Dr Richard Bean

Research Fellow

School of Information Technology and Electrical Engineering
Faculty of Engineering, Architecture and Information Technology


Dr Richard Bean is working at the Centre for Energy Data Innovation. The Centre for Energy Data Innovation undertakes research using near real-time big data from low voltage electricity networks.

The centre is partnering with Redback Technologies/Luceo, Energy Queensland, and other entities to unlock new insights into electricity networks using IoT technology at a neighbourhood level. Richard has extensive experience in data science gained through working in academia in Australia and Iran, for government (Queensland Health) and industry (ROAM Consulting and the Australian Energy Market Operator). He has more than 40 publications in areas including combinatorics, statistics, power systems, and transport.

Outside of his academic work - although with some overlap - Richard enjoys cycling, cycling advocacy, and classical cryptography challenges.

Research Interests

  • Renewable energy
  • Power systems
  • Combinatorics
  • Machine learning

Research Impacts

At the Centre for Energy Data Innovation, experts in Electrical Engineering, Data Science and Interaction Design are working together to provide network operators with improved understanding of the rapidly changing landscape of local electricity generation and storage.

Richard's research at CEDI helps network operators to perform phase identification accurately and a low cost; and to use short and long term weather forecasts to predict solar and household energy usage at an aggregate level, which enables the efficient operation of a distribution network and operation of virtual power plants (VPPs) and embedded networks with batteries.

Previously, his research has focussed on areas as diverse as the combinatorics of Latin squares and designs, statistics (the analysis of gene microarray expression data, and clustering techniques), power systems analysis (scheduling battery charging using energy forecasting, and reserve planning in the Austrralian NEM), and transport (the effect of weather and land-use on bike share demand in cities across the world).


  • PhD, The University of Queensland


View all Publications


Book Chapter

  • Bean, Richard, Zhang, Yanjun, Ko, Ryan K. L., Mao, Xinyu and Bai, Guangdong (2023). Preserving the privacy and cybersecurity of home energy data. Emerging trends in cybersecurity applications. (pp. 323-343) edited by Kevin Daimi, Abeer Alsadoon, Cathryn Peoples and Nour El Madhoun. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-031-09640-2_14

  • Pojani, Dorina, Chen, Jiashuo, Mateo-Babiano, Iderlina, Bean, Richard and Corcoran, Jonathan (2020). Docked and dockless public bike-sharing schemes: research, practice and discourse. Handbook of sustainable transport. (pp. 129-138) edited by Carey Cutis. Cheltenham, Glos, United Kingdom: Edward Elgar Publishing. doi: 10.4337/9781789900477.00025

  • 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

  • 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

  • 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

Journal Article

Conference Publication

Other Outputs