Postdoctoral fellow: Dr. Mathieu Sinn, David R. Cheriton School of Computer Science, University of Waterloo
Lead faculty member: Dr. Pascal Poupart, David R. Cheriton School of Computer Science, University of Waterloo
We will develop algorithms to automatically generate descriptive labels for large collections of web documents. Such labels can be used by companies in order to decide on which web sites they want to place advertisements, or by electronic publishers to categorize media offers. Currently, there doesn't exist any approach that can robustly and automatically label clusters of documents with a level of quality that approaches human labellers.
Advanced Mathematical Modeling and Parallel Simulation Algorithms for Analysis and Design of Electrical Power Systems and Smart Grid Technologies
Postdoctoral fellow: Dr. Natalie Nakhla, Electronics, Carleton University
Lead faculty member: Dr. Q. J. Zhang, Electronics, Carleton University
With today’s rapidly increasing energy demands and the emergence of smart grids and renewable energy resources, the current energy and power technologies need to be advanced to keep up with these changes. Simulation and modeling plays a vital role in understanding, designing and planning of electrical power systems. The proposed research aims at developing a new generation of advanced mathematical models and simulation tools for electrical power systems and smart grids.
Developing a Mathematical Model for Coherent Anti-Stokes Raman Scattering Imaging of Biological Processes in Living Cells
Postdoctoral fellow: Dr. Konstantin Popov, Physics, University of Ottawa
Lead faculty member: Dr. Lora Ramunno, Physics, University of Ottawa
Coherent Anti-Stokes Raman Scattering (CARS) microscopy is a very promising method of directly imaging biological processes occurring in living cells. It is unique because the imaging does not harm the cell, is molecule specific, and does not require the introduction of additional chemicals that may alter the biology. For example, CARS would allow us to visualize how viruses invade a cell membrane, which is still a mystery.
Several New Mathematical Models for the Integrated Optimization and Control of Human-Friendly Parallel Robots for Advanced Healthcare and Biomedical Manipulation
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.
Modelling Growth Charts with Measurement Error: A Modern Perspective of Prediction of Abnormal Growth Responses in Young Children and Adults
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.
Dr. François Anctil, Université Laval
The goal of this project is to evaluate if mesoscale (35 km) meteorological ensemble forecasts coupled to a short-range hydrological forecasting system can lead to improved forecasts, and thus help maximize hydropower production and minimize flood risks. Positive results would pave the way for a full project which would aim to design an efficient short-range hydrological ensemble forecasting system adapted to the climate and hydrology of the Great-Lakes and Saint Lawrence River basin.
Dr. Tom Salisbury, York University
With many baby-boomers entering retirement in North America, and with the increasing size of the aging population worldwide due to economic and social development, managing retirement income becomes an important question for the finance and insurance industry as well as for individuals. At the same time, corporations are stepping away from the standard “pensions" they have traditionally offered employees. As a result, individuals are responsible more often for managing the risks associated with securing their retirement income.
Dr. Steven Easterbrook, (University of Toronto)
Bell Canada University Labs,
IBM Canada for Advanced Studies
Dr. Holger H. Hoos , University of British Columbia
Dr. Kim McAuley, Queen's University
Engineers use mathematical models to describe the production of plastics and other chemicals. The models contain unknown parameters that are estimated from plant data. In the past year, the research team analyzed several criteria that modelers use to decide how complex or how simplified their models should be. They showed that one popular model-selection criterion, the corrected Akaike Information Criterion, tends to select very simple models, and that another, the adjusted coefficient of determination, tends to select models with many parameters.