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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. Majid Jaberi-Douraki, Mathematics and Statistics, York University

Lead faculty member: Dr. Seyed Moghadas, Mathematics and Statistics, York University

A major pharmaceutical intervention for management of many infectious diseases is the use of antiviral drugs. However, the rise of drug resistance poses significant threats to the effectiveness of drugs. This research proposes to determine optimal treatment strategies, through the development of population dynamical models for disease transmission and control, which can minimize the effect of resistance emergence in the population. This work will primarily focus on influenza infection, which still inflicts substantial morbidity, mortality, and socioeconomic costs worldwide.

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): 

Postdoctoral fellow: Dr. Thomas Degris, Computing Sciences, University of Alberta

Lead faculty member: Dr. Richard Sutton, Computing Sciences, University of Alberta

Non-academic participants: 

Design, build, and program a small mobile robot at the University of Alberta that can interact successfully, without supervision, with members of the public visiting the Courage Center at the Glenrose Rehabilitation Hospital in Edmonton. Robotics is playing an increasing role in multiple aspects of rehabilitative medicine, including prosthetics, mobility aids, and patient-adapted physical therapy. The Courage Center is a new facility for demonstrating and showcasing such applications of technology in rehabilitative medicine to the public.

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. Ian Goldberg, University of Waterloo and Dr. Rei Safavi-Naini, University of Calgary

Project team: 
Dr. Reda Alhajj, University of Calgary
Dr. Ken Barker, University of Calgary
Dr. Urs Hengartner, University of Waterloo
Dr. Michael Jacobson, University of Calgary
Dr. Alfred Menezes, University of Waterloo
Dr. William Chad Saunders, University of Calgary
Dr. Douglas Stinson, University of Waterloo
Dr. Hugh Williams, University of Calgary
Dr. Carey Williamson, University of Calgary
Funding period: 
April 1, 2021 - March 31, 2021

In today’s highly connected world in which data is so easy to collect, search, and transfer, privacy is of increasing importance. Unfortunately, the way most communication happens today - particularly over the Internet - is quite privacy unfriendly. When you send email, use instant messaging, or simply browse the world-wide web, information about you and your actions gets disseminated to diverse parties around the world, and you have little, if any, control over it.

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