Dr

Dr. Bailing Zhang

Lecturer
School of Computer Science and Mathematics
Victoria University of Technology

Email:   bzhang@csm.vu.edu.au

Phone:   +61 3 9919 4829

Fax:      +61 3 99194050

Dr. Bai-ling Zhang has been a lecturer in the School of Computer Science and Mathematics, Victoria University of Technology since 2003. He received his Ph.D. degree in Electrical and Computer Engineering from the University of Newcastle, NSW, Australia, in 1999. From 2000 to 2001, he was a research staff in the Media Lab., Kent Ridge Digital Labs (KRDL), Singapore, (now renamed as Agency for Science, Technology and Research). Prior to the research activities in Singapore, he worked as a postdoctoral fellow in the School of Electrical and Information Engineering, University of Sydney, Australia. Before 1995, he had been a lecturer in the South China University of Technology, Guangzhou, The People's Republic of China. His research and teaching are in the areas of Computer Graphics, Image Processing, Multimedia, and Machine Learning with applications in computer vision, health informatics and bioinformatics. His academic track record includes 13 journal publications in top level journals (including six IEEE Transactions ), and many successful research projects. He has been actively involved in many joint researches with other institutes nationally and internationally, particularly in health informatics and bioinformatics.

Teaching

Subject Taught in the past:

SCM1311 Programming

SCM3511 Image Processing

SCM5800 Object Oriented Programming

SCM2213 Computer Graphics

SCM6825 Multimeida System Design and Development,

SCM6501 Image Processing Algorithms

SCM6105 Postgraduate Minor Thesis

SCM3950 Computer Graphics for Game Programming

SCM2930 3D Web Technologies,

2007 Subject :

           RCM2213 Computer Graphics

           RCM2930 3D Web Technologies

           RCM1002 Mathematics B

Research

Machine learning with applications in computer vision, health informatics and bioinformatics.

Selected Publications

1. Donggang Yu, Tuan D. Pham, Hong Yan, Bailing Zhang and Denis I Crane, “Segmentation of Cultured Neurons using Logical Analysis of Grey”, Journal of Neuroscience Methods, Vol.166, pp. 125-137, 2007.

2. B. Zhang, P. Cerone and Y. Gao, “Robust Face Recognition by Hierarchical Kernel Associative Memory Models Based on Spatial Domain Gabor Transforms”, Journal of Multimedia, pp. 1-10, vol.1, 2006.

3. H. Zhang, B. Zhang, W. Huang and Q. Tian, “Gabor Wavelet Associative Memory for Face Recognition”, IEEE Transactions on Neural Networks, pp. 275- 278, 2005.

4. H. Zhang, B. Zhang, and Q.Tian, “A Kernel Auto-Associator Approach to Pattern Classification”, IEEE Trans on System, Man and Cybernetics –B, Vol 35, pp. 593-606, 2005.

5. B.Zhang, H.Zhang and S. Ge, “Face Recognition by Applying Wavelet Subband Representation and Kernel Associative Memories”, IEEE Transactions on Neural Networks, pp.166-177, Jan. 2004.

6. B. Zhang, R. Coggins, M.A.Jabri, D.Dersch and B. Flower “Multi-resolution Forecasting for Futures Trading Using Wavelet Decomposition”, IEEE Transactions on Neural Networks,Vol.12,No.4, pp. 765-775, July 2001.

7. B. Zhang and Z. Dong, “Adaptive Neural-Wavelet Model for Short Term Load Forecasting”, International Journal of Electric Power Systems Research, Vol.59, pp.121-129, 2001.

8. B. Zhang, M.Fu, H. Yan and M.A.Jabri, “Handwritten Digit Recognition by Adaptive-Subspace Self-organizing Map (ASSOM),” IEEE Transactions on Neural Networks, Vol.10, No 4, pp.939-945, 1999.

9. L. Huang, B. Zhang and Q.Huang , “Robust Interval Regression Analysis via Fuzzy Neural Network”, Fuzzy Sets and Systems, Vol.97, pp.337-347, 1998.

10. B. Zhang, M.Fu and H. Yan, “Handwritten Digit Recognition by a Mixture of Local Principal Component Analysis,” Neural Processing Letters, Vol.8, pp.1-12, Sept. 1998.

11. B. Zhang, M.Fu and H. Yan, “A Nonlinear Neural Network Model of Mixture of Local Principal Component Analysis: Application to Handwritten Digits Recognition,” Pattern Recognition, Vol.34, no.2, pp. 203-214, 2001.

12. B. Zhang, L. Xu and M. Fu, “Learning Multiple Causes by Competition Enhanced Least Mean Square Error Reconstruction,” International Journal of Neural Systems, Vol.7, No.3, pp.223-236, 1996.

13. B. Zhang, B.Xu and C. Kwong, “Performance Analysis of the Bidirectional Associative Memory and an Improved Model from the Matched-filtering Viewpoint,” IEEE Transactions on Neural Networks, Vol.5, No.4, pp.864-873, Sept. 1993.