
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 Diploma of Science (Advanced), The University of Queensland
- Australian Mathematical Society, Australian Mathematical Society
Works
Search Professor Geoffrey McLachlan’s works on UQ eSpace
2008
Journal Article
Professor Gopal Kanji's retirement as editor of Journal of Applied Statistics
Agrawal, M. C., Caudill, Steven B., Chakraborti, S., Draper, Norman, Dryden, Ian, Gani, Joe, Gilmour, Steven G., Govindarajulu, Z., Hand, David J., Franses, Philip Hans, Kacker, Raghu, Khamis, Harry, Khuri, Andre I., Lewis, Toby, Mardia, Kanti, McLachlan, Geoff, Naik, Dayanand, Prescott, Phil, Kumar, V. S. Sampath, Tomizawa, Sadao and Wynn, Henry (2008). Professor Gopal Kanji's retirement as editor of Journal of Applied Statistics. Journal of Applied Statistics, 35 (1), 1-8. doi: 10.1080/02664760701814495
2008
Book
The EM algorithm and extensions
McLachlan, Geoffrey J. and Krishnan, Thriyambakam (2008). The EM algorithm and extensions. 2nd ed. Hoboken, NJ, United States: John Wiley & Sons. doi: 10.1002/9780470191613
2008
Book Chapter
Correcting for Selection Bias via Cross-Validation in the Classification of Microarray Data
McLachlan, G J., Chevelu, J. and Zhu, J. (2008). Correcting for Selection Bias via Cross-Validation in the Classification of Microarray Data. Beyond Parametrics in Interdisciplinary Research: Festschrift in Honor of Professor Pranab K. Sen. (pp. 364-376) edited by Balakrishnan, N., Pena, E. A. and Silvapulle, M. J.. United States: Institute of Mathematical Statistics. doi: 10.1214/193940307000000284
2008
Conference Publication
Clustering via mixture regression models with random effects
McLachlan, G. J., Ng, S. K. and Wang, K. (2008). Clustering via mixture regression models with random effects. 18th Symposium on Computational Statistics (COMSTAT 2008), Porto, Portugal, 24-29 August 2008. Heidelberg, Germany: Physica-Verlag,. doi: 10.1007/978-3-7908-2084-3_33
2008
Book Chapter
Clustering
McLachlan, G. J., Bean, R. W. and Ng, S.-K. (2008). Clustering. Bioinformatics, volume 2: Structure, function and applications. (pp. 423-439) edited by J. M. Keith. New Jersey, United States: Humana Press. doi: 10.1007/978-1-60327-429-6_22
2008
Journal Article
Large-scale simultaneous inference with applications to the detection of differential expression with microarray data (with discussion)
McLachlan, Geoff J., Wang, Kent and Ng, Shu Kay (2008). Large-scale simultaneous inference with applications to the detection of differential expression with microarray data (with discussion). Statistica, 68 (1), 1-30. doi: 10.6092/issn.1973-2201/3525
2008
Journal Article
Top 10 Algorithms in Data Mining
Wu, X., Kumar, V., Quinlan, J. R., Ghosh, J., Yang, Q., Motoda, H., McLachlan, G. J., Ng, A., Liu, B., Yu, P. S., Zhou, Z. H., Steinbach, M., Hand, D. J. and Steinberg, D. (2008). Top 10 Algorithms in Data Mining. Knowledge and Information Systems, 14 (1), 1-37. doi: 10.1007/s10115-007-0114-2
2007
Journal Article
Two-component Poisson Mixture Regression Modelling of Count Data With Bivariate Random Effects
Wang, Kui, Yau, Kelvin K. W., Lee, Andy H. and McLachlan, Geoffrey J. (2007). Two-component Poisson Mixture Regression Modelling of Count Data With Bivariate Random Effects. Mathematical and Computer Modelling, 46 (11-12), 1468-1476. doi: 10.1016/j.mcm.2007.02.003
2007
Journal Article
Resolving the latent structure of schizophrenia endophenotypes using expectation-maximization-based finite mixture modeling
Lenzenweger, M. F., McLachlan, G. J. and Rubin, D. B. (2007). Resolving the latent structure of schizophrenia endophenotypes using expectation-maximization-based finite mixture modeling. Journal of Abnormal Psychology, 116 (1), 16-29. doi: 10.1037/0021-843X.116.1.16
2007
Journal Article
A Score Test for Overdispersion in Zero-Inflated Poisson Mixed Regression Model
Xiang, L., Lee, A. H., Yau, K. K. W. and McLachlan, G. J. (2007). A Score Test for Overdispersion in Zero-Inflated Poisson Mixed Regression Model. Statistics in Medicine, 26 (7), 1608-1622. doi: 10.1002/sim.2616
2007
Journal Article
Extension of Mixture-of-Experts Networks for Binary Classification of Hierarchical Data
Ng, S. K. and McLachlan, G. J. (2007). Extension of Mixture-of-Experts Networks for Binary Classification of Hierarchical Data. Artificial Intelligence in Medicine, 41 (1), 57-67. doi: 10.1016/j.artmed.2007.06.001
2007
Journal Article
Application of gene shaving and mixture models to cluster microarray gene expression data
Do, K. A., McLachlan, G. J., Bean, R. W. and Wen, S. (2007). Application of gene shaving and mixture models to cluster microarray gene expression data. Cancer Informatics, 5, 25-43. doi: 10.1177/117693510700500002
