Congratulations to the 21 new fellows elected to the Australian Academy of Science for their outstanding contributions to science and scientific research on 25 May 2015.
Three mathematicians and statisticians are among those elected Professor Peter Bartlett, Professor Geoffrey McLachlan and Professor Malcolm Sambridge.
Professor Peter Bartlett FAA
Faculty of Science and Engineering, Queensland University of Technology
Peter Bartlett is a pioneer at the interface of computer science and statistics, with a focus on the science behind large, complex statistical decision problems. He has created the theoretical foundations for many key advances in statistical machine learning.
Peter Bartlett is a pioneer in statistical learning theory, which is at the interface of computer science and statistics, and is focused on the science behind large, complex statistical decision problems. He has created the theoretical foundations for many key advances in statistical machine learning. Peter’s contributions include analysing large margin classifiers (a successful family of computationally efficient methods for classifying patterns), developing and analysing statistical learning methods based on convex optimisation, and developing new techniques for analysing the performance of prediction methods.
Biography
Professor Peter Bartlett’s research is in statistical learning theory, an area that lies at the interface between statistics and computer science and is concerned with the development of the theoretical foundations for methods that use large and complex data to make effective decisions. He is professor in Mathematics at the Queensland University of Technology and professor in Computer Science and Statistics at UC Berkeley, he has been professor in the Research School of Information Sciences and Engineering at the Australian National University, Visiting Miller Professor at UC Berkeley, honorary professor at the University of Queensland, and visiting professor at the University of Paris. He was awarded the Malcolm McIntosh Prize for Physical Scientist of the Year in 2001, was an IMS Medallion Lecturer in 2008, and is an Australian Laureate Fellow and a Fellow of the Institute of Mathematical Statistics.
Professor Geoffrey McLachlan FAA
Department of Mathematics, The University of Queensland
Geoffrey McLachlan’s pioneering work in mixture models has been especially influential, from inference and clustering and error-rate estimation for classifiers, to new techniques in analysing gene expression data.
Mixture models play a central role in statistical science, and Geoffrey McLachlan’s pioneering work in this field has been especially influential. His research on mixture models for inference and clustering is of particular note, as is his work on applications of the EM algorithm, especially to complex multivariate problems. Geoffrey has also made major contributions to error-rate estimation for classifiers and to new techniques in analysing gene expression data, including techniques for clustering tissue samples containing thousands of genes, and for controlling false discovery rate.
Biography
Professor Geoff McLachlan is a University of Queensland Vice-Chancellor’s Senior Research Fellow and has been an Australian Research Council Professorial Fellow. He has had a career-long interest in classification and pattern recognition and was elected President of the International Federation of Classification Societies for 2010-2011. In other main fields of interest, his focus on statistical inference has been on the theory and applications of finite mixture models and on estimation via the EM algorithm. He has also been actively involved in bioinformatics with the focus on the statistical analysis of microarray gene expression data and on multiple testing. He has published extensively in these fields, including six monographs. He is an Institute for Scientific Information (ISI) Highly Cited Author in Mathematics. On the basis of his research, he was awarded a DSc in 1994, the Pitman medal of the Statistical Society of Australia in 2010, and the IEEE ICDM medal in 2011.
Professor Malcolm Sambridge FAA
Research School of Earth Sciences, The Australian National University
Malcolm Sambridge’s new mathematical approaches to analysing complex geophysical data have fundamentally altered the way in which we understand the Earth and its internal processes.
Malcolm Sambridge has made lasting fundamental contributions to the understanding of the Earth and its internal processes through new mathematical approaches to analysing complex geophysical datasets. His robust approaches to modelling diverse observational data – including statistically meaningful estimates of uncertainty – has had wide-ranging impact in geoscientific research. Malcolm’s work has changed the way in which we analyse seismic waves for the structure of the Earth’s interior, model landscape evolution, understand populations of mineral ages from isotopic microanalysis, and interpret infrared absorption spectra associated with hydrous crystal defects in silicate minerals.
Biography
Professor Malcolm Sambridge’s research contributions have been in geophysical inverse theory and methods of inference from indirect observations, together with their application across the Earth Sciences. Specific research directions include the development and application of data inference techniques; theoretical seismology; imaging of the internal structure of Earth using seismic waves; robust inference and uncertainty estimation from Earth science data; Mathematical methods and numerical algorithms. Professor Sambridge is Head of Seismology and Mathematical Geophysics at the Australian National University’s Research School of Earth Sciences.
Other elected fellows:
Professor Martin Asplund FAA
Professor Christine Beveridge FAA
Professor Jenefer Blackwell FAA
Professor Christine Charles FAA
Professor Susan Clark FAA
Professor Maria Forsyth FAA
Professor Julian Gale FAA
Professor Edward Holmes FAA
Professor Wendy Hoy AO FAA
Professor William Laurance FAA
Professor Helene Marsh FAA FTSE
Professor Michael McLaughlin AM FAA FTSE
Professor Linda Richards FAA
Professor Ian Small FAA
Professor San Thang FAA
Professor Carola Vinuesa FAA
Dr Zygmunt Switkowski AO FAA FTSE