Togaware: Graham J. Williams

Graham J. Williams

Latest News

25 May 2011 It was a suprise and great honour to receive the PAKDD Distinguished Contribution award at PAKDD 2011, Shenzhen, China, May 2011.

20 October 2011 My new book Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R) is now available from Springer as part of the Use R! series.

15 March 2011 The free and open source Rattle data mining software and the companion Data Mining Desktop Survival Guide continue to grow (content, userbase, readers) - learn to data mine using R.

Key Affiliations

Director and Senior Data Miner
Australian Taxation Office
Graham.Williams@ato.gov.au

Visiting Professor 2011-2012
Shenzhen Institutes of Advanced Computing
Chinese Academy of Sciences

Adjunct Professor
Data Mining, Fraud Prevention and Security
Research Leadership
School of Information Sciences and Engineering
University of Canberra
Graham.Williams@canberra.edu.au

Adjunct Professor
Computer Science
Faculty of Engineering and Information Technology
Australian National University
Graham.Williams@anu.edu.au

Togaware Pty Ltd, PO Box 655, Jamison Centre, Canberra, ACT 2614, Australia

Email: Graham.Williams@togaware.com
Phone: +61 2 6104 9053
Mobile: +61 402 409 418

Key Skills

Leadership and Management of Data Mining Teams
Data Mining Research and Consultancies
Programming Data Analyses using R
Data Mining Software Development using R (Rattle)
Machine learning algorithms
Training Courses and Books in Data Mining
Debian GNU/Linux
Knowledge-based systems implementation
Software engineering, Python, C++, Java
XML, SOAP, Web Delivery
Databases programming, SQL, JDBC, ODBC

Professional Interests

Ensemble models, social network analysis, high performance computing
Open source software and freedom in computing
Data Mining to identify Fraud, Non-Compliance, Security
Data Mining in Health
Machine Learning
Artificial Intelligence and Knowledge-Based Expert Systems

Professional Memberships

American Association for Artificial Intelligence
Association for Computing Machinery
IEEE Computer Society
Australian Computer Society
Fellow, Institute of Analytics Professionals of Australia

Professional Involvement

Head, ACT Chapter, Institute of Analytics Professionals of Australia
Chair, Steering Committee, Australasian Data Mining Conference
Chair, Steering Committee, Pacific Asia Knowledge Discovery and Data Mining Conference
Steering Committee, Australian Artificial Intelligence Conference

Achievements

Awards

2011 PAKDD Distinguished Contribution Award.
2007 Australia Day Award for Contriutions to the Community through open souce data mining software and outreach.
2006 Australian Taxation Office Innovation Award
1986 Best Paper Award, Avignon Expert Systems Conference

Teaching and Training

The book Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery published by Springer in 2011.

Ensemble Learning: Multiple Decision Tree Induction PhD research 1986 to 1990.
- Demonstrated use of ID3 to build a class of classifiers rather than just a single classifier.
- Identified that decision tree induction algorithms like ID3 can generate multiple decision trees that can be combined to produce classifiers that perform better than the individual classifiers.
- Integrated into commercial Database Management System in 1988 by BBJ Computers, into the TODAY 4GL.
Commercial Knowledge-Based Expert Systems Development
- Victorian Government Departments 1987: VBARS combined business advice from multiple agencies to provide a single point of entry for the delivery of this advice to the public.
- Esanda Finance 1989: Credit Assessment System. One of the first commercial Australian expert systems and still in daily operation in 2000, providing credit assessments for distributed on-line application for credit from motor vehicle dealers.
Spatial Reasoning
- One of the earliest spatial expert systems developed for fire management at Kakadu National Park 1985
  Awarded best paper at International conference, Avignon, France.
- Spatial reasoning systems based on expectations integrated within GIS 1991
Methodologies for Exploring for Interesting Discoveries
- Hot Spots Data Mining Methodology 1994
  Combine rule induction with clustering to identify interesting groups within very large datasets.
- Rule Evolver for Interesting Rule Discovery 1997
  Employ evolutionary techniques to assist in the task of identify interesting patterns in extremely large databases.
- Statistical Outlier Detection with NEC Japan
  Identify under-represented patterns within extremely large databases.
- Fraud Detection for the Health Insurance Commission 1998
  Successful identification of cases of fraudulent behaviour
Other Data Mining Activities
- Introduced the idea of building ensembles for machine learning in 1987.
- With Peter Milne and Joshua Huang, set up the first data mining research and applications group in data mining in Australia in 1995, within CSIRO, Canberra.
- Health Insurance Commission 1995 to 2000
- Australian Taxation Office 1995 to 2000
  Largest ever extraction of data from the Taxation Office
- Medicare Pathology Analysis 2000
- Medicare and Pharmaceutical Benefits Schemes 2000
- Linking and Cleaning distributed administrative health databases 2002
- Symposium Chair, Symposium on Applications of Artificial Intelligence in Industry, Melbourne, 2000
- Program Committee Co-Chair, Pacific Asia Conference on Knowledge Discovery and Data Mining, Hong Kong, 2001
- Member of steering committee, Pacific Asia Conference on Knowledge Discovery and Data Mining
- With Simeon Simoff, instigated the Australasian Data Mining Conference in 2002.

Professional Qualifications

1982: BSc Maths First Class Hons (University of Adelaide)
1991: PhD (Australian National University)