Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

29670 Completed Projects

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801
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663
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825
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8841
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95
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568
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1088
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Projects by Category

Enhanced Modelling of Exfiltration Events in Sun Life Cybersecurity Data

Theft or loss of sensitive data is a growing concern for companies who may suffer losses of consumer confidence, market valuation and intellectual property when large amounts of data are stolen. In this research project we will use an enhanced “screen and review” approach to combating exfiltration in a large data set of activity logs within a large corporate network. We will create realistic simulations of data theft events that can be used as a basis for machine learning, and for the design and prototyping of a system where human experts work with AI algorithms to detect and prevent data theft. We will also build visualization and browsing tools that make it easier for people to judge whether or not observed data access activity indicates malicious intent. Our goal will continue to be the development of a state-of-the-art system for monitoring and reporting possible exfiltration events as they happen.

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Faculty Supervisor:

Mark Chignell

Student:

Partner:

Sun Life Financial

Discipline:

Engineering

Sector:

Finance and Insurance; Artificial Intelligence; Technology

University:

University of Toronto

Program:

Accelerate

Supporting Canadian families: A national review of the F&ST program

Family Service Canada (FSC) is a Canadian nonprofit organization dedicated to building healthy families. One program delivered by FSC, called Family & Schools Together, has been shown to help families become more involved in their children’s education and support student’s learning but it has not yet been researched in Canada. To find out if this program is helpful for Canadian families, we will be interviewing FSC staff, families, children, and teachers across five FSC sites to determine whether or not they feel the F&ST program is effective. We will also research other parent programs that are similar to F&ST to determine if there is a program out there that may be a better fit for Canadian families. Overall, this project will inform FSC’s programming decisions to ensure that Canadian families are receiving the best possible support for their children.

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Faculty Supervisor:

Veronica Smith

Student:

Partner:

Family Service Canada

Discipline:

Sociology

Sector:

Public Service, Policy, and Governance; Education

University:

University of Alberta

Program:

Accelerate

Evaluating impacts of social web-based networks on travel sharing

The specific aim of this study is to examine the demand for a social-network based dynamic ridesharing system called FacePorter. The study will also be focused on the role that social networks can play in facilitating this ride-sharing Program. The University of Calgary population will be examined as potential users for such service. A combination of stated preference and revealed preference survey would be conducted to examine the willingness of the University population to use this system and the factors which would contribute to its success.

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Faculty Supervisor:

Lina Kattan

Student:

Partner:

Harbour Financial Inc

Discipline:

Engineering

Sector:

Finance and Insurance

University:

University of Calgary

Program:

Accelerate

Unsupervised Learning Based Approach for Insider Threat Analysis

Insider threat is one of the most damaging security threats to the safety of data, systems, and intellectual property of institutions. Typical threats caused by malicious insiders are trade secrets / intellectual property theft, disclosure of classified information, theft of personal information and system sabotage. Malicious actions of insider threats are performed by authorized personnel of organizations, which may be familiar with the organizational structure, valued properties, and security layers. Given that a malicious insider is authorized to access the organization’s systems and networks, other challenges appear in this detection problem as well. One of them is that data describing insider threat activities is typically rare and poorly documented. Thus, detecting and mitigating insider threats represent a major cybersecurity challenge to any organization. In summary, the challenges in insider threat detection include unbalanced data, limited ground truth, and possible user behaviour changes. This project aims to design an unsupervised learning-based approach for insider threat detection. Our goal is to employ unsupervised learning algorithms with different working principles, such as Autoencoder and Isolation Forest. Furthermore, we will explore various representations of data with temporal information and compare our approach to other work in the literature to analyze its effectiveness and generalizability.

