ZHANG Haijun
Address:
Room 710, Bld. G, HITSGS Campus, Shenzhen University Town, Xili, Shenzhen, China, 518055 (518055)
Email:
hjzhang@hit.edu.cn
Phone:
26033086
26033008(Fax)
PERSONAL PROFILE
 
RESEARCH INTEREST
 
Massive data mining, Social intelligence, Statistical machine learning, Classification/ Clustering, Optimization.
EDUCATION  
Sep. 2007 - Oct. 2010
Ph.D. from the Department of Electronic Engineering, City University of Hong Kong, Hong Kong.
Sep. 2004 - Mar. 2007
Master of Engineering (MEng) degree from the Department of Control Theory and Engineering, Northeastern University, P.R. China.
Sep. 2000 - Jun. 2004
Bachelor of Science (B.Sc) degree (First Class Hons) from the Department of Traffic Control Engineering, Northeastern University, P.R. China.
RESEARCH & WORK EXPERIENCE  
Mar. 2012 - present
Associate Professor, Shenzhen Graduate School, Harbin Institute of Technology, P.R. China.
Nov. 2010 - Nov. 2011
Postdoctorial Research Fellow, Department of Electrical and Computer Engineering, University of Windsor, Canada.
PROFESSIONAL QUALIFICATION & ACADEMIC SERVICE
 
RESEARCH PROJECTS
2012.9-2014.8
Shenzhen Foundamental Research Fund, entitled by Semantic Analysis of Long Documents
2014.1-2016.12
China NSF, entitled by classifying social media users using heterogeneous features
RESEARCH ACHIEVEMENT & AWARDS
PATENT
   
PAPER & BOOK PUBLICATIONS
Selected published papers:

[1]. Qingyao Wu, Yunming Ye, Haijun Zhang and Shenyang Ho. ML-TREE: A Tree-Structure Based Approach to Multi-Label Learning. IEEE Transactions on Neural Networks and Learning Systems, 2015, vol. 26, no. 3, pp. 430-443.
[2]. Xiaohui Huang, Yunming Ye and Haijun Zhang. Extensions of Kmeans-type Algorithms: A New Clustering Framework by Integrating Intra-cluster Compactness and Inter-cluster Separation. IEEE Transactions on Neural Networks and Learning Systems, 2014, 25(8), 1433-1446.
[3]. Qingyao Wu, Yunming Ye, Haijun Zhang, Michael K. Ng and Shenyang Ho. ForesTexter: An Efficient Random Forest Algorithm for Imbalanced Text Categorization. Knowledge Based Systems, Volume 67, September 2014, Pages 105–116.
[4]. Xiaohui Huang, Yunming Ye, Huifeng Guo, Yi Cai, Haijun Zhang and Yan Li. DSKmeans: A New Kmeans-type Approach to Discriminative Subspace Clustering. Knowledge Based Systems, Volume 70, November 2014, Pages 293–300.
[5]. Yixiang Fang, Haijun Zhang, Yunming Ye, and Xutao Li. Detecting Hot Topics from Twitter: A Multi-View Approach. Journal of Information Science, 2014: 0165551514541614.
[6]. Haijun Zhang, John K. L. Ho, Jonathan Q. M. Wu, and Yunming Ye. Multi-Dimensional Latent Semantic Analysis Using Term Spatial Information. IEEE Transactions on Systems, Man and Cybernetics-Part B, 2013, vol. 43, no. 6, pp. 1625-1640.
[7]. Haijun Zhang, Jonathan Q. M. Wu , Tommy W. S. Chow, and Mingbo Zhao. A Two-Dimensional Neighborhood Preserving Projection for Appearance-Based Face Recognition. Pattern Recognition, 2012, vol. 45, no. 5, pp. 1866-1876.
[8]. Haijun Zhang, Gang Liu, Tommy W. S. Chow and Wenyin Liu. Textual and Visual Content-based Anti-phishing: A Bayesian Approach. IEEE Transactions on Neural Networks, 2011, vol. 22, no. 10, pp. 1532-1546.
[9]. Haijun Zhang, Jaime Llorca, Christopher C. Davis and Stuart D. Milner. Nature-Inspired Self-Organization, Control and Optimization in Heterogeneous Wireless Networks. IEEE Transactions on Mobile Computing, 2012, vol.11, no. 7, pp. 1207-1222.
[10]. Haijun Zhang and Tommy W. S. Chow. A Multi-level Matching Method with Hybrid Similarity for Document Retrieval. Expert Systems With Applications, 2012, vol. 29, no.3, pp. 2710-2719.
[11]. Haijun Zhang and Tommy W. S. Chow. A Coarse-to-Fine Framework to Efficiently Thwart Plagiarism. Pattern Recognition, 2011, vol. 44, no. 2, pp. 471-487.
[12]. Haijun Zhang, Tommy W. S. Chow, and M. K. M. Rahman. A New Dual Wing Harmonium Model for Document Retrieval. Pattern Recognition, 2009, vol. 42, no. 11, pp.2950-2960.
[13]. Tommy W. S. Chow, Haijun Zhang, and M. K. M. Rahman. A New Document Representation Using Term Frequency and Vectorized Graph Connectionists with Application to Document Retrieval. Expert Systems With Applications, 2009, 36(10): 12023-12035.
[14]. Haijun Zhang, Tommy W. S. Chow, and M. K. M. Rahman. A Novel Dual Wing Harmonium Model Aided by 2-D Wavelet Transform Subbands for Document Data Mining. Expert Systems With Application, 2010, vol. 37, no. 6, pp. 4403-4412.
[15]. A.Y.T Leung and Haijun Zhang. Particle swarm optimization of tuned mass dampers. Engineering Structures. 2009, 31: 715-728.
[16]. A.Y.T Leung, Haijun Zhang, C.C. Cheng and Y.Y. Lee. Particle swarm optimization of TMD by non-stationary base excitation during earthquake. Earthquake Engineering and Structural Dynamics, 2008, 37: 1223-1246.
CONFERENCE PAPERS/TALKS
 
