Professor Geoffrey Holmes- Dean of Computing & Mathematical Sciences, University of Waikato

Dean of Computing & Mathematical Sciences

University of Waikato

New Zealand

• BSc(Hons) of Mathematics, University of Southampton, England
• PhD of Mathematics, University of Southampton, England (involving the development of software packages to assist Mathematicians in solving Einstein’s field equations in General Relativity)

• Research Assistant at the Electrical Engineering Department of Cambridge University, England, 1984 – 1987
• Lecturer in Computer Science, University of Waikato, New Zealand, 1987-1994
• Senior Lecturer in Computer Science, University of Waikato, New Zealand, 1994 – 2001
• Associate Professor in Computer Science, University of Waikato, New Zealand, 2001 – 2008
• Dean of Computing & Mathematical Sciences, University of Waikato, New Zealand, 2008-present

Prof. Geoff Holmes has, in the past, been head of the machine learning group at the University of Waikato and has been involved in several open source projects over the last 20 years. Waikato’s machine learning project has had a far-reaching influence on developments in the field worldwide, principally through the open-source Weka software, one of the most widely used machine learning tools in the world today (Weka software has been downloaded 6 million times since it was first hosted at the Sourceforge website for open-source software in April 2000 – currently at a rate of about 3,000 downloads a day). Academic publications (close to 400 articles) by the machine learning group can be found at http://www.cs.waikato.ac.nz/ml/publications.html,

Professor Holmes has led the applied machine learning subgroup at the University for the past 10 years. This group has particular expertise in the deployment of machine learning solutions in practice and has developed a bespoke platform for this purpose (see https://adams.cms.waikato.ac.nz/).

Professor Holmes has also been a co-developer of a platform for processing very large (possibly infinite) datasets MOA (Massive Online Analysis), which is to data stream mining what Weka is to batch learning (see http://moa.cms.waikato.ac.nz/).

Aside from software, Professor Holmes has made contributions to the major conferences in machine learning and data mining (over 120 academic publications). He has recently co-written a book describing the techniques contained in the MOA software. He was part of the team that in 2005 won the SIGKDD Data Mining and Knowledge Discovery Service Award for Weka and regularly serves on senior program committees for KDD, ECMLPKDD and Discovery Science and referees articles in all the major journals in the field.