Skip to menu Skip to content Skip to footer
Dr Richard Bean
Dr

Richard Bean

Email: 

Overview

Background

Dr Richard Bean is an affiliate at the UQ Cyber Research Centre.

Richard brings to his work a rich background in data science honed in academia in Australia and Iran, as well as in government (Queensland Health) and industry sectors (ROAM Consulting, Redback, and the Australian Energy Market Operator). With over 60 publications to his name, his research interests span a wide range of areas, including combinatorics, statistics, power systems, classical cryptography, and transport. He is a Fellow of the Australian Institute of Energy and current chair of the Newcastle branch.

Richard is well-known in the public sphere, frequently appearing on radio shows to share his insights into the solutions for various unsolved ciphers. His research extends into areas of national science and research priorities, such as Energy, Transport, Health, and Cyber Security.

In addition to his academic pursuits, Richard has a passion for cycling and is active in cycling advocacy. He also enjoys tackling classical cryptography challenges in his free time.

Availability

Dr Richard Bean is:
Not available for supervision
Media expert

Qualifications

  • Doctor of Philosophy, The University of Queensland

Research interests

  • Renewable energy

  • Power systems

  • Combinatorics

  • Classical cryptography

Research impacts

Richard has previously focused his research on a broad array of topics. These include the combinatorics of Latin squares and designs, the analysis of gene microarray expression data, clustering techniques, and scheduling battery charging using energy forecasting. His research in transport has shed light on the effect of weather and land-use on bike share demand in cities worldwide.

Whether in academia, industry, or the public sphere, Richard's work consistently strives to make an impact by shedding new light on complex data and helping to shape the future of energy, transport, health, and cyber security.

Works

Search Professor Richard Bean’s works on UQ eSpace

69 works between 2000 and 2025

41 - 60 of 69 works

2017

Book Chapter

Clustering

McLachlan, G. J., Bean, R. W. and Ng, S. K. (2017). Clustering. Bioinformatics Vol. II: Structure, Function, and Applications. (pp. 345-362) edited by Jonathan M. Keith. New York, NY, United States: Humana Press. doi: 10.1007/978-1-4939-6613-4_19

Clustering

2016

Journal Article

How does our natural and built environment affect the use of bicycle sharing?

Mateo-Babiano, Iderlina, Bean, Richard, Corcoran, Jonathan and Pojani, Dorina (2016). How does our natural and built environment affect the use of bicycle sharing?. Transportation Research Part A: Policy and Practice, 94, 295-307. doi: 10.1016/j.tra.2016.09.015

How does our natural and built environment affect the use of bicycle sharing?

2011

Conference Publication

Calculation of minimum reserve levels for the Australian national electricity market

Bean, Richard and Vanderwaal, Ben (2011). Calculation of minimum reserve levels for the Australian national electricity market. 17th Power Systems Computation Conference, Stockholm, Sweden, 22-26 August 2011. Red Hook, NY, United States: Curran Associates.

Calculation of minimum reserve levels for the Australian national electricity market

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

Clustering

2008

Journal Article

Bivariate mixture modeling of transferrin saturation and serum ferritin concentration in Asians, African Americans, Hispanics, and whites in the Hemochromatosis and Iron Overload Screening (HEIRS) Study

McLaren, C. E., Gordeuk, V. R., Chen, W. -P., Barton, J. C., Action, R. T., Speechley, M., Castro, O., Adams, P. C., Snively, B. M., Harris, E. L., Reboussin, D. M., McLachlan, G. J. and Bean, R. (2008). Bivariate mixture modeling of transferrin saturation and serum ferritin concentration in Asians, African Americans, Hispanics, and whites in the Hemochromatosis and Iron Overload Screening (HEIRS) Study. Translational Research, 151 (2), 97-109. doi: 10.1016/j.trsl.2007.10.002

Bivariate mixture modeling of transferrin saturation and serum ferritin concentration in Asians, African Americans, Hispanics, and whites in the Hemochromatosis and Iron Overload Screening (HEIRS) Study

2008

Book Chapter

Clustering of microarray data via mixture models

McLachlan, Geoffrey J., Ng, Angus and Bean, Richard W. (2008). Clustering of microarray data via mixture models. Statistical advances in the biomedical sciences: clinical trials, epidemiology, survival analysis, and bioinformatics. (pp. 365-383) edited by Atanu Biswas, Sujay Datta, Jason P. Fine and Mark R. Segal. Hoboken, NJ, United States: John Wiley & Sons. doi: 10.1002/9780470181218.ch21

Clustering of microarray data via mixture models

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

Application of gene shaving and mixture models to cluster microarray gene expression data

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

Extension of the Mixture of Factor Analyzers Model to Incorporate the Multivariate t-Distribution

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.