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Faculty Supervisor:

Nur Zincir-Heywood

Student:

Partner:

Micro Focus Software (Canada) ULC

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

Dalhousie University

Program:

Accelerate

Examining the operation of Public Pools and Spas in the COVID-19 Era

The COVID-19 pandemic affected every aspect of our lives, and recreational water facilities were not immune to this with several questions and concerns about potential exposure to the virus at these facilities. This research project aims to understand experiences, needs, and attitudes towards the use of recreational water facilities, namely, public pools and spas during the COVID-19 pandemic. Three groups of interest that will be investigated are: 1) public pool and spa staff, 2) members of the public who regularly use recreational water facilities and 3) public health inspectors (PHIs) who conduct inspections at public pools and spas. The partner organization will utilize results to better understand the challenges and develop strategies to support the pool and spa operation.

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Faculty Supervisor:

Fatih Sekercioglu;Chun-Yip Hon

Student:

Partner:

Lowry and Associates

Discipline:

Life Sciences

Sector:

Wholesale trade

University:

Toronto Metropolitan University

Program:

Accelerate

Design and Implementation of Low-Noise, Wide-Bandwidth Transimpedance Amplifiers for High Speed Optical Receivers

Canadian Internet service providers, including Bell, Rogers, and TELUS are facing critical challenges to upgrade their access networks in order to support bandwidth intensive products and services. Fonex Data System Inc. is developing a novel optical receiver which is anticipated to outperform current receivers. The receiver will enable increased bandwidth at reduced costs for next generation access networks. The proposed internship project seeks to design and implement an important block of the receiver, that is a wide bandwidth and low noise transimpedance amplifier (TIA) based on the BiCMOS technology. The TIA has the major role on the performance of the receiver, providing low noise amplification of a current signal from a photodetector. The project will help the partner to develop its optical receiver which can deliver a solution to the Canadian service providers that meets both their capacity, and cost requirements.

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Faculty Supervisor:

Tarek Djerafi

Student:

Partner:

Fonex

Discipline:

Engineering

Sector:

Information and Communications Technology; Technology; Commercial Services

University:

Université du Québec : Institut national de la recherche scientifique

Program:

Accelerate

Design and fabrication of a power-efficient AI-Processor for Edge computing

This project will allow us to develop a microelectronic chip prototype of an energy-efficient AI processor. The AI processor exhibits a 1000 times reduction in power profile compared to standard cloud-based GPUs. Tasks that can be transferred from server GPUs to this solution and deploying our AI-Processor solution to EDGE can estimate substantial energy savings when evaluated over ten years under realistic assumptions. We estimate a net reduction of 83K tonnes of CO2 equivalent over ten years, helping Quebec significantly achieve its clean environment objectives. Economically, this will help Aarish Technologies to launch its product with a solid foundation of intellectual property and to grasp the demands of the mar

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Faculty Supervisor:

Mohammed Khalid

Student:

Partner:

Aarish Technologies

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

McGill University; University of Windsor

Program:

Accelerate

Development of Novel Aluminum Alloys and Metal Matrix Composites Strengthened with Rare Earth Elements and Nano Ceramic and Carbon Particles

This purpose of the proposed project is to comprehensively study the effects that nickel (Ni), iron (Fe), manganese (Mn) and nano-scale particles have on the microstructure and high temperature mechanical properties of aluminum-cerium (Al-Ce) based alloys. This research will use conventional sintering and casting processes to determine how varying the cooling rate during casting and material composition affects the microstructure and mechanical properties. For the first time, composite nano-sized particles will be introduced to the Al-Ce-Ni/Fe/Mn alloys and the resulting material will be examined thoroughly using state of the art microscopes and material testing and analyzing equipment. The new alloys will be subjected to a wide variety of mechanical tests at elevated temperatures (250-350°C). The development of a new temperature resistant Al alloy, with improved properties, will enable the transportation industry to reduce material consumption, improve operating efficiency of engines and reduce harmful green house gas emissions.