[1]. Mingbo Zhao, Zhao Zhang and Haijun Zhang. A Soft Label Based Linear Discriminant Analysis for Semi-Supervised Dimensionality Reduction. International Joint Conference on Neural Networks. Aug. 2013, no.1041,pp.1-8.
[2]. Mingbo Zhao, Haijun Zhang and Zhao Zhang. Learning from Local and Global Discriminative Information for Semi-Supervised Dimensionality Reduction. International Joint Conference on Neural Networks. Aug. 2013, no.1107, pp.1-8.
[3]. Haijun Zhang, Shifu Bie and Bin Luo. Classifying Web Documents Using Term Spectral Transforms and Multi-Dimensional Latent Semantic Representation. International Joint Conference on Neural Networks. Jul. 2014, pp.1320-1327.
[4]. Xiong Cao, Haijun Zhang. Content-based Video Advertising: A General Framework. The 2nd International Conference on Computing, Measurement, Control and Sensor Network, Taiwan, May 2014.
[5]. Haijun Zhang, Tommy W. S. Chow and Anthony Fong. Generalized Particle Swarm Optimizers with Tracking Multiple Local Optima for Multimodal Functions Optimization. International Conference of Computing in Engineering, Science, and Information (ICC2009), Fullerton, Los Angeles, California, USA, Apr. 2009.
[6]. Haijun Zhang, Jaime Llorca, Christopher C. Davis, and Stuart D. Milner. A Novel Flocking Inspired Algorithm for Self-Organization and Control in Heterogeneous Wireless Networks. ISSNIP, Dec. 2010.
TEACHING/SUPERVISING EXPERIENCE
Teaching
Modeling of Complex Networks, 32 Hours/ 2 Credits
Data Mining, 32 Hours/2 Credits, (For Engineering Masters)
Supervising
4 MSc. Students and 1 Ph.D. Student / Each Year.
Current Students:
Yuzhu Ji,PhD student,2015;
Lu Lu,Msc,2013;
Jingxuan Li,Msc,2013;
Zhengqi Li,Msc,2013;
Yusong An,Msc,2013;
Yusheng Wang,Msc,2014;
Fengxin Li,Msc,2014;
FAROOQ MUHAMMAD OMER,Msc,2014(International student from Pakistan);

Graduate Students:
Xiong Cao,Tencent QQ(Beijing),2014.12;
Bin Luo,Baidu(Shenzhen),2014.12。
Updated:2017-09