Dr Shaoning Pang

Interim Director - High Technology Transdisciplinary Research Network, Computer Science; Interim Director - High Technology Transdisciplinary Research Network, High Tech Research
Computer Science
Location: Building 183, Room 3001

Professional memberships

Senior Member of Institute of Electrical and Electronics Engineers, IEEE

Profile

Dr. Paul Pang obtained his Ph.D. in intelligent systems, from Shanghai Jiao Tong University, China (2000). In 2003, he completed his postdoctoral research at Pohang University of Science and Technology (POSTECH), South Korea. From July 2003 to March 2011, he was a senior research fellow and research centre director at Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland University of Technology, New Zealand.

He is currently a senior lecturer in the Department of Computing, Unitec Institute of Technology, New Zealand.

Research Interests

Dr Pang's research interests include Agent Data Mining, Incremental and Multi-task Learning, SVM Aggregating Intelligence, Intelligent Systems and Industry Applications.

He is a principal researcher in the Decentralized Machine Learning Intelligence Laboratory (DMLI).

Teaching
  • Data Mining and its applications to business and industry
  • Research and professional practice at Doctorate Level
  • Thesis supervision at masters and doctorate Level

Publications

Pang, S., Komosny, L. Z., Zhu, L., Zhang, R., Sarrafzadeh, A., Ban, T., & Inoue, D. (2016). Malicious Events Grouping via behaviour Based Darknet Traffic Flow Analysis. Wireless Personal Communications (Vol. 94(336)).

Pang, S., Zhao, J., Hartill, B., & Sarrafzadeh, A. (2016). Modelling land water composition scene for maritime traffic surveillance. International Journal of Applied Pattern Recognition (Vol. 3(4)).
http://hdl.handle.net/10652/3802

Pang, S., Peng, Y., Ban, T., Inoue, D., & Sarrafzadeh, A. (2015). A federated network online network traffics analysis engine for cybersecurity. IJCNN, International Joint Conference on Neural Networks (IJCNN).

Zhao, J., Pang, S., Hartill, B., & Sarrafzadeh, A. (2015). Adaptive Background Modeling for Land and Water Composition Scenes. Murino, V., Puppo, E., & Vernazza, G. ICIAP2015.
http://hdl.handle.net/10652/3359

Chen, G., Douch, C., Zhang, M., & Pang, S. (2015). Reinforcement Learning in Continuous Spaces by Using Learning Fuzzy Classifier Systems. S. Arik et al, 22nd International Conference, ICONIP 2015, Istanbul, Turkey.

Zhang, P., Zhu, L., Xiaosong, L., Pang, S., Sarrafzadeh, A., & Komosny, D. (2015). Behavior Based Darknet Traffic Decomposition for Malicious Events identification. S. Arik et al. 22nd International Conference, ICONIP 2015, Istanbul, Turkey.

Ryan, K., Ko, L., Russello, G., Nelson, R., Pang, S., Cheang, A., Dobbie, G., Sarrafzadeh, A., Chaisiri, S., Rizwan, M. R., & Holmes, G. (2015). STRATUS: Towards Returning Data Control to Cloud Users. Wang, G., Zomaya, A., Perez, G. M & Li, K. ICA3PP International Workshops and Symposiums, China (Vol. 9532).

Dacey, S., Song, L., Zhu, L., & Pang, S. (2014). Analysis and Configuration of Boundary Difference Calculations. Lecture Notes in Computer Science, Neural Information Processing (Vol. 8836).

Tirumala, S. S., Chen, G., & Pang, S. (2014). Quantum Inspired Evolutionary Algorithm by Representing Candidate Solution as Normal Distribution. Lecture Notes in Computer Science, Neural Information Processing (Vol. 8836).

Chen, G., Zhang, M., Pang, S., & Douch, C. (2014). Stochastic Decision Making in Learning Classifier Systems through a Natural Policy Gradient Method. Lecture Notes in Computer Science, Neural Information Processing (Vol. 8836).

Fourie, L., Sarrafzadeh, A., Pang, S., Kingston, T., Hettema, H., and Watters, P. (2014). The global cyber security workforce: an ongoing human capital crisis. N. J. Delener,. L. Fuxman,. F. Victor Lu,. S. Rodrigues, Global Business and Technology Association Conference.

Pang, S., Liu, F., Kadobayashi, Y., Ban, T., & Inoue, D. (2014). A Learner-Independent Knowledge Transfer Approach to Multi-task Learning. Cognitive Computation (Vol. 6(3)).