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

2006

Journal Article

Mixture models for detecting differentially expressed genes in microarrays

Jones, L. B. T., Bean, R., McLachlan, G. J. and Zhu, J. X. (2006). Mixture models for detecting differentially expressed genes in microarrays. International Journal of Neural Systems, 16 (5), 353-362. doi: 10.1142/S0129065706000755

Mixture models for detecting differentially expressed genes in microarrays

2006

Journal Article

Robust cluster analysis via mixture models

McLachlan, G J, Ng, S K and Bean, R W (2006). Robust cluster analysis via mixture models. Austrian Journal of Statistics, 35 (2 & 3), 157-174.

Robust cluster analysis via mixture models

2006

Conference Publication

Issues of robustness and high dimensionality in cluster analysis

Basford, Kaye, McLachlan, Geoff and Bean, Richard (2006). Issues of robustness and high dimensionality in cluster analysis. 17th Symposium on Computational Statistics (COMSTAT 2006), Rome, Italy, 28 August - 1 September 2006. Rome, Italy: Physica-Verlag. doi: 10.1007/978-3-7908-1709-6_1

Issues of robustness and high dimensionality in cluster analysis

2006

Journal Article

Latin trades on three or four rows

Bean, Richard (2006). Latin trades on three or four rows. Discrete Mathematics, 306 (23), 3028-3041. doi: 10.1016/j.disc.2005.06.040

Latin trades on three or four rows

2006

Conference Publication

Clustering replicated microarray data in mixtures of random effects models for varius covariance structures

Ng, S K, McLachlan, G J, Bean, R W and NG, SW (2006). Clustering replicated microarray data in mixtures of random effects models for varius covariance structures. 2006 Workshop on Intelligent Systems for Bioinformatics (WISB, Hobart, Australia, 4 December 2006. Sydney: The Australian Computer Society.

Clustering replicated microarray data in mixtures of random effects models for varius covariance structures

2006

Journal Article

A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays

McLachlan, GJ, Bean, RW and Jones, LBT (2006). A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays. Bioinformatics, 22 (13), 1608-1615. doi: 10.1093/bioinformatics/btl148

A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays

2005

Journal Article

Critical sets in the elementary abelian 2- And 3-groups

Bean, Richard (2005). Critical sets in the elementary abelian 2- And 3-groups. Utilitas Mathematica, 68, 53-61.

Critical sets in the elementary abelian 2- And 3-groups

2005

Journal Article

Using mixture models to detect differentially expressed genes

McLachlan, G. J., Bean, R. W., Jones, L. and Zhu, J. X. (2005). Using mixture models to detect differentially expressed genes. Australian Journal Of Experimental Agriculture, 45 (7-8), 859-866. doi: 10.1071/EA05051

Using mixture models to detect differentially expressed genes

2005

Journal Article

Cluster analysis of high-dimensional data: A case study

Bean, R and McLachlan, G (2005). Cluster analysis of high-dimensional data: A case study. Intelligent Data Engineering And Automated Learning Ideal 2005, Proceedings, 3578 (-), 302-310.

Cluster analysis of high-dimensional data: A case study

2005

Conference Publication

Application of mixture models to detect differentially expressed genes

Jones, LBT, Bean, R, McLachlan, G and Zhu, J (2005). Application of mixture models to detect differentially expressed genes. Berlin: Springer-Verlag Berlin. doi: 10.1007/11508069_55

Application of mixture models to detect differentially expressed genes

2004

Journal Article

Clustering objects on subsets of attributes - Discussion

Hand, DJ, Glasbey, C, Husmeier, D, Gower, JC, van Houwelingen, HC, Bugrien, JB, Nason, G, Critchley, F, Hoff, PD, McLachlan, GJ and Bean, RW (2004). Clustering objects on subsets of attributes - Discussion. Journal of The Royal Statistical Society Series B-statistical Methodology, 66 (4), 839-849.

Clustering objects on subsets of attributes - Discussion

Media

Enquiries

Contact Dr Richard Bean directly for media enquiries about:

  • ciphers
  • codes
  • combinatorics
  • cryptanalysis
  • cryptography
  • cryptology

Need help?

For help with finding experts, story ideas and media enquiries, contact our Media team:

communications@uq.edu.au