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Computing

Project Leader(s): 

Postdoctoral fellow: Dr. Maurizio Ceseri, Mathematics, Simon Fraser University

Lead faculty member: Dr. John Stockie, Mathematics, Simon Fraser University

This project aims to investigate the physical and biological processes that initiate sap flow in maple trees during early spring when maple sap is harvested. Our study will be centered around developing a mathematical model that captures both sap flow and heat transport in the porous wood tissue, and then investigating solutions using a combination of analytical and numerical techniques.

Project Leader(s): 

Postdoctoral fellow: Dr. Rong Xiao, Computer Science, University of Western Ontario

Lead faculty member: Dr. Marc Moreno Maza, Computer Science, University of Western Ontario

Non-academic participants: 

The theoretical and practical aspects of manipulating mathematical expressions on computers are usually referred to as computer algebra or symbolic computation. In this field, calculations are designed to yield exact and complete results, by opposition to numerical analysis which is meant to handle approximate values, potentially producing incomplete results. Exactness and completeness have some significant computational overhead. Computer algebra software is highly demanding in CPU time and memory.

Project Leader(s): 

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

Non-academic participants: 

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.

Project Leader(s): 

Postdoctoral fellow: Dr. Carlton Davis, Computer and Software Engineering, Ecole Polytechnique de Montréal

Lead faculty member: Dr. Jose Fernandez, Computer and Software Engineering, Ecole Polytechnique de Montréal

Botnets are networks consisting of computers that are infected with malicious codes (malware) and are consequently being remotely controlled by botnet operators. Botnets pose some of the most challenging security problems owing to their ubiquitousness, their size, their complexity, and the effectiveness with which they have been used to facilitate and perpetuate a wide range of cybercrimes.

Project Leader(s): 

Dr. John McHugh, Dalhousie University

Project team: 
Dr. William A. Aiello, University of British Columbia
Dr. José Fernandez, Simon Fraser University
Dr. Sudhakar Ganti, University of Victoria
Dr. Michael McAllister, Dalhousie Unversity
Dr. Michael L. McGuire, University of Victoria
Dr. Stephen Neville, University of Victoria
Dr. Alejandro Quintero, École Polytechnique de Montréal
Dr. Jean-Marc Robert, École de technologie superieure
Dr. Nur Zincir-Heywood, Dalhousie University
Non-academic participants: 
Funding period: 
April 1, 2021 - August 30, 2021
Project Leader(s): 

Dr. George Karakostas , (McMaster University)

Project team: 
Dr. Adrian Vetta (McGill University)
Dr. James A. Dimarogonas (MITRE Corporation)
Dr. F. Bruce Shepherd (Bell Laboratories)
Dr. Gordon Wilfong (Bell Laboratories)
Dr. Uyen Trang Nguyen (York University)
Non-academic participants: 
Funding period: 
October 1, 2021 - March 31, 2021

 
Game Theory studies the phenomena occurring when independent, autonomous entities, called agents or users, act selfishly; game theoretic techniques are now being used to model and analyze networks. This project aims to develop a more realistic modelling of communication and data networks of selfish users using game-theoretic models, study the effects that selfish behaviour has on the overall network performance, and the designs of networks which prevent the rapid degradation of the performance due to such behaviour.