My Academic Publications

Classical Cryptography

• Bean, Richard; Lang, Sarah; Piorko, Megan. Solving an Alchemical Cipher in a Shared Notebook of John and Arthur Dee. International Conference on Historical Cryptology, 1-21. 2022 [DOI] [PDF]
• Bean, Richard. Declassified Cold War code-breaking manual has lessons for solving ‘impossible’ puzzles. The Conversation. 2021. The Conversation Media Trust [Web]
• Bean, Richard. Cryptodiagnosis of “Kryptos K4”. International Conference on Historical Cryptology, 25-33. 2021 [DOI] [PDF]
• Bean, Richard; Piorko, Megan; Lang, Sarah. Deciphering the Philosophers’ Stone: how we cracked a 400-year-old alchemical cipher. The Conversation. 2021. The Conversation Media Group [Web]
• Bean, Richard. The Use of Project Gutenberg and Hexagram Statistics to Help Solve Famous Unsolved Ciphers. Proceedings of the 3rd International Conference on Historical Cryptology HistoCrypt 2020(171), 31-35. 2020 [DOI] [PDF]
• Bean, Richard W; Lasry, George; Weierud, Frode. Eavesdropping on the Biafra-Lisbon link–breaking historical ciphers from the Biafran war. Cryptologia, 46(1), 1-66. 2022. Taylor & Francis [DOI] [PDF]
• Bean, Richard. Letter from Richard Bean. Journal of the Society for Psychical Research, 84(1), 56-57. 2020. Society for Psychical Research [PDF]
• Bean, Richard; Weierud, Frode; Lasry, George. We decrypted messages from the Biafran war that have remained secret for 50 years. The Conversation. 2020. The Conversation Media Trust [Web]
• Bean, Richard. Cryptology from the crypt: how I cracked a 70-year-old coded message from beyond the grave. The Conversation. 2019 [Web]

Combinatorics

• Bean, Richard. Latin trades on three or four rows. Discrete mathematics, 306(23), 3028-3041. 2006. Elsevier [DOI] [PDF]
• Bean, Richard; Bidkhori, Hoda; Khosravi, Maryam; Mahmoodian, ES. k-homogeneous Latin trades. Bayreuther Mathematische Schriften, 74, 7. 2005 [DOI] [PDF]
• Bean, Richard. The size of the smallest uniquely completable set in order 8 Latin squares. arXiv preprint math/0403005. 2004 [PDF]
• Bean, Richard. Critical sets in the elementary abelian 2-and 3-groups. arXiv preprint math/0403006. 2004 [PDF]
• Adams, Peter; Bean, Richard; Khodkar, Abdollah. A census of critical sets in the Latin squares of order at most six. Ars Combinatoria, 68, 203-224. 2003. Waterloo [Ont.] Dept. of Combinatorics and Optimization, University of Waterloo. [PDF]
• Bean, Richard; Mahmoodian, Ebadollah S. A new bound on the size of the largest critical set in a Latin square. Discrete mathematics, 267(1-3), 13-21. 2003. North-Holland [DOI] [PDF]
• Bean, Richard; Donovan, Diane; Khodkar, Abdollah; Street, Anne Penfold. Steiner trades that give rise to completely decomposable latin interchanges. International journal of computer mathematics, 79(12), 1273-1284. 2002. Taylor & Francis [DOI] [PDF]
• Adams, Peter; Bean, Richard; Khodkar, Abdollah. Disjoint critical sets in Latin squares. Congressus Numerantium, 33-48. 2001. Winnipeg; Utilitas Mathematica; 1998 [PDF]
• Bean, Richard Winston. Critical sets in Latin squares and associated structures.2001. University of Queensland [DOI] [PDF] [Source] [Overleaf]
• Bean, Richard; Donovan, Diane. Closing a gap in the spectrum of critical sets. Australasian Journal of Combinatorics, 22, 191-200. 2000. Centre for Combinatorics [Web] [PDF]

