis. Neurocomputing (IF=2.005), Vol. 170, pp. 240-250, 2015.
  8. Qing-Song Zeng, Jian-Huang Lai* and Chang-Dong Wang. Multi-Local Model Image Set Matching Based on Domain Description. Pattern Recognition (IF=2.584), Vol. 47, No. 2, pp. 697-704, 2014.
  9. 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.
  10. 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=2.005), Vol. 89, pp. 213-219, 2012.