Simon Fraser University

To understand the fluid dynamics of marine phenomena fluid-structure interaction problems must be solved. Challenges exist in developing analytical and numerical techniques to solve these complex flow problems with boundary conditions at fluid...

Results on a two way convection-diffusion problem; an asymptotic error analysis on a piece-wise uniform grid; and a framework for understanding quadrature errors in Finite Element Methods are presented. These results were never published, although I...

Adaptive time stepping methods for meta-stable dynamics of the Allen Cahn and Cahn Hilliard equations are investigated in the spatially continuous, semi-discrete setting. Predicted behaviour of the number of time steps with specified local error...

Many problems in science and engineering are described in terms of equilibrium shapes on which certain conditions are imposed and which separate regions where the solution may have different properties. A prototypical problem of this type involves...

Efficient and accurate simulation of electromagnetic responses of geologically-rich geophysical settings is crucial in a variety of scenarios, including mineral and petroleum exploration, water resource utilizations, and geothermal power extractions...

In both normal tissue and disease states, cells interact with one another, and other tissue components using cellular adhesion proteins. These interactions are fundamental in determining tissue fates, and the outcomes of normal development, and...

Uncertainty Quantification (UQ) is an increasingly popular subject in computational science and engineering, that deals with assessing the impact on the PDE solution of the uncertainty on the coefficients of the same PDE. Coefficients here is a term...

The aim of this event is to offer graduate students in Statistics and Actuarial Science with an opportunity to attend a seminar with accessible talks providing them an introduction to active areas of research in the field. For three students from...

Compressive sensing (CS) is a general paradigm that enables us to measure objects (such as images, signals, or functions) by using a number of linear measurements proportional to their sparsity, i.e. to the minimal amount of information needed to...

The stochastic inverse problem of determining probability structures on input parameters for a physics model corresponding to a given probability structure on the output of the model forms the core of scientific inference and engineering design. We...