Dr Pamela Burrage is a Senior Lecturer in the School of Mathematical Sciences at the Queensland University of Technology (QUT) and is also an Associate Investigator of ACEMS.
She received her PhD in Mathematics from the University of Queensland (UQ) in 1999, with the thesis “Runge-Kutta methods for Stochastic Differential Equations”.
After being a post-doctoral fellow at UQ in the departments of Mathematics and Civil Engineering, she became an Education/Research Fellow in the Queensland Parallel Supercomputing Foundation (QPSF) (2001 – 2006), developing educational materials and teaching in the areas of Visualisation and High Performance Computing.
A position as Senior Research Fellow at the Institute for Molecular Bioscience (UQ), 2007 – 2009, followed. This was with the QosCosGrid project, modeling and simulating in parallel (on a computational grid) the complex dynamical processes that take place on the plasma membrane of a cell.
She joined QUT as a Senior Lecturer in 2010 in the School of Electrical Engineering and Computer Science, and from 2013 has been in the School of Mathematical Sciences.
Everybody is different, and every body is different. Significant variability is a common feature of all of the physiological systems that compose the function of the human body, and understanding this variability is critical to explaining differences in susceptibility to pathological conditions, and also to explaining how medical treatments can potentially succeed or fail even when applied to treat the same condition.
Burrage, K., Burrage P., Leier A., & Marquez-Lago T.
(2017). A Review of Stochastic and Delay Simulation Approaches in Both Time and Space in Computational Cell Biology.
(Holcman, D., Ed.).Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology. 241–261. doi: 10.1007/978-3-319-62627-7_11
Invited talks, refereed proceedings and other conference outputs
Burrage, P., Donovan D., Thompson B., & Burrage K.
(2015). Populations of Models, Experimental Designs and Coverage of Parameter Space by Latin Hypercube and Orthogonal Sampling. International Conference On Computational Science, ICCS 2015 - Computational Science at the Gates of Nature. doi: 10.1016/j.procs.2015.05.383
Donovan, D., Burrage K., Burrage P., McCourt TA., Thompson B., & Yazici EŞ.
(2018). Estimates of the coverage of parameter space by Latin Hypercube and Orthogonal Array-based sampling. Applied Mathematical Modelling. doi: 10.1016/j.apm.2017.11.036