0000-0002-7539-3465 About
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.
Employment
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University of Canterbury Professor2006 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (148)
- Key Challenges for Respiratory Virus Surveillance while Transitioning out of Acute Phase of COVID-19 Pandemic. Save
- Near-term forecasting of Covid-19 cases and hospitalisations in Aotearoa New Zealand Save
- The impact of Covid-19 vaccination in Aotearoa New Zealand: A modelling study Save
- Detectability of ten invasive mammal pests in New Zealand: a synthesis of spatial detection parameters Save
- Continued mitigation needed to minimise the high health burden from COVID-19 in Aotearoa New Zealand. Save
- Improving estimates of epidemiological quantities by combining reported cases with wastewater data: a statistical framework with applications to COVID-19 in Aotearoa New Zealand Save
- Modelling Aotearoa New Zealand's COVID-19 protection framework and the transition away from the elimination strategy. Save
- Modelling the impact of the Omicron BA.5 subvariant in New Zealand. Save
- Fishing for biodiversity by balanced harvesting Save
- THE ROLE OF THE MATHEMATICAL SCIENCES IN SUPPORTING THE COVID-19 RESPONSE IN AUSTRALIA AND NEW ZEALAND Save