Song, L., Pang, S., Longley, I., Olivares, G., and Sarrafzadeh, A. (2014). Spatio-temporal PM 2.5 prediction by spatial data aided incremental support vector regression. Neural Networks (IJCNN), 2014 International Joint Conference, XX.

Pang, S., Zhu, L., Chen, G., Sarrafzadeh , A., Ban, T., and Inoue , D. (2013). Dynamic class imbalance learning for incremental LPSVM. Neural Networks (Vol. 44).

Chen, G., Sarrafzadeh, A., and Pang, S. (2013). Service Provision Control in Federated Service Providing Systems. IEEE Transactions on Parallel and Distributed Systems (Vol. 24/3).

Narayanan, A., Chen, Y., Pang, S., and Ban, T. (2013). The Effects of Different Representations on Static Structure Analysis of Computer Malware Signatures. The Scientific World Journal (Vol. 2013).

Ban, T., Zhang, R., Pang, S., Sarrafzadeh, A., and Inoue, A. (2013). Referential kNN Regression for Financial Time Series Forecasting. Lecture Notes in Computer Science (Vol. 8226).

Dacey, S., Song, L., and Pang, S. (2013). An Intelligent Agent Based Land Encroachment Detection Approach. Lecture Notes in Computer Science (Vol. 8226).

Chen, G., Pang, S., Sarrafzadeh, A., Ban, T., and Inoue, D. (2012). SDE-Driven Service Provision Control. Lecture Notes in Computer Science (Vol. 7663).

Narayanan, A., Chen, Y., Pang, S., and Ban, T. (2012). The Effects of Different Representations on Malware Motif Identification. Proc. of Eighth International Conference on Computational Intelligence and Security (CIS).

Chen, Y., Narayanan, A., Pang, S., and Ban, T. (2012). Multiple sequence alignment and artificial neural networks for malicious software detection. Proc. of 2012 Eighth International Conference on Natural Computation (ICNC), Digital Object Identifier: 10.1109/ICNC.2012.6234576.

Pang, S., Liu, F., Kadobayashi, Y., Ban, T., and Inoue, D. (2012). Training Minimum Enclosing Balls for Cross Tasks Knowledge Transfer. International Conference on Neural Information Processing (ICONIP).

Ban, T., Zhu, L., Shimamura, J., Pang, S., and Inoue, D. (2012). Behavior Analysis of Long-term Cyber Attacks in the Darknet. International Conference on Neural Information Processing (ICONIP (5)).

Chen , Y., Narayanan, A., Pang, S., and Ban, T. (2012). Malicioius Software Detection Using Multiple Sequence Alignment and Data Mining. The 26th IEEE International Conference on Advanced Information Networking and Applications (AINA).

Zhu, L., Pang, S., Chen, G., and Sarrafzadeh, A. (2012). Class Imbalance Robust Incremental LPSVM for Data Streams Learning. International Joint Conference on Neural Networks (IJCNN2012), Brisbane, Australia.

Lai, A., Song, L., Peng, Y., Zhang, P., Wang, Q., and Pang, S. (2012). Exploring Crude Oil Impacts to Oil Stocks through Graphical Computational Correlation Analysis. Lecture Notes in Computer Science (Vol. 7667).

Rafiq, Mohammed, and S., Pang (2011). Agent Personalized Call Center Traffic Prediction and Call Distribution. Neural Information Processing, 978-3-642-24957-0 (Vol. 7063).

Osawa, Z., Pang, S., and Kasabov, N. (2011). Incremental Learning in Intelligent Systems: Theory and Applications, a monograph book, contracted with John Wiley & Sons, USA. John Wiley & Sons, USA.

S., Pang, Tao, Ban, Youki, Kadobayashi, and N., Kasabov (2011). Personalized mode transductive spanning SVM classification tree. Information Sciences (Vol. 181/11).

S., Pang, T., Ban, Y., Kadobayashi, and N. K., Kasabov (2011). LDA Merging and Splitting With Applications to Multiagent Cooperative Learning and System Alteration. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on (Vol. 99).

Pang, S., Ban, T., Kadobayashi, Y., and Kasabov, N. (2011). Personalized mode transductive spanning SVM classification tree. Information Science (Vol. 181/11).

Pang, S., Ban, T., Kadobayashi, Y., and Kasabov, N. (2011). LDA Merging and Splitting With Applications to Multiagent Cooperative Learning and System Alteration. IEEE Transactions on System, Man, and Cybernetics-Part B (Vol. PP/99).

