Professor Geoffrey McLachlan
Professor

Geoffrey McLachlan

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Phone: 
+61 7 336 52150

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

Statistics

Qualifications

  • Bachelor (Honours) of Science (Advanced), The University of Queensland
  • Doctor of Philosophy, The University of Queensland
  • Doctoral Diploma of Science (Advanced), The University of Queensland
  • Australian Mathematical Society, Australian Mathematical Society

Search Professor Geoffrey McLachlan’s works on UQ eSpace

370 works between 1972 and 2024
All (370) Journal Article (249) Book Chapter (34) Conference Publication (75) Book (9) Other Outputs (2) Edited Outputs (1)

341 - 360 of 370 works

1980

Journal Article

On the mean square error associated with adaptive generalized ridge regression

McLachlan G.J. (1980). On the mean square error associated with adaptive generalized ridge regression. Biometrical Journal, 22 (2), 125-129. doi: 10.1002/bimj.4710220205

On the mean square error associated with adaptive generalized ridge regression

1979

Journal Article

A case study of two clustering methods based on maximum likelihood

Ganesalingam, S. and McLachlan, G. J. (1979). A case study of two clustering methods based on maximum likelihood. Statistica Neerlandica, 33 (2), 81-90. doi: 10.1111/j.1467-9574.1979.tb00665.x

A case study of two clustering methods based on maximum likelihood

1979

Conference Publication

Analysis of Some Censored Survival Data From a Large-Scale Study of Melanoma

Holt, JN and McLachlan, GJ (1979). Analysis of Some Censored Survival Data From a Large-Scale Study of Melanoma. WASHINGTON: INTERNATIONAL BIOMETRIC SOC.

Analysis of Some Censored Survival Data From a Large-Scale Study of Melanoma

1979

Journal Article

Small sample results for a linear discriminant function estimated from a mixture of normal populations

Ganesalingam, S. and McLachlan, G. J. (1979). Small sample results for a linear discriminant function estimated from a mixture of normal populations. Journal of Statistical Computation and Simulation, 9 (2), 151-158. doi: 10.1080/00949657908810306

Small sample results for a linear discriminant function estimated from a mixture of normal populations

1979

Journal Article

Comparison of the Estimative and Predictive Methods of Estimating Posterior Probabilities

McLachlan, G. J. (1979). Comparison of the Estimative and Predictive Methods of Estimating Posterior Probabilities. Communications in Statistics Part A-Theory and Methods, 8 (9), 919-929. doi: 10.1080/03610927908827807

Comparison of the Estimative and Predictive Methods of Estimating Posterior Probabilities

1979

Journal Article

Expected error rates for logistic regression versus normal discriminant analysis

McLachlan, G. J. and Byth, K. (1979). Expected error rates for logistic regression versus normal discriminant analysis. Biometrical Journal, 21 (1), 47-56. doi: 10.1002/bimj.4710210107

Expected error rates for logistic regression versus normal discriminant analysis

1978

Journal Article

Efficiency of a Linear Discriminant Function Based On Unclassified Initial Samples

Ganesalingam, S and McLachlan, GJ (1978). Efficiency of a Linear Discriminant Function Based On Unclassified Initial Samples. Biometrika, 65 (3), 658-662. doi: 10.1093/biomet/65.3.658

Efficiency of a Linear Discriminant Function Based On Unclassified Initial Samples

1978

Journal Article

Small sample results for partial classification with the Studentized statistic W

McLachlan, G. J. (1978). Small sample results for partial classification with the Studentized statistic W. Biometrical Journal, 20 (7-8), 639-644. doi: 10.1002/bimj.197800003

Small sample results for partial classification with the Studentized statistic W

1978

Journal Article

Biases Associated with Maximum Likelihood Methods of Estimation of Multivariate Logistic Risk Function

Byth, K and McLachlan, GJ (1978). Biases Associated with Maximum Likelihood Methods of Estimation of Multivariate Logistic Risk Function. Communications in Statistics Part A-Theory and Methods, 7 (9), 877-890. doi: 10.1080/03610927808827679

Biases Associated with Maximum Likelihood Methods of Estimation of Multivariate Logistic Risk Function

1978

Conference Publication

Bias Associated with Maximum Likelihood Estimation of Multivariate Logistic Risk Function

McLachlan, GJ (1978). Bias Associated with Maximum Likelihood Estimation of Multivariate Logistic Risk Function. WASHINGTON: INTERNATIONAL BIOMETRIC SOC.

