Qualifications & Memberships
Michael Plank is a Professor in the School of Mathematics and Statistics at the University of Canterbury, a Fellow of the New Zealand Mathematical Society, and an Investigator at Te Pūnaha Matatini, New Zealand's Centre of Research Excellence in Complex Systems and Data Analytics. He obtained a BSc(Hons) in Mathematics from the University of Bristol in 2000 and a PhD in Applied Mathematics from the University of Leeds in 2003. He started at the University of Canterbury as a postdoctoral research fellow in 2004 and joined the permanent academic staff in 2006.
Professor Plank's research interests are in mathematical biology and mathematical epidemiology. His work aims to use mathematical techniques and modelling to help answer research questions in application areas and to support policymaking. His research is interdisciplinary and he has worked in a range of application areas including ecological and social networks, population dynamics, infectious diseases, marine ecosystems and fisheries, collective cell behaviour, and intracellular dynamics. His work draws on numerous fields in applied mathematics and statistics including stochastic processes, integro and partial differential equations, dynamical systems, spatial moments, statistical modelling, and parameter inference.
- Law R. and Plank MJ. (2023) Fishing for biodiversity by balanced harvesting. Fish and Fisheries 24(1): 21-39. http://dx.doi.org/10.1111/faf.12705.
- Lustig A., Vattiato G., Maclaren O., Watson LM., Datta S. and Plank MJ. (2023) Modelling the impact of the Omicron BA.5 subvariant in New Zealand. Journal of the Royal Society Interface 20(199) http://dx.doi.org/10.1098/rsif.2022.0698.
- Vattiato G., Lustig A., Maclaren O., Binny RN., Hendy SC., Harvey E., O'neale D. and Plank MJ. (2023) Modelling Aotearoa New Zealand's COVID-19 protection framework and the transition away from the elimination strategy. Royal Society Open Science 10(2) http://dx.doi.org/10.1098/rsos.220766.
- Binny RN., Lustig A., Hendy SC., Maclaren OJ., Ridings KM., Vattiato G. and Plank MJ. (2022) Real-time estimation of the effective reproduction number of SARS-CoV-2 in Aotearoa New Zealand. PeerJ 10 http://dx.doi.org/10.7717/peerj.14119.
- Binny RN., Priest P., French NP., Parry M., Lustig A., Hendy SC., Maclaren OJ., Ridings KM., Steyn N. and Vattiato G. (2022) Sensitivity of Reverse Transcription Polymerase Chain Reaction Tests for Severe Acute Respiratory Syndrome Coronavirus 2 Through Time. The Journal of infectious diseases 227(1): 9-17. http://dx.doi.org/10.1093/infdis/jiac317.