Professor Nigel Bean is internationally known for his research in stochastic modelling. He completed his B.Sc. (Hons) in Applied Mathematics at the University of Adelaide in 1988 and his PhD at the University of Cambridge in 1993. Since then he has been at the University of Adelaide in roles varying from a Postdoctoral fellow, Lecturer, Senior Lecturer, Director of TRC Mathematical Modelling – a commercially funded contract research and consulting centre with a turnover then of over $750,000 – and then was appointed Chair of Applied Mathematics in 2004. Since then, he has been continuously on the School Management Committee and Head of Applied Mathematics. He has also been Director of Research (2011 - 2016) and Deputy Head of School (2004 - 06, 2012 -).
The quality of Professor Bean’s research has been recognised through the award of the 2001 JH Mitchell Medal by ANZIAM and the 2003 PAP Moran Medal by the Australian Academy of Science. Professor Bean has published about 91 scientific articles and has been awarded 8 ARC awards (Large Grants, Discovery Projects and a Linkage Grant). He has supervised twenty-three successful PhD students, six successful MPhil students, and is currently supervising nine more PhD students and six more MPhil students.
Professor Bean has been very active in national leadership roles. From 2008-2010, he was on the Board of the Federation of the Australian Scientific and Technological Societies as the Mathematical Sciences Cluster Representative and on the Board of the Australian Mathematical Sciences Institute (AMSI) from 2014 - 2016. In 2011 and 2012 he was a member of the ACARA Australian Curriculum: Mathematics Advisory Panel. Professor Bean was also Co-Chair of the Sub-committee for Mathematics and statistics research in universities and related institutions and a member of the Steering Committee, Mathematical Sciences Decadal Plan (2012 -- 2016), as well as being a member of the Steering Committee. Professor Bean is Deputy Chair of the AMSI Industry/Mathematical Sciences Engagement Task Force and a member of the AMSI Industry Advisory Committee.
This project combines large open datasets from social media with predictive machine learning models to predict social unrest events and monitor trends relevant to elections, both in Australia and abroad. The work is done in collaboration with researchers and software engineers from Data to Decisions CRC.
In this project we develop the necessary statistical techniques to analyze ancient DNA datasets to address important phylogenetic and population dynamic questions, such as the peopling of Australia and South America, and investigating the genetic diversity of Australia's endemic marsupials.
Invited talks, refereed proceedings and other conference outputs
Tuke, J., Nguyen A., Nasim M., Mellor D., Wickramasinghe A., Bean N. G., et al.
(2018). Pachinko Prediction: A Bayesian method for event prediction from social media data. arXiv preprint arXiv:1809.08427.
Fitzgerald, S. P., & Bean N. G.
(2016). The relationship between population T4/TSH set point data and T4/TSH physiology. Journal of Thyroid Research. 1-7. doi: 10.1155/2016/6351473
Price, D. J., Bean N. G., Ross J.V., & Tuke J.
(2016). On the efficient determination of optimal Bayesian experimental designs using ABC: A case study in optimal observation of epidemics. Journal of Statistical Planning and Inference. 172, 1-15. doi: 10.1016/j.jspi.2015.12.008
Dini, S., Binder B. J., Fischer S. C., Mattheyer C., Schmitz A., Stelzer E. H. K., et al.
(2016). Identifying the necrotic zone boundary in tumour spheroids with pair-correlation functions. Journal of The Royal Society Interface. 13(123), doi: 10.1098/rsif.2016.0649
Robinson, S. J., Souter N. J., Bean N. G., Ross J.V., Thompson R. M., & Bjornsson K. T.
(2015). Statistical description of wetland hydrological connectivity to the River Murray in South Australia under both natural and regulated conditions. Journal of Hydrology. 531, 929-939. doi: 10.1016/j.jhydrol.2015.10.006
Feenstra, J., McGarvey R., Linnane A., Punt A. E., & Bean N. G.
(2014). Environmental influences on daily commercial catch rates of South Australia's southern rock lobster (Jasus edwardsii). Fisheries Oceanography. 23(4), 362-374. doi: 10.1111/fog.12069