
Jianhua loves computing and information technology, teaching the subject and researching and developing IT applications. He started his academic career in tertiary education in 2002, and has had considerable input into developing and teaching Introduction to Database, Object-Oriented Analysis, Object-Oriented Design and Object-Oriented Programming.
His research focuses on Data mining and Knowledge Discovery, Artificial Intelligence and Machine Learning, Software Engineering and Web Services. The research findings have been extensively reported via seminars, workshops, conferences, and journals. He has had long-term work experience in different sectors of the IT industry.
Jianhua has been involved in projects ranging across Management Information System, Computer Aided Design, Computer Simulation, and Web Applications. He pursues teaching innovations, research advances, and industrial opportunities in computer science and software engineering.
Data mining and Knowledge Discovery; Artificial Intelligence and Machine Learning; Software Engineering and Web Services.
Research Projects
- Iterative class diagram construction in consideration of modeling granularity.
- Explore knowledge and skills of OO in 3 dimensions: Philosophies, Principles, and Practices.
- Automate IS construction: Turning Requirement Specification to Object Definition.
- Creation of a Composite Application Software Development Process Framework.
Books
J. Yang, A. Ginige, H.C. Mayr, and R.D. Kutsche (Eds), Information Systems: Modeling, Development, and Integration. Proceedings of the 3rd United Information Systems Conference (UNISCON'09). Sydney, Australia, April 21-24, 2009.
Book Chapters
I. Lee and J. Yang. Unsupervised Data Mining: Common Clustering Algorithms, Comprehensive Chemometrics, Walczak, B., Ferre, R. T. and Brown, S. (editors), Elsevier.
D. Coomans, T. Hancock, I. Lee, C. Smyth and J. Yang. Unsupervised Data Mining: Introduction, Comprehensive Chemometrics, Walczak, B., Ferre, R. T. and Brown, S. (editors), Elsevier.
Journal Articles
V. Estivill-Castro and J. Yang. Fast and Robust General Purpose Clustering Algorithms. The Journal of Data Mining and Knowledge Discovery, Vol. 8, pp 127-150, 2004.
V. Estivill-Castro and J. Yang. Clustering Web Visitors by Fast, Robust and Convergent Algorithms. Special Issue of IJFCS (International Journal of Foundations of Computer Science) on Mining the Web, Vol. 13, No. 4, pp 497-520, C. X. Ling and N. Cercone (eds), 2002.
Conference Papers
J. Yang and I. Lee. Hybrid Clustering for Large Sequential Data. Proceedings of 2007 International Conference on Artificial Intelligence and Pattern Recognition (AIPR-07), Orlando, FL, USA, July 9-12, 2007.
J. Yang and I. Lee. Hybrid O(n sqrt(n)) Clustering for Sequential Web Usage Mining. Proceedings of the 19th Australian Joint Conference on Artificial Intelligence (AI’06), Lecture Notes in Computer Science Vol.4304, Abdul Sattar, Byeong Ho Kang (Eds) Springer-Verlag, Hobart, Australia, December 4-8, 2006.
I. Lee and J. Yang. Hybrid Agglomerative Clustering for Large Databases: An Efficient Interactivity Approach. Proceedings of the 18th Australian Joint Conference on Artificial Intelligence (AI’05), Lecture Notes in Artificial Intelligence Vol. 3809, pp 938-941, Shichao Zhang, Ray Jarvis (Eds) Springer-Verlag, Sydney, Australia, December 5-9, 2005.
I. Lee and J. Yang. Voronoi-based Topological Information for Combining Partitioning and Hierarchical Clustering. Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation (CIMCA'2005), Vienna, Austria, November 28-30, 2005.
J. Yang and I. Lee. Cluster Validity Through Graph-based Boundary Analysis. Proceedings of the International Conference on Information and Knowledge Engineering (IKE’04), pp 204-210, Hamid R. Arabnia (Eds), Las Vegas, Nevada, USA, June 21-24, 2004.
V. Estivill-Castro and J. Yang. Cluster Validity Using Support Vector Machines. Proceedings of the 5th International Conference on Data Warehousing and Knowledge Discovery (DaWak 2003), Lecture Notes in Computer Science Vol. 2737, pp 244-256, Y. Kambayashi, M. Mohania, and W. Wöß (Eds) Springer-Verlag, Prague, Czech Republic, September 3-5, 2003.
J. Yang, V. Estivill-Castro and S. K. Chalup. Support Vector Clustering through Proximity Graph Modeling, Processing of the 9th International Conference on Neural Information (ICONIP'02). Orchid Counry Club, Singapore, November 18-22, 2002.
V. Estivill-Castro and J. Yang. Categorizing Web Visitors Dynamically by Fast and Robust Clustering of Access Logs, Proceedings of the 1st Asia-Pacific Conference on Web Intelligence (WI'2001), Lecture Notes in Artificial Intelligence Vol. 2198, pp 498-507, Ning Zhong and Yiyu Yao (Eds) Springer-Verlag, Maebashi City, Japan, October 23-26, 2001.
V. Estivill-Castro and J. Yang. Non-crisp Clustering by Fast, Convergent and Robust Algorithms. Proceedings of the 5th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'01), Lecture Notes in Artificial Intelligence Vol. 2168, pp 103-114, L. De Raedt and A. Siebes (Eds) Springer-Verlag, Freiburg, Germany, September 3-7, 2001.
V. Estivill-Castro and J. Yang. Fast and Robust General Purpose Clustering Algorithms. Proceedings of the 6th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2000), Lecture Notes in Artificial Intelligence Vol. 1886, pp 208-218, R. Mizoguchi and J. Slaney (Eds) Springer-Verlag, Melbourne, Australia, August 29-September 1, 2000.
Current Membership
Member of AeIMS research group and an associate member of ISL group, SCM, UWS
Membership of IEEE since 2004
Recent Scholarly Activities
Member of the Organising Committee for KDWeb2 2009.
Member of the Organising Committee (Publication chair) for UNISCON’09 conference.
TPC member for ICIAfS'08.
PC member for Australian AI'06.
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