Bias Associated with Maximum Likelihood Estimation of Multivariate Logistic Risk Function

1977

Journal Article

Estimating Linear Discriminant Function From Initial Samples Containing a Small Number of Unclassified Observations

McLachlan, GJ (1977). Estimating Linear Discriminant Function From Initial Samples Containing a Small Number of Unclassified Observations. Journal of the American Statistical Association, 72 (358), 403-406. doi: 10.2307/2286807

Estimating Linear Discriminant Function From Initial Samples Containing a Small Number of Unclassified Observations

1977

Journal Article

Note On Choice of a Weighting Function to Give An Efficient Method for Estimating Probability of Misclassification

McLachlan, GJ (1977). Note On Choice of a Weighting Function to Give An Efficient Method for Estimating Probability of Misclassification. Pattern Recognition, 9 (3), 147-149. doi: 10.1016/0031-3203(77)90012-7

Note On Choice of a Weighting Function to Give An Efficient Method for Estimating Probability of Misclassification

1977

Journal Article

Constrained Sample Discrimination with Studentized Classification Statistic-W

McLachlan, GJ (1977). Constrained Sample Discrimination with Studentized Classification Statistic-W. Communications in Statistics Part A-Theory and Methods, 6 (6), 575-583. doi: 10.1080/03610927708827515

Constrained Sample Discrimination with Studentized Classification Statistic-W

1977

Journal Article

The bias of sample based posterior probabilities

McLachlan, G. J. (1977). The bias of sample based posterior probabilities. Biometrical Journal, 19 (6), 421-426. doi: 10.1002/bimj.4710190604

The bias of sample based posterior probabilities

1976

Journal Article

Criterion for Selecting Variables for Linear Discriminant Function

McLachlan, GJ (1976). Criterion for Selecting Variables for Linear Discriminant Function. Biometrics, 32 (3), 529-534. doi: 10.2307/2529742

Criterion for Selecting Variables for Linear Discriminant Function

1976

Journal Article

Further Results On Effect of Intraclass Correlation Among Training Samples in Discriminant-Analysis

McLachlan, GJ (1976). Further Results On Effect of Intraclass Correlation Among Training Samples in Discriminant-Analysis. Pattern Recognition, 8 (4), 273-275. doi: 10.1016/0031-3203(76)90047-9

Further Results On Effect of Intraclass Correlation Among Training Samples in Discriminant-Analysis

1976

Journal Article

Bias of Apparent Error Rate in Discriminant-Analysis

McLachlan, GJ (1976). Bias of Apparent Error Rate in Discriminant-Analysis. Biometrika, 63 (2), 239-244. doi: 10.2307/2335615

Bias of Apparent Error Rate in Discriminant-Analysis

1975

Journal Article

Confidence Intervals for Conditional Probability of Misallocation in Discriminant-Analysis

McLachlan, GJ (1975). Confidence Intervals for Conditional Probability of Misallocation in Discriminant-Analysis. Biometrics, 31 (1), 161-167. doi: 10.2307/2529717

Confidence Intervals for Conditional Probability of Misallocation in Discriminant-Analysis

1975

Journal Article

Iterative reclassification procedure for constructing an asymptotically optimal rule of allocation in discriminant analysis

McLachlan, G. J. (1975). Iterative reclassification procedure for constructing an asymptotically optimal rule of allocation in discriminant analysis. Journal of the American Statistical Association, 70 (350), 365-369. doi: 10.1080/01621459.1975.10479874

Iterative reclassification procedure for constructing an asymptotically optimal rule of allocation in discriminant analysis

1975

Journal Article

Some Expected Values for Error Rates of Sample Quadratic Discriminant Function

McLachlan, GJ (1975). Some Expected Values for Error Rates of Sample Quadratic Discriminant Function. Australian Journal of Statistics, 17 (3), 161-165. doi: 10.1111/j.1467-842x.1975.tb00953.x

Some Expected Values for Error Rates of Sample Quadratic Discriminant Function

Current funding

  • 2023 - 2026
    A Novel Approach to Semi-Supervised Statistical Machine Learning
    ARC Discovery Projects
    Open grant

