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University of Toronto

Project Leader(s): 

Postdoctoral fellow: Dr. Nima Safaei, Mechanical and Industrial Engineering, University of Toronto

Lead faculty member: Dr. Andrew K.S. Jardine, Mechanical and Industrial Engineering, University of Toronto

Non-academic participants: 

The research is aimed at providing effective long-term resource planning to effective scheduling of the maintenance tasks over a short-term horizon. The Bombardier Company provides the necessary requirements to the customers around the world to do the predefined maintenance tasks as well as unexpected repair jobs for their aircraft fleet. These services are performed as onsite or offsite, i.e., different centres or stations.

Project Leader(s): 

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.

Project Leader(s): 

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.

Project Leader(s): 

Postdoctoral fellow: Dr. Hamid Usefim, Mathematics, University of Toronto

Lead faculty member: Dr. Kumar Murty, Mathematics, University of Toronto

Protecting copyright is one of the hottest topics in information and media technology at the moment. Digital technology enables perfect copying on amateur equipment. Digital Fingerprinting is an emerging technology to protect multimedia from unauthorized redistribution. It embeds a unique ID into each user's copy, which can be extracted to help identify culprits when an unauthorized leak is found. Thereby any emerging illegitimate copy can be traced back to the guilty party. A major challenge is to make this system secure against coalitions of pirates.

Project Leader(s): 

Postdoctoral fellow: Dr. Paul Nguyen, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto
Lead faculty member: Dr. Patrick Brown, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto

This project aims to develop methods and software for performing spatio-temporal analysis of cancer incidence and smoking data in Ontario over long time periods with high spatial resolution. This will allow changes of cancer incidence over time to be better understood, and accommodate rare cancers that require long study periods in order to accumulate data. Because of small counts common to small area analysis, computationally intensive Bayesian inference methods will be needed.

Project Leader(s): 

Postdoctoral fellow: Dr. Taraneh Abarin, Public Health Sciences, University of Toronto

Lead faculty member: Dr. Laurent Briollais, Public Health Sciences, University of Toronto

Using modern statistical measurement error methodologies and analysis, we aim to efficiently and accurately discover and characterize predictive models of responses associated with abnormal growth development in young children and adults. This proposal is unique in scope and vision by addressing health issues that threaten the sustainability of the health care system.

Project Leader(s): 

Postdoctoral fellow: Dr. Babak Taati, Department of Occupational Science and Occupational Therapy, University of Toronto

Lead faculty member: Dr. Alex Mihailidis, Department of Occupational Science and Occupational Therapy, University of Toronto

Each year, about 50,000 Canadians suffer from a stroke and 75% of them are left with a post-stroke disability or impairment. The economic costs of strokes are $3.6 billion a year. Our proposal involves developing an advanced rehabilitation device that helps post-stroke patients regain their mobility. Such patients often suffer from partial paralysis due to brain tissue damage during the stroke. While the physical brain damage could somewhat recover over time, the mobility problems often persist as a “learned paralysis” that settles during recovery.

Project Leader(s): 

Postdoctoral Fellow: Dr. Yildiz Yilmaz, Dalla Lana School of Public Health, University of Toronto

Lead faculty member: Dr. Shelley Bull, Dalla Lana School of Public Health, University of Toronto

The objective of the project is to develop, evaluate and apply informative statistical methods to the task of identifying novel genes/pathways involved in breast cancer recurrence. A model for time to cancer recurrence using clinical, pathological, and molecular measures in the setting of high-dimensional genome-wide genetic scans will be developed that allows for a proportion of the patients to be long-term survivors.

Project Leader(s): 

Dr. Steven Easterbrook, (University of Toronto)

Project team: 
Dr. Marsha Chechik, (University of Toronto)
Dr. Mehrdad Sabetzabeh, (University of Toronto)
Dr. Shiva Nejati, (University of Toronto)
Non-academic participants: 

Bell Canada University Labs, 
IBM Canada for Advanced Studies

Funding period: 
April 1, 2021 - March 31, 2021
Project Leader(s): 

Dr. Karan Singh , University of Toronto

Project team: 
Dr. Ravin Balakrishnan, University of Toronto
Dr. Eugene Fiume, University of Toronto
Dr. Pierre Poulin, Université de Montréal
Dr. Alla Sheffer, University of British Columbia
Dr. Michiel Van de Panne, University of British Columbia
Dr. Richard Zhang, Simon Fraser University
Funding period: 
April 1, 2021 - March 31, 2021

How quickly and effectively a designer can transform a mental concept into a digital object that is easy to refine and reuse is a central challenge in computer graphics. The focus of this project is, therefore, to develop new mathematical representations, or build upon existing ones, to capture the essence of shape as perceived by designers. In the past year, a freeware software program, Shapeshop, which was developed by the project team was released for download.