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mining

Project Leader(s): 

Dr. Guy Lapalme, Université de Montréal

Project team: 
Dr. Philippe Langlais, Université de Montréal
Dr. Pascal Vincent, Université de Montréal
Fabrizio Gotti, Université de Montréal
Non-academic participants: 
Funding period: 
April 1, 2021 - March 31, 2021

This project will explore new ways of customizing and translating the mass of daily information produced by Environment Canada (EC). This information in digital format is later transformed into weather and environmental forecasts, warnings and alerts that must be broadcast in real-time in at least two languages, in many different formats and in a way that takes location into account.

Project Leader(s): 

Dr. Yoshua Bengio, Université de Montréal

Project team: 
Dr. Hugh Chipman, Acadia University
Dr. Dale Schuurmans, University of Alberta
Dr. Pascal Vincent, Université de Montréal
Dr. Shai Ben-David, University of Waterloo
Funding period: 
February 25, 2022 - March 31, 2021

Statistical machine learning is an endeavor in which statisticians and computer scientists use computation to identify useful information from large amounts of data. Telecommunications, insurance and pharmaceutical companies use the team’s machine learning and data mining techniques to determine customer patterns, predict future customer behavior and better understand their needs. The project addresses some of the main practical and theoretical difficulties encountered when dealing with large datasets.

Project Leader(s): 

Dr. Jack A. Tuszynski , University of Alberta

Project team: 
Dr. Thoms Hillen, (University of Alberta)
Dr. Gerda de Vries, (University of Alberta)
Dr. Michael Y. Li, (University of Alberta)
Dr. D. Peter Tieleman, (University of Calgary)
Dr. Lukasz Kurgan, (University of Alberta)
Dr. Eric Cytrynbaum, (University of British Columbia)
Dr. Stephane Portet, (University of Manitoba)
Dr. Siv Sivaloganathan, (University of Waterloo)
Dr. Roderick Melnik, (Wilfrid Laurier University)
Funding period: 
July 1, 2021 - March 31, 2021
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Project Leader(s): 

Dr. Shelley Bull, University of Toronto

Project team: 
Dr. Rafal Kustra, University of Toronto
Dr. David Tritchler, University of Toronto
Dr. Gerarda Darlington, University of Guelph
Dr. Celia Greenwood, University of Toronto
Dr. Kenneth Morgan, McGill University
Dr. Jinko Graham, Simon Fraser University
Dr. Brad McNeney, Simon Fraser University
Dr. J.C. Loredo-Osti, Memorial University of Newfoundland
Dr. Joseph Beyene, University of Toronto
Funding period: 
February 25, 2022 - March 31, 2021

Complex traits, such as susceptibility to diabetes, cancer or tuberculosis, which vary in human and natural populations, are determined by multiple genetic and environmental factors that interact with one another in complicated ways. This interaction depends upon population characteristics as well as characteristics of the individual and the family.

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