Energy

• Bean, Richard. Forecasting the Monash Microgrid for the IEEE-CIS Technical Challenge. Energies, 16(3), 1050. 2023. MDPI [DOI] [PDF]
• Bean, Richard. Methodology for forecasting and optimization in IEEE-CIS 3rd Technical Challenge. arXiv preprint arXiv:2202.00894. 2022 [DOI]
• Bean, Richard; Zhang, Yanjun; Ko, Ryan KL; Mao, Xinyu; Bai, Guangdong. Preserving the Privacy and Cybersecurity of Home Energy Data. Emerging Trends in Cybersecurity Applications, 301-322. 2022. Springer International Publishing Cham [DOI] [PDF]
• Abolghasemi, Mahdi; Bean, Richard. How to predict and optimise with asymmetric error metrics. arXiv preprint arXiv:2211.13586. 2022 [DOI] [PDF]
• Bergmeir, Christoph; de Nijs, Frits; Sriramulu, Abishek; Abolghasemi, Mahdi; Bean, Richard; Betts, John; Bui, Quang; Dinh, Nam Trong; Einecke, Nils; Esmaeilbeigi, Rasul. Comparison and Evaluation of Methods for a Predict+ Optimize Problem in Renewable Energy. arXiv preprint arXiv:2212.10723. 2022 [DOI] [PDF]
• Bean, Richard. Forecasting and Optimizing a Microgrid for the IEEE-CIS Technical Challenge. AUPEC2022. 2022 [PDF]
• Bean, Richard; Horrocks, Neil. How closely monitoring households’ energy data can unleash their solar outputs and (possibly) make them more money. The Conversation. 2022. The Conversation Media Trust [Web]
• Balson, Alexander; Bean, Richard; Chapman, Archie C; Snow, Stephen; Viller, Stephen; Horrocks, Neil; Glencross, Mashhuda. On-demand batteries as a peer-to-peer service. 2021 IEEE PES Innovative Smart Grid Technologies-Asia (ISGT Asia), 1-5. 2021. IEEE [DOI] [PDF]
• Tushar, Wayes; Saha, Tapan Kumar; Yuen, Chau; Azim, M Imran; Morstyn, Thomas; Poor, H Vincent; Niyato, Dustin; Bean, Richard. A coalition formation game framework for peer-to-peer energy trading. Applied Energy, 261, 114436. 2020. Elsevier [DOI] [PDF]
• Bean, Richard; Snow, Stephen; Glencross, Mashhuda; Viller, Stephen; Horrocks, Neil. Keeping the power on to home medical devices. Plos one, 15(7), e0235068. 2020. Public Library of Science San Francisco, CA USA [DOI] [PDF]
• Snow, Stephen; Bean, Richard; Glencross, Mashhuda; Horrocks, Neil. Drivers behind residential electricity demand fluctuations due to COVID-19 restrictions. Energies, 13(21), 5738. 2020. MDPI [DOI] [PDF]
• Tushar, Wayes; Saha, Tapan Kumar; Yuen, Chau; Morstyn, Thomas; Poor, H Vincent; Bean, Richard. Grid influenced peer-to-peer energy trading. IEEE Transactions on Smart Grid, 11(2), 1407-1418. 2019. IEEE [DOI] [PDF]
• Bean, Richard; Khan, Hina. Using solar and load predictions in battery scheduling at the residential level. arXiv preprint arXiv:1810.11178. 2018 [DOI] [PDF]
• Tushar, Wayes; Saha, Tapan Kumar; Yuen, Chau; Liddell, Paul; Bean, Richard; Poor, H Vincent. Peer-to-peer energy trading with sustainable user participation: A game theoretic approach. IEEE Access, 6, 62932-62943. 2018. IEEE [DOI] [PDF]
• Bean, Richard; Vanderwaal, Ben. Calculation of Minimum Reserve Levels for the Australian National Electricity Market. 17th Power Systems Computation Conference Stockholm Sweden - August 22-26, 2011, 364-371. 2011 [Web] [PDF]

