JIANG Qingshan

Date:25-07-2017   |   【Print】 【close

JIANG Qingshan


Professor, Researcher Fellow, Doctoral Tutor
Shenzhen Institutes of Advanced Technology
Chinese Academy of Science
Email: qs.jiang@siat.ac.cn
Telephone: 0755-86392340
Address: 1068 Xueyuan Avenue, Shenzhen University Town Shenzhen, China
Postcode: 518055  


Research Areas 

Data mining, information security, pattern recognition, Massive data analysis, database technology  



He received a Ph.D. in mathematics from Chiba Institute of Technology, Japan in 1996; and a Ph.D. in computer science from University of Sherbrooke, Canada in 2002. He worked as a post-doc fellow at The Fields Institute for Research in Mathematical Sciences, University of Toronto, Canada since February 1999 to January 2000.  



  1. The State Council allowance winner, Shenzhen local level leading talent. 
  2. The executive director of the Shenzhen Key Laboratory for High Performance Data Mining. 



Work Experience 

Qingshan Jiang is a professor at Shenzhen Key Lab for High Performance Data Mining of Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China since November 2010. He has been a professor at Xiamen University since November 2003 to October 2010,and has more than 160 publications.  

Teaching Experience 

He has been teaching at Xiamen University since 2003 as a full professor and had more than 100 graduate students at his Lab. He is teaching a course of Multivariate Data Analysis for  PhD students. 


Representative Publications 

  1. Wei Zhang, Qingshan Jiang, Lifei Chen, Chengming Li,Two-stage ELM for phishing Web pages detection using hybrid features, World Wide Web Journal,2016; 
  2. Guo Shun, Qingshan Jiang, Lifei Chen and Donghui Guo, Gene Regulatory Network Inference using PLS-based Methods,BMC Bioinformatics,2016, 17:545; 
  3. Guo S, D. Guo, L. Chen, Q.Jiang, A centroid-based gene selection method for microarray data classification, Journal of Theoretical Biology, 400: 32-41,2016; 
  4. Khan I., J.Z.Huang, MA. Masud, and Q.Jiang, Segmentation of Factories on Electricity Consumption Behaviors Using Load Profile Data, IEEE Access, Vol.40,8395-8406,2016; 
  5. Hasan, A. S. M., Qingshan Jiang*, Jun Luo, Chengming Li, and Lifei Chen. An effective value swapping method for privacy preserving data publishing,Security and Communication Networks, Vol. 9, No. 16, 3219– 3228,2016( http://dx.doi.org/10.1002/sec.1527) 
  6. Zhang W., Ren H.,Jiang Q.,Application of feature engineering for phishing detection. IEICE Transactions on Information & Systems, E99.D(4), 1062-1070,2016(SCI);   
  7. Wang Ran, Kwong Sam,Wang Xizhao, Jiang Qingshan, Segment Based Decision Tree Induction With Continuous Valued Attributes, IEEE TRANSACTIONS ON CYBERNETICS,Vol.45 No.7,1261-1275,2015(SCI) ; 
  8. Tengke Xiong, Shengrui Wang, Qingshan Jiang and Joshua Zhexue Huang. A novel variable-order Markov model for clustering categorical sequence. IEEE Transactions on Knowledge and Data Engineering, Vol 26(10), 2339-2353, 2014; 
  9. Pan Jiacai, Qingshan Jiang, Shao, Zheping, Trajectory Clustering by Sampling and Density ,Marine Technology Society Journal, 48(6) 74-85, 2014/12(SCI); 
  10. Aftab A. C., B. Kashif,  B , T. Nikos, Z. Yu , Qingshan Jiang, S. U. Khan, and C. Xu, A comparative study on resource allocation and energy efficient job scheduling strategies in large-scale parallel computing systems, Cluster Computing, 17, Issue 4, 1349-1367,2014; 
  11.  Shang C., Ming Li, S. Feng, Q. Jiang, Jianping Fan, Feature selection via maximizing global information gain for text classification,Knowledge-Based Systems, Volume 54, Pages 298–309, 2013(SCI:261SV ); 
  12. Dan Wei, Huiling Zhang, Yanjie Wei, Qingshan Jiang, A Novel Splice Site Prediction Method using Support Vector Machine. Journal of Computational Information Systems, 2013,9(20): 8053-8060. (EI:20134616980384); 
  13. Dan Wei, Qingshan Jiang, Yanjie Wei, Shengrui Wang, A Novel Hierarchical Clustering Algorithm for Gene Sequences, BMC Bioinformatics2012,13:174 (SCI: 944LB); 
  14. L.Chen, Q.Jiang, S. Wang. Model-based Method for Projective Clustering, IEEE Transactions on Knowledge and Data Engineering, Volume: 24 , Issue: 7 Page(s): 1291 – 1305, 2012; 
  15. Weiwei Zhuang, Qingshan Jiang, Intelligent anti-phishing framework using multiple classifiers combination, Journal of Computational Information Systems, Volume: 8, Issue:17, 7267-7281,2012 (EI: 20123915472596); 
  16. Tengke Xiong, Shengrui Wang, Qingshan Jiang, Joshua Zhexue Huang, A New Markov Model for Clustering Categorical Sequences,IEEE ICDM 2011, 854-863.( EI: 20120814794812); 
  17. Qingshan Jiang, Yanping Zhang, Lifei Chen. An Initialization Method for Subspace clustering Algorithm. Journal of Intelligent Systems and Applications, Volume 3, Number 3,54-61,2011; 
  18. Qingshan Jiang, Sheng Li, Shun Guo, Dan Wei, A New Model for Finding Approximate Tandem, Journal of Software, Vol. 6, No. 3, pp386-394,2011 (EI:20111313877734); 
  19. Yanfang Ye, Tao Li, Qingshan Jiang, Youyu Wang,CIMDS: Adapting Postprocessing Techniques of Associative Classification for Malware Detection,IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews,Vol.40 No.3, 298-307,2010 (SCI: 583NI,EI: 20101712883045); 
  20. Kelil A.,S.Wang,Q.Jiang and R. Brzezinski, "A general measure of similarity for categorical sequences", Journal of Knowledge and Information Systems, Volume 24, Number 2, 197-220,2010(SCI:630DB); 
  21. Yanfang.Ye, Tao Li, K.Huang, Q. Jiang, Y. Chen. Hierarchical Associative Classifier (HAC) for Malware Detection from the Large and Imbalanced Gray List. Journal of Intelligent Information Systems, 35 (1), pg. 1-20, 2010,    SCI:619XQ,EI:20102813066242); 
  22. L. Chen, Q.Jiang, S.Wang. Model-based Method for Projective Clustering, IEEE Transactions on Knowledge and Data Engineering, Volume: 24 , Issue: 7 Page(s): 1291 – 1305, 2012; 
  23. Qingshan Jiang, Yanping Zhang, Lifei Chen. An Initialization Method for Subspace clustering Algorithm. Journal of Intelligent Systems and Applications, Volume 3, Number 3,54-61,2011; 
  24. Qingshan Jiang, Sheng Li, Shun Guo, Dan Wei, A New Model for Finding Approximate Tandem, Journal of Software,Vol. 6, No. 3, pp386-394,2011 (EI:20111313877734).