2007 IEEE ICDM Research Contributions Award: Dr. J. Ross Quinlan

Quinlan has worked in machine learning since the mid-1960s. His PhD thesis (the University of Washington, 1968) described a problem-solving system that learned to improve its search heuristics from experience. He is among the most cited and most influential researchers in both machine learning and data mining.

Quinlan is best known for machine learning/data mining systems such as ID3, C4.5, FOIL, and M5 - his book describing C4.5 ranks eighth on CiteSeer's list of most cited documents, and has 8488 citations by Google Scholar as of September 2007. The C4.5 algorithm was ranked number 1 in the top-10 algorithms in data mining by the 2006 IEEE International Conference in Data Mining. The data mining and machine learning communities do not only refer to his seminal work on C4.5, but in fact have been using his C4.5 software as a base classifier for empirical studies in classification papers.

Quinlan has held appointments at the University of Sydney, Rand Corporation, NSWIT (now University of Technology, Sydney), and visiting appointments at CMU, Stanford, MIT, and the University of NSW. Since early 1997 he runs Rulequest Research (www.rulequest.com), a company that develops data mining tools.

2007 IEEE ICDM Nomination and Evaluation Committees

• Xindong Wu (Chair), University of Vermont, USA
• Max Bramer, University of Portsmouth, UK
• Nick Cercone, York University, Canada
• Christos Faloutsos, Carnegie Mellon University, USA
• David Hand, Imperial College, UK
• Ramamohanarao Kotagiri, University of Melbourne, Australia
• Vipin Kumar, University of Minnesota, USA
• Katharina Morik, University of Dortmund, Germany
• Vijay V. Raghavan, University of Louisiana, USA
• Benjamin W. Wah, University of Illinois, Urbana-Champaign, USA
• Philip S. Yu, IBM T.J. Watson Research Center, USA
• Ning Zhong, Maebashi Institute of Technology, Japan

2007 IEEE ICDM Research Contributions Award: Dr. J. Ross Quinlan

Quinlan has worked in machine learning since the mid-1960s. His PhD thesis (the University of Washington, 1968) described a problem-solving system that learned to improve its search heuristics from experience. He is among the most cited and most influential researchers in both machine learning and data mining.

Quinlan is best known for machine learning/data mining systems such as ID3, C4.5, FOIL, and M5 - his book describing C4.5 ranks eighth on CiteSeer's list of most cited documents, and has 8488 citations by Google Scholar as of September 2007. The C4.5 algorithm was ranked number 1 in the top-10 algorithms in data mining by the 2006 IEEE International Conference in Data Mining. The data mining and machine learning communities do not only refer to his seminal work on C4.5, but in fact have been using his C4.5 software as a base classifier for empirical studies in classification papers.

Quinlan has held appointments at the University of Sydney, Rand Corporation, NSWIT (now University of Technology, Sydney), and visiting appointments at CMU, Stanford, MIT, and the University of NSW. Since early 1997 he runs Rulequest Research (www.rulequest.com), a company that develops data mining tools.

2007 IEEE ICDM Nomination and Evaluation Committees

• Xindong Wu (Chair), University of Vermont, USA
• Max Bramer, University of Portsmouth, UK
• Nick Cercone, York University, Canada
• Christos Faloutsos, Carnegie Mellon University, USA
• David Hand, Imperial College, UK
• Ramamohanarao Kotagiri, University of Melbourne, Australia
• Vipin Kumar, University of Minnesota, USA
• Katharina Morik, University of Dortmund, Germany
• Vijay V. Raghavan, University of Louisiana, USA
• Benjamin W. Wah, University of Illinois, Urbana-Champaign, USA
• Philip S. Yu, IBM T.J. Watson Research Center, USA
• Ning Zhong, Maebashi Institute of Technology, Japan