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Professor Geordie Richards’ research focuses on the analysis of deterministic, stochastic nonlinear partial differential equations (PDEs) arising from physics and engineering, particularly equations modeling fluid and dispersive (wave-like) phenomena. His work utilizes PDE techniques to combine nonlinear analysis, probability theory, and dynamical systems theory. He conducts collaborative research with engineers and applied mathematicians on topics related to nonlinear dynamics and uncertainty quantification. His areas of focus include random data dispersive PDEs, ergodic theory, stochastic PDEs, singular stochastic PDEs, and uncertainty quantification applications. Geordie completed his PhD in Mathematics at the University of Toronto in 2012. He has held academic positions at the Institute for Mathematics and its Applications at the University of Minnesota (2012-2013), the Department of Mathematics at the University of Rochester (2013-2016), the Department of Mechanical and Aerospace Engineering at Utah State University (2016-2021), and the Department of Mathematical and Computational Sciences at the University of Toronto Mississauga (2021-2022) before joining the Department of Mathematics and Statistics at the University of Guelph in 2022.
Department of Mathematics & Statistics, University of Guelph • Guelph, ON, Canada
Teaching and researching in the field of Mathematics.
Department of Mechanical & Aerospace Engineering, Utah State University • Utah, USA
Involved in teaching and research within the Mechanical and Aerospace Engineering department.
Department of Mathematics, University of Rochester • Rochester, NY, USA
Focused on teaching and research in Mathematics.
Institute for Mathematics and its Applications, University of Minnesota • Minnesota, USA
Engaged in research activities and collaboration.
Department of Clinical Studies. Offers MSc by thesis (2 years) and MSc by coursework (1 year).