Allan R. Willms

Allan R. Willms is a Professor in the Department of Mathematics and Statistics at the University of Guelph, Ontario, Canada. He received his B.Math and M.Math from the University of Waterloo and his Ph.D. from Cornell University in 1997. After working as a Visiting Scientist at Cornell and as a Lecturer at the University of Canterbury in New Zealand (1998-2003), he joined the University of Guelph faculty in 2003 where he continues to maintain an active research program.

Dr. Willms' research focuses on dynamical systems models of biological and physical processes, with particular emphasis on:

• Simple models of climate change, including paleoclimate transitions and Arctic climate bifurcations
• Parameter range reduction techniques for ordinary differential equation models
• Bifurcation theory with symmetry, including work on Huygens' clocks
• Mathematical biology applications spanning neuronal ion channels, disease transmission, fluid dynamics in biological systems, and veterinary medicine

His recent publications demonstrate a diverse research portfolio spanning mathematical biology, climate modeling, and complex analysis. The analysis of his work reveals a consistent theme of applying dynamical systems theory to solve practical problems across multiple disciplines, with a recent emphasis on veterinary applications and climate change modeling. His publications show a progression from fundamental mathematical theory to increasingly applied interdisciplinary work.

Dr. Willms has received multiple NSERC Discovery grants (2004, 2010, 2015, 2020) and has served as Editor for Biosystems (2014-present) and the International Journal of Applied Nonlinear Science (2012-2016). His research has been recognized with features as NPG Paper of the Month for 'Anthropocene Climate Bifurcation' and in DSWeb Magazine for 'Breathing Torus Near Double Hopf Bifurcation'.

He actively mentors students and maintains available positions for graduate students, undergraduates, and postdoctoral fellows. His research group develops computational tools for parameter estimation and dynamical systems analysis, including the PRRMD (Parameter Range Reduction using Monotonic Discretizations) software package and NEUROFIT for Hodgkin-Huxley model fitting.