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Ben Binder

Associate Professor
Mathematical Sciences
University of Adelaide
Australia

Biography

I was awarded my PhD in Applied Mathematics from the University of East Anglia, UK, 2005. The research involved numerical and analytical studies on non-linear free-surface flows. Shortly after completing my PhD I accepted a Research Associate position at the University of Adelaide, researching the chaotic dynamical systems approach to fluid mixing and its application to designing mixing devices. I briefly left Adelaide in 2007, joining the University of Melbourne as a Research Fellow. There I developed both discrete and continuous mathematical models for the neural crest cell invasion in the embryonic gut. I returned to the University of Adelaide in 2009, having been appointed a continuing position as a Lecturer in Applied Mathematics. My current research includes (i) quantifying and modelling biological spatial patterns and (ii) predicting channel bed topography in free-surface flows. I was awarded my PhD in Applied Mathematics from the University of East Anglia, UK, 2005. The research involved numerical and analytical studies on non-linear free-surface flows. Shortly after completing my PhD I accepted a Research Associate position at the University of Adelaide, researching the chaotic dynamical systems approach to fluid mixing and its application to designing mixing devices. I briefly left Adelaide in 2007, joining the University of Melbourne as a Research Fellow. There I developed both discrete and continuous mathematical models for the neural crest cell invasion in the embryonic gut. I returned to the University of Adelaide in 2009, having been appointed a continuing position as a Lecturer in Applied Mathematics. My current research includes (i) quantifying and modelling biological spatial patterns and (ii) predicting channel bed topography in free-surface flows.

Research Interest

Mathematical Sciences

Publications

  • Dini, S., Binder, B. & Green, J. (2018). Understanding interactions between populations: Individual based modelling and quantification using pair correlation functions. Journal of Theoretical Biology, 439, 50-64.

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