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Geoff Mclachlan

Professor
Department of Physics
The University of Queensland
Australia

Biography

Professor McLachlan received his PhD from the University of Queensland in 1973 and his DSc from there in 1994. His current research projects in statistics are in the related fields of classification, cluster and discriminant analyses, image analysis, machine learning, neural networks, and pattern recognition, and in the field of statistical inference. The focus in the latter field has been on the theory and applications of finite mixture models and on estimation via the EM algorithm. A common theme of his research in these fields has been statistical computation, with particular attention being given to the computational aspects of the statistical methodology. This computational theme extends to Professor McLachlan's more recent interests in the field of data mining. He is also actively involved in research in the field of medical statistics and, more recently, in the statistical analysis of microarray gene expression data. As an ISI Highly Cited Author, Professor McLachlan is part of an elite club of less than half of one percent of all published researchers in the world. He has published six monographs, 20 book chapters and more than 140 articles in peer-reviewed literature. He has a personal chair in statistics in UQ's School of Mathematics and Physics, and a joint appointment with the Institute for Molecular Bioscience. He currently holds an ARC Professorial Fellowship and is a chief investigator in the ARC Centre of Excellence in Bioinformatics. In December 2010, Professor Geoff McLachlan was awarded the Statistical Society of Australia's highest honour - the Pitman Medal - to recognise his "outstanding achievement in, and contribution to, the discipline of statistics". He is only the 18th recipient of the medal since it was first awarded in 1978. Qualifications: GCEd(Qld), BSc Hons(Qld), PhD(Qld), DSc(Qld)

Research Interest

data mining, statistical analysis of microarray, gene expression data, finite mixture models and medical statistics.

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