Pang, S., Song, L., and Kasabov, N. (2010). Correlation-aided support vector regression for forex time series prediction. Neural Computing & Applications, DOI: 10.1007/s00521-010-0482-5.

Ozawa, S., Pang, S., and Kasabov, N. (2010). Online Feature Extraction for Evolving Intelligent Systems. P. Angelov, D. P. Filev and N. Kasabov (Eds). Evolving Intelligent Systems, John Wiley & Sons, Inc., Hoboken, JK, USA. doi: 10.1002/9780470569962.ch7.

Pang, S., Chen, G., Lei, S., and Kasabov, N. (2010). High Speed Algorithms for Outlier Detection and Classification over Huge-size Network Data Streams. Technical Project Report to National Institute of Information and Communication Technologies (NICT), Japan. Knowledge Engineering Discovery Research Institute, Auckland University of Technology.

Ozawa, S., Pang, S., and Kasabov Kasabov , N. (2010). Online Feature Extraction for Evolving Intelligent Systems. Evolving Intelligent Systems: Methodology and Applications, ISBN 978-0-470-28719-4.

Shimo, N., Pang, S., Horio, K., Kasabov, N., Tamukoh, H., Koga, T., Sonoh, S., Isogai, H., Yamakawa, T., Hanazawa, A., Miki, T., and Horio, K. (2010). Effective and Adaptive Learning Based on Diversive/Specific Curiosity. Brain-Inspired Information Technology, Isbn: 978-3-642-04024-5 (Vol. Volume 266).

Lu, B., He, Z., Yang, J., and Pang, S. (2010). A new FCM algorithm based on monkey-king genetic algorithm for remote sensing image segmengtation. Laser Journal, CNKI:SUN:JGZZ.0.2010-06-009.

Pang, S., Ozawa, S., and Kasabov, N. (2009). Curiosity Driven Incremental LDA Agent Active Learning. Proc. Of 2009 International Joint Conference on Neural Networks, Atlanta GA.

Pang, S., Ban, T., Kadobayashi , Y., and Kasabov, N. (2009). Spanning SVM Tree for Personalized Transductive Learning. Proc. of ICANN 2009, Part I (Vol. Volume 5768).

Michlovsky, Z., Pang, S., Kasabov, N., Ban, T., and Kadobayashi, Y. (2009). String kernel based SVM for internet security implementation. NEURAL INFORMATION PROCESSING Lecture Notes in Computer Science (Vol. 5864/2009).

Chen, Y., Pang, S., Kasabov, N., Ban, T., and Kadobayashi, Y. (2009). Hierarchical Core Vector Machines for Network Intrusion Detection. Proc. of ICONIP 2009, Part II (Vol. Volume 5864).

Pang, S., Dhoble , K., Chen, Y., Kasabov, N., Ban, T., and Kadobayashi, Y. (2009). Active Mode Incremental Nonparametric Discriminant Analysis Learning. Proc. of the Eighth International Conference on Information and Management Sciences.

Gordon, S., Pang, S., Nishioka, R., Kasabov, N., and Yamakawa, T. (2009). Vision based mobile robot for indoor environmental security. ADVANCES IN NEURO-INFORMATION PROCESSING Lecture Notes in Computer Science, DOI: 10.1007/978-3-642-02490-0_117 (Vol. 5506/2009).

Pang, S., and Ban, T. (2009). Guest editorial: Thematic issue on 'Adaptive Soft Computing Techniques and Applications'. Memetic Computing (Vol. 1/4).

Pang, S., and Kasabov, N. (2009). Encoding and decoding the knowledge of association rules over SVM classification trees. Knowledge and Information Systems (Vol. 19/1).

Pang, S., and Ban, T. (2009). Adaptive Soft Computing Techniques and Applications. Special issue of Memetic Computing, ISSN: 1865-9292 (Vol. Volume 1).

Pang, S., Havukkala, I., Hu, Y., and Kasabov, N. (2008). Bootstrapping Consistency Method for Optimal Gene Selection from Microarray Gene Expression Data for Classification Problems. In Y.-Q. Zhang and J. C. Rajapakse (Eds.). Machine Learning in Bioinformatics, Hoboken, NJ: John Wiley & Sons.

