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Dr Graham J Williams
Dr Graham Williams is Director and Senior Data Miner with the Australian Taxation Office, and previously Principal Computer Scientist for Data Mining with the Australian Government's premiere research organisation (CSIRO), and before then, a Lecturer in Computer Science, Australian National University. He is also Adjunct Professor, Data Mining, Fraud Prevention, Security, University of Canberra, and with the Australian National University, where he teaches data mining.
Graham has been involved in many data mining projects for clients including the Health Insurance Commission, the Australian Taxation Office, the Commonwealth Bank, NRMA Insurance Limited, the Commonwealth Department of Health and Ageing, Queensland Health, and the Australian Customs Service. He has developed software and hardware environments for data mining, and implemented web services for the delivery of data mining. Developments include Multiple Decision Tree Induction, HotSpots for identifying target areas in very large data collections, WebDM for the delivery of data mining services over the web using XML, and Rattle, a simple to use Graphical User Interface designed to make data mining accessible for data analysts.
Graham is involved in numerous international artificial intelligence and data mining research activities and conferences, as chair of the Australasian Data Mining Conference and member of the steering committees of the Pacific Asia Knowledge Discovery and Data Mining conference and the Australian Artificial Intelligence conference. He has worked with collaborators in Europe, Asia, and the US. His research interests cover many aspects of artificial intelligence, data mining and very large databases, including fraud and compliance, linked health data, spatio-temporal data mining, evolutionary rule induction, agent systems, web services, machine learning, and GNU/Linux. He has editted a number of books and has authored many academic and industry papers.
Graham's PhD (Australian National University, 1991) introduced the new idea of combining multiple predictive models for the better understanding of data and predictive capability. The thesis explored algorithms for building multiple decision trees from a source data set (land use data) and combining those decision trees. Such approaches are now widely used with such approaches as ensembles, boosting, and bagging, and recognised as providing significant gains for modelling.
Graham has worked for a number of organisations including: CSIRO Land and Water in Canberra, Australia, developing award wining spatial expert systems (using Prolog); BBJ Computers in Melbourne, Australia, as Research and Development manager and then Marketing Manager, overseeing the implementation of a data mining tool for integration with a 4GL database environment; Vish Corporation, involved in developing one of the first and one of the longest running Expert Systems for Esanda Finance, Melbourne, Australia; and the Australian National University, Canberra, lecturing in Database Systems, Machine Learning, Data Mining, and Software Engineering.
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