Statistics

• McLachlan, Geoffrey J; Bean, Richard W; Ng, Shu-Kay. Clustering. Bioinformatics: Structure, Function and Applications, 423-439. 2008. Humana Press [DOI] [PDF]
• McLaren, Christine E; Gordeuk, Victor R; Chen, Wen-Pin; Barton, James C; Acton, Ronald T; Speechley, Mark; Castro, Oswaldo; Adams, Paul C; Snively, Beverly M; Harris, Emily L. 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. 2008. Mosby [DOI] [PDF]
• McLachlan, Geoffrey J; Bean, R; Ng, SK. Clustering of microarray data via mixture models. Statistical advances in biomedical sciences: clinical trials, epidemiology, survival analysis, and bioinformatics, 365-384. 2008. Hoboken, New Jersey: Wiley [DOI] [PDF]
• McLachlan, Geoffrey J; Bean, Richard W; Jones, L Ben-Tovim. Extension of the mixture of factor analyzers model to incorporate the multivariate t-distribution. Computational Statistics & Data Analysis, 51(11), 5327-5338. 2007. North-Holland [DOI] [PDF]
• Do, KA; McLachlan, GJ; Bean, R; Wen, S. Application of gene shaving and mixture models to cluster microarray gene expression data. Cancer Informatics, 5, 1.18E+17. 2007. SAGE Publications Sage UK: London, England [DOI] [PDF]
• McLaren, Christine E; Gordeuk, Victor R; Chen, Wen-Pin; Barton, James C; Acton, Ronald T; Speechley, Mark; Castro, Oswaldo; Adams, Paul C; Snively, Beverly M; Harris, Emily L. Subpopulations with Iron Deficiency, Liver Disease, or HFE Mutations Revealed by Statistical Mixture Modeling of Transferrin Saturation and Serum Ferritin Concentration in Asians, African Americans, Hispanics, and Whites.. Blood. 2007. American Society of Hematology [DOI] [PDF]
• McLachlan, Geoffrey J; Bean, Richard W; Jones, L Ben-Tovim. A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays. Bioinformatics, 22(13), 1608-1615. 2006. Oxford University Press [DOI] [PDF]
• McLachlan, Geoffrey J; Ng, Shu-Kay; Bean, Richard. Robust cluster analysis via mixture models. Austrian Journal of Statistics, 35(2&3), 157–174-157–174. 2006 [DOI] [PDF]
• Jones, Liat Ben-Tovim; Bean, Richard; McLachlan, Geoffrey J; Zhu, Justin Xi. Mixture models for detecting differentially expressed genes in microarrays. International journal of neural systems, 16(5), 353-362. 2006. World Scientific Publishing Company [DOI] [PDF]
• Ng, SK; McLachlan, GJ; Bean, RW; Ng, S-W. Clustering replicated microarray data via mixtures of random effects models for various covariance structures. Proceedings of the 2006 workshop on Intelligent systems for bioinformatics-Volume 73, 29-33. 2006 [Web] [PDF]
• Basford, Kaye; McLachlan, Geoff; Bean, Richard. Issues of robustness and high dimensionality in cluster analysis. Compstat 2006-Proceedings in Computational Statistics: 17th Symposium Held in Rome, Italy, 2006, 3-15. 2006. Physica-Verlag HD [DOI] [PDF]
• McLachlan, GJ; Bean, RW; Jones, L Ben-Tovim; Zhu, JX. Using mixture models to detect differentially expressed genes. Australian Journal of Experimental Agriculture, 45(8), 859-866. 2005. CSIRO Publishing [DOI] [PDF]
• Jones, Liat Ben-Tovim; Bean, Richard; McLachlan, Geoff; Zhu, Justin. Application of mixture models to detect differentially expressed genes. Intelligent Data Engineering and Automated Learning-IDEAL 2005: 6th International Conference, Brisbane, Australia, July 6-8, 2005. Proceedings 6, 422-431. 2005. Springer Berlin Heidelberg [DOI] [PDF]
• Bean, Richard; McLachlan, Geoff. Cluster analysis of high-dimensional data: A case study. Intelligent Data Engineering and Automated Learning-IDEAL 2005: 6th International Conference, Brisbane, Australia, July 6-8, 2005. Proceedings 6, 302-310. 2005. Springer Berlin Heidelberg [DOI] [PDF]
• Friedman, Jerome H; Meulman, Jacqueline J. Clustering objects on subsets of attributes (with discussion). Journal of the Royal Statistical Society: Series B (Statistical Methodology), 66(4), 815-849. 2004. Blackwell Publishing Oxford, UK [DOI] [PDF]
• McLachlan, Geoffrey J; Peel, David; Bean, Richard W. Modelling high-dimensional data by mixtures of factor analyzers. Computational Statistics & Data Analysis, 41(3-4), 379-388. 2003. North-Holland [DOI] [PDF]
• McLachlan, Geoffrey J.; Bean, Richard W; Peel, David. A mixture model-based approach to the clustering of microarray expression data. Bioinformatics, 18(3), 413-422. 2002. Oxford University Press [DOI] [PDF]

Transport

• Kimpton, Anthony; Loginova, Julia; Pojani, Dorina; Bean, Richard; Sigler, Thomas; Corcoran, Jonathan. Weather to scoot? How weather shapes shared e-scooter ridership patterns. Journal of Transport Geography, 104, 103439. 2022. Pergamon [DOI] [PDF]
• Kimpton, Anthony; Pojani, Dorina; Corcoran, Jonathan; Loginova, Julia; Bean, Richard; Sigler, Thomas. E-scooters are becoming wildly popular–but we have to factor in the weather. The Conversation. 2022. The Conversation Media Group [Web]
• Bean, Richard; Corcoran, Jonathan; Pojani, Dorina. How does weather affect bikeshare use? A comparative analysis of forty cities across climate zones. Journal of Transport Geography. 2021. Mendeley Data [DOI] [PDF]
• Bean, Richard; Pojani, Dorina; Corcoran, Jonathan. We analysed 100 million bike trips to reveal where in the world cyclists are most likely to brave rain and cold. The Conversation. 2021. The Conversation Media Group [Web]
• Pojani, Dorina; Chen, Jiashuo; Mateo-Babiano, Iderlina; Bean, Richard; Corcoran, Jonathan. Docked and dockless public bike-sharing schemes: research, practice and discourse. Handbook of Sustainable Transport, 129-138. 2020. Edward Elgar Publishing [DOI] [PDF]
• Mateo-Babiano, Iderlina; Pojani, Dorina; Corcoran, Jonathan; Bean, Richard. Here’s what bike-sharing programs need to succeed. The Conversation. 2017. The Conversation Media Trust [Web]
• Mateo-Babiano, Iderlina; Bean, Richard; Corcoran, Jonathan; Pojani, Dorina. How does our natural and built environment affect the use of bicycle sharing?. Transportation Research Part A: Policy and Practice, 94, 295-307. 2016. Pergamon [DOI] [PDF]

Chess

• Bean, Richard. Counting nodes in chess. Unpublished. 2003 [PDF]