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Faculty Supervisor:

Dimitry Sediako

Student:

Partner:

Eck Industries

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

The University of British Columbia - Okanagan

Program:

Accelerate

Production of FDCA directly from glucose/fructose in a continuous-flow two-stage reactor system and study of reaction kinetics

2,5-furandicarboxylic acid (FDCA), as one of the most promising green chemicals, has found a variety of commercial applications, particularly in the synthesis of polyesters, polyamides, and plasticizers as well as adhesives and coatings. FDCA is commonly produced from pure 5-hydroxymethylfurfural (5-HMF) by selective oxidation. However, pure 5-HMF is by far very expensive, generated by catalytic dehydration of carbohydrates (sugars, starch or cellulose), in which the yield and selectivity are still low due to the formation of byproducts such as humins, hence posing a big challenge for commercial-scale production of FDCA. Alternatively, synthesis of FDCA directly from biomass or sugars through 5-HMF intermediate could be economically viable and sustainable. In this Mitacs Accelerate project, our existing continuous-flow biphasic catalytic reactor system (15g/h) for HMF synthesis will be modified to a two-stage continuous-flow process for production of FDCA directly from glucose/fructose and for study of reaction kinetics.

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Faculty Supervisor:

Charles Chunbao Xu

Student:

Partner:

Climicals

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

The University of Western Ontario

Program:

Accelerate

Optimisation de la réfection des groupes turbine-alternateurs dans une centrale hydroélectrique

Dans les centrales hydroélectriques, les groupes turbine-alternateurs sont réparés et installés selon un calendrier de travaux. Compte tenu de leur taille, d’autres pièces doivent être déplacées pour accéder aux pièces à démonter, réparer ou à installer. Afin de déterminer le plan d’aménagement des pièces, plusieurs contraintes doivent être respectées : 1) le calendrier des travaux, 2) l’espace disponible pour les pièces, 3) l’accessibilité aux pièces à réparer et à installer et 4) les normes de santé et sécurité au travail. De plus, les déplacements des pièces ainsi que l’encombrement dans la centrale doivent être minimisés. Actuellement, ce plan est conçu à tâtons et vérifié par un simulateur. Ce processus est long et exige souvent des déplacements d’autres pièces. L’objectif principal de ce projet consiste à proposer un outil d’aide à la décision automatique permettant de déterminer le plan d’aménagement des pièces en développant un logiciel d’optimisation de boîtes noires.

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Faculty Supervisor:

Sara Séguin;Marilène Cherkesly

Student:

Partner:

Hydro-Quebec

Discipline:

Computer science

Sector:

Energy and Utilities; Green/Alternative Energy

University:

Université du Québec à Chicoutimi

Program:

Accelerate

Harmonisation de données d’imagerie de diffusion par auto-encodage adversariel avec respect de contraintes anatomiques

L’acquisition de données d’imagerie de diffusion est suceptible à un important problème de variabilité à travers les différents sites d’acquisition (e.g. Sherbrooke vs. Montréal) et à travers les fabricants (e.g. Siemens vs Philips). Puisque ces données de diffusion ne sont pas invariantes aux protocoles et scanners utilisés, il s’agit d’un problème de taille pour les études cliniques qui désirent utiliser des données provenant de multiples sites d’acquisition. Les algorithmes d’apprentissage profonds semblent adaptés à ce type de problème et pourraient permettre de nouvelles avancées technologiques dans le domaine de l’harmonisation de données.

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Faculty Supervisor:

Maxime Descoteaux;Pierre-Marc Jodoin

Student:

Partner:

Imeka Solutions Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Université de Sherbrooke

Program:

Accelerate

Development of social and economic indicators for sustainable remediation

The proposed research will develop and test a sustainable remediation framework and set of proposed social and economic ind icators. The framework will build upon existing tools and complement current practices and regulations. The intern ‘s work is part of SRC’s two-year project is to provide a new niche service that will help SRC’s clients select the optimal remediation alternative. Objectives of the project are to deliver a technical report describing a framework, tools, methods and metrics to be used to support decision-making process to achieve sustainable remediation, and to test the framework and demonstrate expertise in this field through case studies. The additional understanding of social and economic indicators will allow SCR to initiate sustainable remediation for different industry resource sectors.

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Faculty Supervisor:

Bram Noble

Student:

Partner:

Saskatchewan Research Council

Discipline:

Earth science

Sector:

Mining; Professional, scientific and technical services

University:

University of Saskatchewan

Program:

Accelerate

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