HIV-1 remains a global health challenge, with over 35 million people infected. The high rates of turnover and evolutionary adaptability exhibited by HIV-1 pose a particular challenge to the use of antiretrovirals, as well as the development of a vaccine. Our focus is to understand the dynamics of two of the most commonly tracked clinical markers of an HIV-1 infection: CD4+ T cells/mm3 (CD4 count) and HIV-1 RNA/ml (viral load).

Computational Fluid Dynamics (CFD) is a branch of fluid mechanics that is focused on using numerical methods to solve and analyze practical engineering problems involving fluid flow. The purpose of the proposed research project is to develop novel simulation methods directed at applications in sensitivity analysis and design optimization. Sensitivity and optimization studies are becoming more common as engineers are challenged to determine optimal operating configurations for their designs.

Quantitative interpretation of magnetic data through inversion for general distributions of magnetic susceptibility has played an increasingly important role in mineral exploration in recent years. The goal of the proposed project is to develop efficient and robust computational simulation tools for the inversion of magnetization at a specified depth using ground/airborne magnetic data.

Cascades within the MITACS Elevation program are threefold: a. Ensure their industrial voice is represented on this international consensus building  process b. Being proactive, influence the process and anticipate the developments on the consensus around water footprinting methods c. Generate industry specific case studies to test  the method, ensure key problems are addressed and increase internal awareness Supporting the researcher that will lead the international process conducted under WULCA group is the mean of meeting the above mentioned objectives.

This research project tackles a condition-based maintenance optimization problem in the railway equipment at ArcelorMittal Infrastructure Canada (AMIC). Logical Analysis of Data (LAD), a data mining technique, will be applied to exploit thousands of data records in order to identify and predict failure causes and degradation behavior of the equipment under study. New knowledge discovery approaches will be developed in order to deal with AMIC’s large scale databases. Mathematical programming and artificial intelligence techniques will be employed to develop these approaches.

Computational Fluid Dynamics (CFD) is a branch of fluid mechanics that is focused on using numerical methods to solve and analyze practical engineering problems involving fluid flow. The purpose of the proposed research project is to develop novel simulation methods directed at applications in sensitivity analysis and design optimization. Sensitivity and optimization studies are becoming more common as engineers are challenged to determine optimal operating configurations for their designs.

The goal of this project is to develop a software system to collect, store, organize and query Twitter messages, and to develop algorithms that can process the Twitter data to extract value-added information, in particular, the geolocation of Tweets. First, we will design and implement a processing and analytics system for Twitter data using the Apache Spark environment. Second, we will research and extend advanced algorithms to infer the geolocation of Tweets from their contents.

L’une des stratégies mise en oeuvre par Hydro-Québec pour accompagner la demande croissante d’électricité, consiste à caractériser les phénomènes contribuant à la dégradation des turbines hydrauliques. Dans cette optique, le phénomène de cavitation est étudié, car il est à l’origine de l’érosion et donc de l’endommagement des turbines. Ce phénomène correspond au passage de l’eau de l’état liquide à l’état gazeux sous l’effet d’une baisse de pression, engendrée par la rotation des aubes de la turbine.

Understanding the underlying factors that cause inherited diseases to develop is an important step in improving the health status of individuals, and identifying effective prevention and control measures. This project aims to apply fundamental know of genetics, genome sequence analysis, modeling and simulations, and bio-informatics to uncover the relationship between these factors and assess the risk of such diseases.

This project is to focus on building an application that can be used to perform a audiology-grade calibration of consumer headphones (and microphones) on a mobile device (such as an iPhone or iPad). The intern will use mathematical techniques (such as spectral analysis) to help gather and analyze user information more efficiently in order to provide a fast, accurate assessment of the user’s hardware capabilities for the purposes of hearing testing.