School of Science, Engineering and Information Technology

Dr Paul Pang - Research

Graduate research supervisions

Completed doctorate student supervision

  • Risk Analysis of Pest Survival and Establishment (Ph.D. Candidate: Snjezana Soltic, Associate Supervisor 2005-2007, AUT)
  • Novel Bioinformatics methods for understanding gene regulation (Ph.D. Candidate: Vishal Jain, Associate Supervisor, 2004-2008, AUT)
  • Curiosity-Driven Multi-Agent Competitive and Cooperative LDA Learning, (PhD Candidate: Naoki Shimo at the Graduate School of Life Science and Systems Engineering, Kitakyushu Institute of Technology, Primary Supervisor, 2006-2009, KIT, Japan)
  • Incremental Learning for Environmental Pollution monitoring, examination and prediction (Doctorate Student: Lei Song, Primary Supervisor, 2010-2014, Unitec)
  • Computational land use management of public spaces in New Zealand (Doctorate Student: Simon Dacey, Primary Supervisor, 2010-2017, Unitec)
  • 24-hour Boat-Flow Analysis and Counting in a Specific Harbour-Area Based on Computer Vision (Doctorate Student: Jane Zhao, Primary Supervisor, 2013~2016, Unitec)
  • Incremental and Parallel Learning Algorithms for Data Stream Knowledge Discovery (PhD Student: Lei Zhu, Primary Supervisor 2015~2017, joint with Nara Institute of Science and Technology, Japan)

Completed masters student supervision

  • Gene Selection Based on Consistency Modelling, Algorithms and Applications (Master Candidate: Raphael Wu, Graduated in 2006 with his Master thesis graded A+ and the School best Master student Award of 2006, Primary Supervisor, 2005-2006, AUT)
  • Multi-resolution call centre agent prediction over call volume data forecast (Master Candidate: Rafiq Ahmed Mohammed, Primary Supervisor, 2007-2008, AUT)
  • Developing a Mobile Robot with Curiosity-driven Discrimination Intelligence (Master Candidate:  Sean William Gordon, Primary Supervisor, 2008-2009, AUT)
  • Active Mode Incremental Nonparametric Discriminant Analysis Learning (Master Candidate: Kshitij Dhoble, Primary Supervisor, 2009-2010, AUT)
  • Multi-label classification for simultaneous internet intrusion detection and categorization (MPhil Candidate: Gary Chen, Primary Supervisor,  2008-2009, AUT)
  • Informative correlation extraction from and for Forex market analysis (Master Candidate: Lei Song, Primary Supervisor, 2009-2010, AUT)
  • An MEB based Learner Independence Multi-task Learning Algorithm (Master Candidate: Fan Liu, Primary supervisor, 2009-2010, AUT)
  • Meta Learning on String Kernel SVM for String Discrimination (Master Candidate: Nuwan Alima, Primary Supervisor, 2009-2010, AUT)
  • Multi-agent collaborative learning for Intrusion Detection (Master Candidate: Yiming Peng, Primary Supervisor, Graduated in 2011 with his Master thesis graded A+ and the School best Master student Award of 2011 Primary Supervisor, 2010-2011, AUT)
  • Weighted Incremental LPSVM for Dynamic Class Imbalance Data Streams (Master Candidate: LeiZhu, Graduated in 2012 with his Master thesis graded A+, Primary Supervisor, 2010-2012, Unitec)
  • Identifying Methods to Determine the Accuracy of Budgets for Small and Medium-sized Enterprises (SMEs) in New Zealand (Master Student: Antonio Yip, 2011-2012, Unitec)
  • A Java-based Multi-agent Decentralized Security Platform (Master Student: YouLi, Primary Supervisor, 2012-2013, Unitec)
  • A Quantum-inspired Competitive Coevolution Evolutionary Algorithm (Master Student: Sreenivas, Primary Supervisor, 2013-2014, Unitec)
  • Stock Products Ranking by Computational Correlation Analysis, (Master Student: Peter Ruibin Zhang, Primary Supervisor, 2012-1013, Unitec)
  • Evolutionary Dynamics of Complex Networks: Structure and Analysis of A Scientific Co-Author Network, (Master Student: Bernd Martin, Primary Supervisor, 2012-2013, Unitec)
  • An Air Quality Monitoring and Alert Service for Mobile Devices (Master Student: Sebastian Walther, Associate Supervisor 2016~2017 joint with Technische Universität Berlin, funded by DAAD, Germany)