Pang, S., and Kasabov, N. (2008). Wireless Network Coverage and Capacity Dynamic Optimization for NewZealand Telecom. Technical Project Report to Telecom New Zealand Ltd., Lucentand Bell Lab, and Foundation for Research Science & Technology (FRST) NewZealand, Knowledge Engineering Discovery Research Institute, Auckland Universityof Technology.

Pang, S., and Kasabov, N. (2008). SVMT-rule: Association Rule Mining over SVM Classification Trees. Rule Extraction from Support Vector Machines, ISBN: 978-3-540-75389-6 (Vol. Volume 80).

Shimo, N., Pang, S., Kasabov, N., and Yamakawa, T. (2008). Curiosity-Driven Multi-Agent Competitive and Cooperative LDA Learning. International Journal of Innovative Computing, Information and Control (Vol. 4/7).

Ozawa, S., Pang, Shaoning, and Kasabov, N. (2008). Incremental Learning of Chunk Data for Online Pattern Classification Systems. Neural Networks, IEEE Transactions on (Vol. 19/6).

Ozawa, S., Pang, S., and Kasabov, N. (2008). Incremental Learning of Chunk Data for On-line Pattern Classification Systems. IEEE Transactions on Neural Networks (Vol. 19/6).

Ozawa, S., Matsumoto, K., Pang, S., and Kasabov, N. (2008). An Incremental Principal Component Analysis based on Dynamic Accumulation Ratio. SICE Annual Conference.

Pang, S., and Kasabov, N. (2008). r-SVMT: Discovering the Knowledge of Association Rule over SVM Classification Trees. Proc. of IEEE International Joint Conference on Neural Networks.

Pang, S., Ban, T., Kadobayashi, Y., and Kasabov, N. (2008). gSVMT: Aggregating SVMs over a Dynamic Grid Learned from Data. Proc. of 11th International Conference on Computer and Information Technology.

Pang, S., Havukkala, I., Hu, Y., and Kasabov, N. (2007). Classification Consistency Analysis for Bootstrapping Gene Selection. Neural Computing and Applications (Vol. 16/6).

Pang, S., and Chen, G. (2007). Speech Feature Extraction with reference to Smoking Quitting Voice Change Detection. Technical Project Report to Health Research Council (HRC) New Zealand, Knowledge Engineering Discovery Research Institute, Auckland University of Technology.

Pang, S., Havukkala , I., and Kasabov, N. (2006). Two-Class SVM Trees (2-SVMT) for Biomarker Data Analysis. In J. Wang et al. (Eds.). ISNN 2006: Proceedings of International Symposium on Neural Networks, Berlin: Springer Verlag.

Pang, S., and Havukkala, I. (2006). Proceeding of 1st Korean New Zealand Joint Workshop on Advance of Computational Intelligence Methods and Applications. Auckland University of Technology, New Zealand.

Ozawa, S., Pang, S., and Kasabov, N. (2006). Incremental Learning of Feature Space and Classifier for Online Pattern Recognition. Computer Science, Artificial Intelligence and Software Development (Vol. 10/1).

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 (Vol. 10/10).

Havukkala, I., Benuskova, L., Pang, S., Jain, V., Kroon , R., and Kasabov, N. (2006). Image and Fractal Information Processing for Large-Scale Chemoinformatics, Genomics Analyses and Pattern Discovery. Proceedings of PRIB.

Pang, S., and Kasabov, N. (2006). Investigating LLE Eigenface on Pose and Face Identification. ADVANCES IN NEURAL NETWORKS - ISNN 2006 Lecture Notes in Computer Science, DOI: 10.1007/11760023_21 (Vol. 3972/2006).

Hu, Y., Pang, S., and Havukkala, I. (2006). A Novel Microarray Gene Selection Method Based on Consistency. Sixth International Conference on Hybrid Intelligent Systems, 2006. HIS '06.

Ozawa, S., Toh, S.L., Abe, S., Pang, Shaoning, and Kasabov, N. (2005). Incremental learning for online face recognition. Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on (Vol. 5/5).

Pang, Shaoning, Ozawa, S., and Kasabov, N. (2005). Incremental linear discriminant analysis for classification of data streams. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on (Vol. 35/5).

Kasabov, N., Zhang, D., and Pang, S. (2005). Incremental learning in autonomous systems: evolving connectionist systems for on-line image and speech recognition. Advanced Robotics and its Social Impacts, 2005. IEEE Workshop on.

Kasabov, N., and Pang, Shaoning (2003). Transductive support vector machines and applications in bioinformatics for promoter recognition. Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on (Vol. 1).