2007
Conference Publication
Resolving the latent structure of schizophrenia endophenotypes using em-based finite mixture modeling
Lenzenweger, M. F., McLachlan, G. and Rubin, D. B. (2007). Resolving the latent structure of schizophrenia endophenotypes using em-based finite mixture modeling. 10th International Congress on Schizophrenia Research, Savannah Ga, 02-06 April 2005. Oxford, United Kingdom: Oxford University Press. doi: 10.1093/schbul/sbm004
2007
Journal Article
Maternity length of stay modelling by Gamma mixture regression with random effects
Lee, Andy H., Wang, Kui, Yau, Kelvin K. W., McLachlan, Geoffrey J. and Ng, Shu Kay (2007). Maternity length of stay modelling by Gamma mixture regression with random effects. Biometrical Journal, 49 (5), 750-764. doi: 10.1002/bimj.200610371
2007
Journal Article
Segmentation and intensity estimation of microarray images using a gamma-t mixture model
Baek, J., Son, Y. S. and McLachlan, G. J. (2007). Segmentation and intensity estimation of microarray images using a gamma-t mixture model. Bioinformatics, 23 (4), 458-465. doi: 10.1093/bioinformatics/btl630
2007
Journal Article
Multilevel Survival Modelling of Recurrent Urinary Tract Infections
Wang, Kui, Yau, Kelvin K. W., Lee, Andy H. and McLachlan, Geoffrey J. (2007). Multilevel Survival Modelling of Recurrent Urinary Tract Infections. Computer Methods and Programs in Biomedicine, 87 (3), 225-229. doi: 10.1016/j.cmpb.2007.05.013
2007
Journal Article
Extension of the Mixture of Factor Analyzers Model to Incorporate the Multivariate t-Distribution
McLachlan, G. J., Bean, R. W. and Jones, L. B. T. (2007). Extension of the Mixture of Factor Analyzers Model to Incorporate the Multivariate t-Distribution. Computational Statistics & Data Analysis, 51 (11), 5327-5338. doi: 10.1016/j.csda.2006.09.015
2007
Journal Article
A tutorial in genetic epidemiology and some considerations in statistical modeling
Suarez, E., Sariol, C. A., Burguete, A. and McLachlan, G. J. (2007). A tutorial in genetic epidemiology and some considerations in statistical modeling. Puerto Rico Health Sciences Journal, 26 (4), 401-421.
2007
Conference Publication
Merging algorithm to reduce dimensionality in application to web-mining
Nikulin, V and McLachlan, GJ (2007). Merging algorithm to reduce dimensionality in application to web-mining. 20th Australian Joint Conference on Artificial Intelligence, Gold Coast, Qld, Australia, 2-6 December, 2007. Berlin, Germany: Springer Berlin / Heidelberg. doi: 10.1007/978-3-540-76928-6_88
2007
Conference Publication
Subpopulations with iron deficiency, liver disease, or HFE mutations revealed by statistical mixture modeling of transferrin saturation and serum ferritin concentration in Asians, African American, Hispanics, and Whites
McLaren, C. E., Gordeuk, V. R., Chen, W. P., Barton, J. C., Acton, R. T., Speechley, M., Castro, O., Adams, P. C., Snively, B. M., Harris, E. L., Reboussin, D. M., McLachlan, G. J., Bean, R. and McLaren, G. D. (2007). Subpopulations with iron deficiency, liver disease, or HFE mutations revealed by statistical mixture modeling of transferrin saturation and serum ferritin concentration in Asians, African American, Hispanics, and Whites. 49th Annual Meeting of the American Society of Hematology, Atlanta, GA, U.S.A., 8 - 11 December 2007. Washington, DC, U.S.A.: American Society of Hematology.
Funding
Current funding
Past funding
Supervision
Availability
- Professor Geoffrey McLachlan is:
- Available for supervision
Before you email them, read our advice on how to contact a supervisor.
Supervision history
Current supervision
-
Doctor Philosophy
Role of Finite Mixture Models in Semi-Supervised Learning
Principal Advisor
Other advisors: Dr Sharon Lee
-
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
-
Doctor Philosophy
Learning a mineralised fault network at the Cracow Gold Mine from geologically-informed 3D synthetic seismic data
Associate Advisor
Other advisors: Dr Dion Weatherley, Professor Rick Valenta
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
-
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2015
Doctor Philosophy
Finite Mixture Models for Regression Problems
Principal Advisor
Other advisors: Dr Ian Wood
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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
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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
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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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