The Development of Focused Retrieval Tools to Support Energy Conservation and Management using an n-gram Based Approach
Postdoctoral fellow: Dr. Jane E. Mason, David R. Cheriton School of Computer Science, University of Waterloo
Lead faculty member: Dr. Frank Tompa, David R. Cheriton School of Computer Science, University of Waterloo
Business Intelligence (BI) refers to computer-based techniques that facilitate the use of information within organizations to make informed decisions and to run operations effectively based on available data. Our goal is the research and development of new BI tools for focused search and retrieval, which will support analysis and decision-making related to energy conservation and management. Such tools will also have wide applicability to business analytics in general.
Development of a Direct Experimental Test to Measure the Effect of Fish Farms on Wild Salmon Survival
Postdoctoral fellow: Dr. Wendell Challenger, Department of Statistics and Actuarial Science, Simon Fraser University
Lead faculty member: Dr. Carl Schwarz, Department of Statistics and Actuarial Science, Simon Fraser University
The effect of the British Columbia aquaculture industry on wild salmon stocks is currently unclear. In this project we will create a scientific advisory panel to guide development of an explicit experiment testing the effect of fish farms on wild smolt survival by using a large-scale marine telemetry array to measure survival of key BC salmon stocks. The PDF will extend Kintama’s existing mathematical software to design an optimal 2nd generation array to measure the effect of fish farm exposure on survival and advance aspects of the underlying mathematics.
Postdoctoral fellow: Dr. Clinton Groth, Institute for Aerospace Studies, University of Toronto
Lead faculty member: Dr. Marc Charest, Institute for Aerospace Studies, University of Toronto
Combustion of fossil fuels is responsible for a major fraction of greenhouse gas emissions and the emission of pollutants such as nitrogen oxides (NOx), carbon monoxide (CO), soot, aerosols and other harmful chemical species. Reducing Canada’s dependence on fossil fuels is one of today’s major challenges. To design new pollutant-free combustion devices, improved mathematical models and computational tools for describing reactive flows are required. These models will enable a new understanding of combustion and lead to improved combustor designs and energy systems.
Postdoctoral fellow: Dr. Lee Betchen
Lead faculty member: Dr. Hans De Sterck
Novel methods for the computationally efficient simulation of compressible fluid flow will be developed, with applications to aerospace and space physics. First, new formulations of multigrid techniques for the implicit solution of time-dependent flows will be studied, using parabolization to increase diagonal dominance and solution efficiency. Second, new direct solution methods for steady transonic flows will be developed, employing dynamical systems and characteristic analysis.
Postdoctoral fellow: Dr. Xiaodong Wang, Institute for Aerospace Studies, University of Toronto
Lead faculty member: Dr. David Zingg, Institute for Aerospace Studies, University of Toronto
Modern engineering designs require fast and high credible scientific computations which usually run in a parallel way. The proposed research focuses on the development of the parallel preconditioning technology used in large scale scientific computations. A multi-level recursive strategy is developed to improve the parallel computing performance when a large number of processors (up to at least 5000) are used. An existing Newton-Krylov flow solver will be improved by coupling with this multi-level preconditioner.
Postdoctoral fellow: Dr. Mathieu Sinn, David R. Cheriton School of Computer Science, University of Waterloo
Lead faculty member: Dr. Pascal Poupart, David R. Cheriton School of Computer Science, University of Waterloo
We will develop algorithms to automatically generate descriptive labels for large collections of web documents. Such labels can be used by companies in order to decide on which web sites they want to place advertisements, or by electronic publishers to categorize media offers. Currently, there doesn't exist any approach that can robustly and automatically label clusters of documents with a level of quality that approaches human labellers.
Postdoctoral fellow: Dr. Lung Kwan Tsui, Department of Statistics and Actuarial Science, University of Waterloo
Lead faculty member: Dr. David Saunders, Department of Statistics and Actuarial Science, University of Waterloo
The consequences of the mismanagement of credit risk and mispricing of structured credit portfolios are notorious. The purpose of this project is to research, develop and implement superior methods for managing credit derivatives, from single name instruments such as credit default swaps to complex structured products, such as mortgage-backed securities and collateralized debt obligations. The algorithms investigated will employ a bottom-up approach, based on realistic modeling of the underlying collateral instruments (e.g. mortgages).
Postdoctoral fellow: Dr. Carlton Davis, Computer and Software Engineering, Ecole Polytechnique de Montréal
Lead faculty member: Dr. Jose Fernandez, Computer and Software Engineering, Ecole Polytechnique de Montréal
Botnets are networks consisting of computers that are infected with malicious codes (malware) and are consequently being remotely controlled by botnet operators. Botnets pose some of the most challenging security problems owing to their ubiquitousness, their size, their complexity, and the effectiveness with which they have been used to facilitate and perpetuate a wide range of cybercrimes.
The Inverse Problem Accounting for Therapeutic Variability: Development of a Practical Strategy to Maximally Extract Information from Limited Clinical Data
Postdoctoral fellow: Dr. Olivier Barrière, Faculty of Pharmacy, Université de Montréal
Lead faculty member: Dr. Fahima Nekka, Faculty of Pharmacy, Université de Montréal
Pharmacometrics (PM) is an emerging research area defined as “the science that interprets and describes pharmacology in a quantitative fashion to aid efficient drug development and/or regulatory decision”. Over the years, Dr. Nekka’s team has encompassed deep thinking on how to join and enhance emerging worldwide efforts to make mathematical modeling and simulation a complementary language to the usual empirical and clinical methods used in drug discovery and development. This work is part of these sustained efforts to deal with the complex relationship of dose-exposure-effect of drugs.
Postdoctoral fellow: Dr. Yijun Lou, Mathematics and Statistics, York University
Lead faculty member: Dr. Jane Heffernan, Mathematics and Statistics, York University
Genital herpes (GH), caused by Herpes simplex virus type 1 or 2 (HSV-1 or -2), is one of the most prevalent sexually transmitted diseases in the world. Currently, there is no effective treatment for GH, but a new vaccine Simplirix (by GSK), is currently in clinical trials. Simplirix has had some success in preventing disease, but only in females that are HSV-1 and -2 negative. Since oral herpes (OH, also caused by HSV-1 and -2) infection can occur at very early ages, vaccination against GH may be most effective in a childhood vaccination program.