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Health

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. Zhen Gao, Mechanical Engineering, University of Ontario Institute of Technology

Lead faculty member: Dr. Dan Zhang, Mechanical Engineering, University of Ontario Institute of Technology

This research develops a comprehensive methodology for the integrated optimization and control of human-friendly robotic technology that will be applied for the advanced healthcare and biomedical manipulation. Some original ideas, methods and algorithms are proposed in this research based on several novel mathematical models, which will benefit the development of general robotics in the direction of safety with high performance to human beings.

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. Xiteng Liu, Mathematics and Statistics, York University

Lead faculty member: Dr. Hongmei Zhu, Mathematics and Statistics, York University

Non-academic participants: 

Magnetic Resonance Imaging (MRI) is an important medical imaging technology for clinical diagnostics. However, its slowness in data acquisition poses major problems in practice. In recent years, many research efforts to accelerate MRI data acquisition were based on the compressed sensing (CS) theory. CS is effective for signals that have highly sparse representations. However, it suffers from high computational complexity and lack of performance stability.

Project Leader(s): 

Dr. Anthony Vannelli, University of Guelph & Dr. Miguel F, AnjosEcole Polytechnique

Project team: 
Dr. Abdo Youssef Alfakih, University of Windsor
Dr. Kankar Bhattacharya, University of Waterloo
Dr. Claudio A. Canizares, University of Waterloo
Dr. Richard J. Caron, University of Windsor
Dr. Thomas Coleman, University of Waterloo
Dr. Tim N. Davidson, McMaster University
Dr. Antoine Deza, McMaster University
Dr. Samir Elhedhli, University of Waterloo
Dr. David Fuller, University of Waterloo
Dr. Elizabeth Jewkes, University of Waterloo
Dr. Paul McNicholas, University of Guelph
Dr. Chitra Rangan, University of Windsor
Dr. Tamás Terlaky, Lehigh University
Dr. Stephen Vavasis, University of Waterloo
Dr. Henry Wolkowicz, University of Waterloo
Dr. Guoqing Zhang, University of Windsor
Funding period: 
April 1, 2021 - March 31, 2021

Due to the explosive growth in the technology for manufacturing integrated circuits, modern chips contain millions of transistors. Using sophisticated optimization algorithms, it is possible to achieve notable increases in the performance of the chips, reduce the manufacturing costs, and produce faster, cheaper computing for society. Thus, the objective of this project is to enhance the solution of large-scale optimization problems arising in these applications.

Project Leader(s): 

Dr. Hermann Eberl, University of Guelph and Dr. John Stockie, Simon Fraser University

Project team: 
Dr. John R Dutcher, University of Guelph
Dr. Ian Frigaard, University of British Columbia
Dr. Nilima Nigam, Simon Fraser University
Dr. David Pink, St. Francis Xavier University
Dr. Gideon Wolfaardt, Ryerson University
Funding period: 
October 1, 2021 - March 31, 2021

Bacterial biofilms are microbial depositions on immersed surfaces and are ubiquitous in natural and engineered environments. For example, they play a significant role in medical applications where they can grow on artificial implants and cause infections; they form dental plaques and contribute to tooth decay; they can be utilized to assist in clean-up of contaminated soils or groundwater aquifers; they accelerate corrosion of metal surfaces; and they are a main culprit behind contamination of drinking water systems and food processing equipment.

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. Martin Puterman , University of British Columbia

Project team: 
Dr. Dionne Aleman, University of Toronto
Dr. Derek Atkins, University of British Columbia
Dr. John Blake, Dalhousie University
Dr. Michael Carter, University of Toronto
Dr. Armann Ingolfsson, University of Alberta
Dr. Bora Kolfal, University of Alberta
Dr. Wojtek Michalowski, University of Ottawa
Dr. Jonathan Patrick, University of Ottawa
Dr. Maurice Queyranne, University of British Columbia
Pablo Santibáñez, BC Cancer Agency
Dr. Steven Shechter, University of British Columbia
Dr. Vedat Verter, McGill University
Dr. Greg Zaric, University of Western Ontario
Funding period: 
October 1, 2021 - March 31, 2021
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Project Leader(s): 

Dr. Daniel Coombs, University of British Columbia

Project team: 
Dr. Christopher Cairo, University of Alberta
Dr. Eric Cytrynbaum, University of British Columbia
Dr. Leah Keshet, University of British Columbia
Dr. Michael C. Mackey, McGill University
Dr. Bruce Verchere, Child and Family Institute of BC
Dr. Gerda de Vries, University of Alberta
Non-academic participants: 
Funding period: 
February 25, 2022 - March 31, 2021

Diseases such as diabetes, Alzheimer's, HIV and blood disorders present challenges to our society, our healthcare and our basic scientific understanding of physiological processes within the human body. Mathematical modelling can be used to help scientists decipher the processes at work in these complex diseases at a molecular, cellular and organ level. Recently, research team members examined the ways in which drugs such as Filgrastim could be used to replenish levels of white blood cells, a common challenge following chemotherapy.

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Project Leader(s): 

Dr. Fahima Nekka, Université de Montréal

Project team: 
Dr. Jun Li, Universite de Montreal
Dr. Catherine Litalien, Universite de Montreal
Dr. Anne-Laure Lepeyraque, Universite de Montreal
Dr. Pascal Girard, Merck Serono S.A.
Non-academic participants: 
Funding period: 
October 1, 2021 - March 31, 2021

When patients do not use medications as prescribed, the drugs may lose the ability to treat the disease. However, the impact of variations in patient use is not generally studied during clinical trials. By identifying the reasons for patient non-compliance and individual patient modifications, the team will determine the impact that poor compliance or dosing regimen adjustments have on therapeutic failure. A quantitative analysis of this impact will be developed. Initially, the team will focus on oral chemotherapy where concerns about compliance have become an important issue.

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