Overview
Background
Professor Geoffrey McLachlan's research interests are in: data mining, statistical analysis of microarray, gene expression data, finite mixture models and medical statistics.
Professor McLachlan received his PhD from the University of Queensland in 1974 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.
Availability
- Professor Geoffrey McLachlan is:
- Available for supervision
- Media expert
Fields of research
Qualifications
- Bachelor (Honours) of Science (Advanced), The University of Queensland
- Doctor of Philosophy, The University of Queensland
- Doctoral (Research) of Science (Advanced), The University of Queensland
- Australian Mathematical Society, Australian Mathematical Society
Works
Search Professor Geoffrey McLachlan’s works on UQ eSpace
1972
Journal Article
Asymptotic Expansion for Variance of Errors of Misclassification of Linear Discriminant Function
McLachla.GJ (1972). Asymptotic Expansion for Variance of Errors of Misclassification of Linear Discriminant Function. Australian Journal of Statistics, 14 (1), 68-72. doi: 10.1111/j.1467-842X.1972.tb00339.x
Funding
Current funding
Past funding
Supervision
Availability
- Professor Geoffrey McLachlan is:
- Available for supervision
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Supervision history
Current supervision
-
Doctor Philosophy
Role of Finite Mixture Models in Semi-Supervised Learning
Principal Advisor
Other advisors: Dr Sharon Lee
-
Doctor Philosophy
Robust Multi-Agent Reinforcement Learning under Non-Stationarity, Incomplete Information, and Adversarial Dynamics
Associate Advisor
Other advisors: Professor Fred Roosta
-
Doctor Philosophy
An Adaptive Cross-Cultural Platform for Early Readiness Profiling of University Students
Associate Advisor
Other advisors: Professor Robyn Gillies
Completed supervision
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2024
Doctor Philosophy
Detecting the unexpected in astronomical data using complexity based approaches
Principal Advisor
-
2023
Doctor Philosophy
Improving Predictability of Minerals Processing Models by Developing a Methodology based-on Machine Learning Techniques
Principal Advisor
-
-
2015
Doctor Philosophy
Finite Mixture Models for Regression Problems
Principal Advisor
Other advisors: Dr Ian Wood
-
2014
Doctor Philosophy
Finite Mixture Modelling using Multivariate Skew Distributions
Principal Advisor
Other advisors: Dr Ian Wood
-
2012
Doctor Philosophy
Detection of Differentially Expressed Genes via Mixture Models and Cluster Analysis
Principal Advisor
Other advisors: Dr Ian Wood
-
2009
Doctor Philosophy
Statistical analysis of high-dimensional gene expression data
Principal Advisor
-
2005
Doctor Philosophy
CLUSTERING WITH MIXED VARIABLES
Principal Advisor
-
2004
Master Science
Modelling the statistical behaviour of temperature using a modified Brennan and Schwartz 1982 interest rate model
Principal Advisor
Other advisors: Associate Professor Michael Bulmer
-
2025
Doctor Philosophy
Learning a mineralised fault network at the Cracow Gold Mine from geologically-informed 3D synthetic seismic data
Associate Advisor
Other advisors: Associate Professor Dion Weatherley, Professor Rick Valenta
-
2025
Doctor Philosophy
Using statistical approaches to gain insight into patterns of variation in melanoma transcriptomic data
Associate Advisor
Other advisors: Dr Vivi Arief, Dr Quan Nguyen, Emeritus Professor Kaye Basford
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2024
Doctor Philosophy
The Wealth of Features: towards a coherent cooperative game theory for feature importance
Associate Advisor
Other advisors: Associate Professor Sally Shrapnel, Dr Ian Wood
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2019
Doctor Philosophy
Maximum pseudolikelihood estimation with Markov random fields in the segmentation of brain magnetic resonance images
Associate Advisor
Other advisors: Dr Ian Wood
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2016
Doctor Philosophy
Estimation of missing values in multivariate multi-environment trial data for three-way pattern analysis
Associate Advisor
Other advisors: Emeritus Professor Kaye Basford
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-
Doctor Philosophy
TOPOLOGICAL MODELS OF TRANSMEMBRANE PROTEINS FOR SUBCELLULAR LOCALIZATION PREDICTION
Associate Advisor
Other advisors: Associate Professor Marcus Gallagher, Professor Mikael Boden
Media
Enquiries
Contact Professor Geoffrey McLachlan directly for media enquiries about:
- Bioinformatics
- Computation - statistics
- Computer learning
- Data mining
- Gene expression data
- Image analysis - statistics
- Machine learning
- Neural networks
- Pattern recognition - statistics
- Statistical methodology
- Statistics
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