Research publications/conferences

  1. Pang S., Zhang, X., Ikeda, K., Puthal D., Li,  J. and Sarrafzadeh, A. (2019) Editorial The convergent Study of Big Data Processing, Cloud and IoT, Computational Intelligence Journal, vol. 35, no. 3, pp. 474, Willey.
  2. Ratana R., Sharifzadeh H., Krishnan J. and Pang S. (2019) A Comprehensive Review of Computational Methods for Automatic Prediction of Schizophrenia With Insight Into Indigenous Populations, Frontiers in Psychiatry, doi: 10.3389/fpsyt.2019.00659
  3. Zhu, L. Ikeda, K. Pang, S. Ban, T. and  Sarrafzadeh A. (2018) Merging weighted SVMs for parallel incremental learning. Neural Networks vol. 100, pp. 25-38.
  4. Pang, S. Komosny, D. Zhu, L. Zhang, R. Sarrafzadeh, A. Ban, T. and Inoue, D. (2017) Malicious Events Grouping via Behavior Based Darknet Traffic Flow Analysis. Wireless Personal Communications, vol. 96, no. 4, pp. 5335-5353.
  5. Zhang, Y. Zhou, J.  Xiang, Y. Zhang, LY. Chen, F. Pang, S. and Liao X. (2017) Computation outsourcing meets lossy channel: Secure sparse robustness decoding service in multi-clouds, IEEE Transactions on Big Data, doi: 10.1109/TBDATA.2017.2711040
  6. Zhu, L. Pang, S.  Sarrafzadeh, A. and Ban, T. (2016) Inoue D, Incremental and Decremental Max-Flow for Online Semi-Supervised Learning (2016) IEEE Transactions on Knowledge and Data Engineering,  vol. 28, no. 8, pp. 2115-2127.
  7. Pang, S. Zhao, J. Hartill B., and Sarrafzadeh, A. (2016) Modelling Land Water Composition Scene for Maritime Traffic Surveillance. International Journal of Applied Pattern Recognition, 2016 Vol.3, no.4, pp.324 – 350.
  8. Pang, S Zhu, L. Chen, G. Sarrafzadeh, A. Ban, T. and Inoue D. (2013) Dynamic class imbalance learning for incremental LPSVM, Neural Networks, no. 44, pp. 87-100.
  9. Pang, S. Ban, T. Kadobayashi, Y. and Kasabov, N. (2012) LDA Merging and Splitting with Applications to Multi-agent Cooperative Learning and System Alteration, IEEE Transactions on System, Man, and Cybernetics-Part B, vol. 42, no. 2, pp. 552-564.
  10. Pang, S. Ban, T. Kadobayashi, Y. and Kasabov, N. (2011) Tansductive Mode Personalized Support Vector Machine Classification Tree, Information Sciences, vol. 181, no. 11,  pp 2071-2085.
  11. Pang, S., Song, L. and Kasabov, N. (2011) Correlation Aided Support Vector Regression for Forex Time Series Prediction, Neural Computing and Application, vol. 20, no. 8,  pp 1193-1203.
  12. Pang, S. Ban, T. Kadobayashi, Y. and Kasabov, N. (2011) Personalized Mode Tansductive Spanning Support Vector Machine Classification Tree, Information Science, vol. 181, no. 11, pp. 2071 - 2085, 2011.
  13. Ozawa, S. Pang, S. and Kasabov, N. (2008) Incremental Learning of Chunk Data for On-line Pattern Classification Systems, IEEE Transactions on Neural Network, 19(6):1061-1074, June 2008.
  14. Ozawa, S. Pang, S. and Kasabov, N., (2006), On-line Feature Selection for Adaptive Evolving Connectionist Systems, International Journal of Innovative Computing, Information and Control, 2(1):181-192.
  15. Pang, S. Ozawa, S. and Kasabov, N. (2005), Incremental Linear Discriminant Analysis for Classification of Data Streams, IEEE Transactions on System, Man, and Cybernetics-Part B, 35(5), 905-914.
  16. Pang, S. and Kasabov, N. (2009), Encoding and Decoding the Knowledge of Association Rules over SVM Classification Trees, Knowledge and Information Systems, 19(1): 79-105.
  17. Pang, S. Kim, D. Bang, S. (2005), Face Membership Authentication Using SVM Classification Tree Generated by Membership-based LLE Data Partition, IEEE Transactions on Neural Network, 16(2): 436-446.
  18. Pang, S. Kim, H. Kim, D. and Bang, S. (2004), Prediction of the Suitability for Image-matching Based on Self-Similarity of Vision Contents, Image and Vision Computing Journal, 22(5): 355-365.

Professional memberships and associations

  • Senior Member of the Institute of Electrical and Electronics Engineers (IEEE)
  • Member of the Association for Computing Machinery (ACM)
  • Member of the Institute of Electronics, Information and Communication Engineers (IEICE)