Past funding

  • 2018 - 2022
    Classification methods for providing personalised and class decisions
    ARC Discovery Projects
    Open grant
  • 2017 - 2024
    ARC Training Centre for Innovation in Biomedical Imaging Technology
    ARC Industrial Transformation Training Centres
    Open grant
  • 2017 - 2020
    Power Quality Monitoring of Grids with High Penetration of Power Converters
    ARC Linkage Projects
    Open grant
  • 2017 - 2020
    Expanding the Role of Mixture Models in Statistical Analyses of Big Data
    ARC Discovery Projects
    Open grant
  • 2015 - 2018
    Gene expression profiling in critically ill patients with septic shock: The ADRENAL-GEPS Study
    NHMRC Project Grant
    Open grant
  • 2015 - 2017
    Large-Scale Statistical Inference: Multiple Testing
    ARC Discovery Projects
    Open grant
  • 2014 - 2016
    System to Synapse
    ARC Linkage Projects
    Open grant
  • 2014 - 2017
    Advanced Mixture Models for the Analysis of Modern-Day Data
    ARC Discovery Projects
    Open grant
  • 2012 - 2014
    System to synapse: a small animal imaging suite
    UQ Collaboration and Industry Engagement Fund
    Open grant
  • 2012 - 2014
    Joint Clustering and Matching of Multivariate Samples Across Objects
    ARC Discovery Projects
    Open grant
  • 2012 - 2014
    Statistical Modelling of Complex, High-Dimensional Data
    Vice-Chancellor's Senior Research Fellowship
    Open grant
  • 2011 - 2013
    A New Approach to Fast Matrix Factorization for the Statistical Analysis of High-Dimensional Data
    ARC Discovery Projects
    Open grant
  • 2008 - 2010
    Mixture models for high-dimensional clustering with applications to tumour classification, network intrusion, and text classification
    ARC Discovery Projects
    Open grant
  • 2007 - 2011
    Multivariate Methods for the Analysis of Microarray Gene-Expression Data with Applications to Cancer Diagnostics
    ARC Discovery Projects
    Open grant
  • 2007 - 2009
    Noncoding RNAs as prognostic markers and therapeutic targets in breast cancer
    NHMRC Project Grant
    Open grant
  • 2004
    ARC Network in Imaging Science and Technology
    ARC Seed Funding for Research Networks
    Open grant
  • 2004
    ARC Research Network in Microarray Technology
    ARC Seed Funding for Research Networks
    Open grant
  • 2003 - 2010
    ARC Centre of Excellence in Bioinformatics
    ARC Centres of Excellence
    Open grant
  • 2003
    Classification of Microarray Gene-Expression Data
    ARC Discovery Projects
    Open grant
  • 2003
    Classification of Microarray Gene-expression Data
    UQ External Support Enabling Grant
    Open grant
  • 2003
    Unsupervised learning of finite mixture models in data mining applications
    ARC Discovery Projects
    Open grant
  • 2000 - 2002
    Classification of Multiply Observed Features in Terms of Fitted Densities
    ARC Australian Research Council (Large grants)
    Open grant
  • 2000 - 2002
    On Algorithms for the Automatic Analysis and Segmentation of Correlated Images
    ARC Australian Research Council (Large grants)
    Open grant
  • 1999 - 2001
    Artificial Neural Networks and the EM Algorithm
    ARC Australian Research Council (Large grants)
    Open grant
  • 1999
    On mixture regression models with constrained components for application to failure data on heart valves
    ARC Australian Research Council (Small grants)
    Open grant
  • 1998
    Robust cluster analysis
    ARC Australian Research Council (Small grants)
    Open grant
  • 1997
    On mixture models in medical imaging
    ARC Australian Research Council (Small grants)
    Open grant
  • 1997 - 1999
    The Analysis of Plant Adaptation Data with Emphasis on Unbalanced Sets
    ARC Australian Research Council (Large grants)
    Open grant
  • 1995 - 1997
    Approximation of multi-dimensional functions for curve fitting and model building
    ARC Australian Research Council (Large grants)
    Open grant

Availability

Professor Geoffrey McLachlan is:
Available for supervision

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Supervision history

Current supervision

Completed supervision

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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