Innovative Projects Realized

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

30508 Completed Projects

2882
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5105
BC
825
MB
681
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860
SK
9051
ON
9491
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97
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586
NB
1141
NS

Projects by Category

Exploring factors that influence avian diversity and community composition in Detroit, MI. and potential synergies with the health and wellbeing of neighbourhood residents.

A collaboration between health geographers from Michigan State University and ornithologists from Carleton University, this proposed research project will investigate the factors influencing avian diversity and community composition in Detroit, MI. and the potential relationship between human health and access to biodiversity and nature. The results of this research project will lead to several high-quality manuscripts that will inform sustainable urban land-use policies that benefit people and wildlife. Being transdisciplinary, this research project will address complex socio-ecological issues facing cities globally, but is uniquely positioned to answer questions pertinent to post-industrial cities like Detroit. Of interest is the potential role of vacant lands in promoting bird diversity in urban spaces, and exploring the social implications of these spaces for neighbourhood residents in light of their conservation potential. A continuation of an already strong and long-standing collaboration, this proposed research will strengthen knowledge of urban bird ecology, and the potential synergies between urban conservation and the enhancement of human well-being in cities.

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Faculty Supervisor:

Rachel Buxton

Student:

Partner:

Michigan State University

Discipline:

Life Sciences

Sector:

Sustainability & the Environment; Health and Related Sciences & Technology; Social Innovation

University:

Carleton University

Program:

Globalink Research Award

Modèle de prévision dynamique du comportement des renouvellements de polices d’assurance

Le département de Prévision et Analytique de TD Assurance est actuellement en charge de prédire les ventes et les revenues des différents produits d’assurance sur une base annuelle et mensuelle. Prédire les revenues, et ceci de manière précise, est crucial pour l’entreprise et son bon fonctionnement. Les modèles jusqu’alors utilisés ont étés construits il y a un peu plus de dix ans et ont été implémentés avec le logiciel Excel. Ces modèles sont complexes et requièrent trop de manipulations manuelles, engendrant non seulement des erreurs potentielles mais également une perte de temps. Le but du présent projet est de développer de nouveaux modèles, tout aussi performant, sinon plus, de les automatiser et de les dynamiser, notamment grâce au logiciel SAS. Nous nous concentrons sur les modèles de renouvellements et d’annulation de polices d’assurance afin de généraliser le phénomène à l’ensemble des produits d’assurance. Ces deux modèles sont dynamiques car directement liés l’un à l’autre. L’utilisation de séries chronologiques est ici requise pour construire les dits modèles.

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Faculty Supervisor:

Pierre Duchesne

Student:

Partner:

TD Assurance

Discipline:

Mathematics

Sector:

Finance and Insurance

University:

Université de Montréal

Program:

Accelerate

Dynamic Trust Modeling in Federated Learning Through Balancing Utility and Privacy

The surge in data-intensive machine learning (ML) applications necessitates effective incentives for data owners (DOs) to contribute data and train ML models collaboratively. The decision to participate in collaboration depends on the balance between utility gains and privacy loss. This project focuses on federated learning (FL), where DOs participate in collaborative learning without sharing raw data. While FL preserves privacy to some extent, vulnerabilities exist in preserving data privacy through shared models. Existing literature proposes privacy guarantees but lacks a clear method to measure the utility gain of each participant. The project aims to study participants’ contributions to collaborative learning and determine compensation based on different privacy levels. The project then investigates the utility gain of each participant. In practice, FL often faces data heterogeneity, resulting in different privacy needs. This can prompt DOs to exit at different times, managing privacy budgets according to their gained utility. Exits can deplete the data pool, impoverishing model quality and potentially triggering a cascade effect. Conversely, rapid disengagement by some participants may inspire others to contribute more data, aiding joint training for a personalized model. The project explores these dynamic utility-privacy trade-offs, analyzing participants’ evolving trust in the FL procedure.

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Faculty Supervisor:

Stark C. Draper

Student:

Partner:

CISPA

Discipline:

Engineering

Sector:

Artificial Intelligence; Information and Communications Technology

University:

University of Toronto

Program:

Globalink Research Award

Deep Learning for Automation of 3D Pore Analysis in Micro-CT Tomographs

This research proposal focuses on addressing the prevalent challenges associated with Proton Exchange Membrane Fuel Cells (PEMFCs), specifically targeting the reduction of greenhouse gas emissions. Despite significant advancements in performance and durability, particularly in automotive contexts, the high cost associated with essential materials for optimal functionality remains a formidable barrier. Notably, advancements in cathode gas diffusion layer (GDL) water management have enhanced performance metrics and subsequently mitigated costs. However, a detailed understanding of microscale pores and liquid water dynamics is crucial for further innovation. Current image processing methods for bubble analysis within GDLs are time-consuming, potentially biased, and limited in their capacity for complex analyses. This project proposes the integration of artificial intelligence (AI) to automate image analysis processes, aiming to increase precision, reduce bias, and expedite research timelines. By combining experimental insights with advanced image analysis techniques, this initiative strives to develop a comprehensive tool for characterizing and understanding the intricate phenomena occurring within PEMFCs. Collaborative efforts between theoretical and experimental research groups will facilitate the necessary data collection, development, and validation of this innovative tool, ultimately contributing to the advancement of PEMFC technology and its commercial application.

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Faculty Supervisor:

Aimy Bazylak

Student:

Partner:

Rheinisch-Westfälische Technische Hochschule Aachen

Discipline:

Computer science

Sector:

Clean Technology; Environmental Science and Technology; Green/Alternative Energy

University:

University of Toronto

Program:

Globalink Research Award

Genetic toolbox to understand ovule development

How complex organs develop from a small set of undifferentiated cells is a fundamental question in biology. Genetic mutations that alter organs shape give us important insight to answer this question. This project aims to use CRISPR/CAS9 technology to introduce different types of genetic constructions into the model plant Arabidopsis thaliana to understand the development of its ovules. The ovule is particularly important since it’s at the origin of the seeds, which constitutes most of human and animal sources of food, and the development of the correct shape is directly related to fertility, and thus plant productivity. This genetic toolbox will allow us to analyse the regulation of ovule development, linking gene expression, hormone flow and biomechanical growth in the different tissues. It will also deliver the capacity to manipulate the ovule growth, opening the possibility to increase its size, which could be of interest to the agricultural industry.

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Faculty Supervisor:

Daniel Kierzkowski

Student:

Partner:

Indiana University Bloomington

Discipline:

Life Sciences

Sector:

Agriculture and Food; Biotechnology; Life Sciences (not health)

University:

Université de Montréal

Program:

Globalink Research Award

Valorisation de données en viabilité hivernale (Interfaces graphiques et optimisation)

Le problème d’entretien hivernal des routes constitue un domaine de recherche crucial, où les chercheurs ont cherché à élaborer des stratégies novatrices pour gérer
efficacement les ressources tout en garantissant un service de qualité. Les variations climatiques, les quantités variables de neige et les contraintes logistiques
font de ce problème un terrain propice à l’application d’algorithmes d’optimisation. Ce projet, qui est une collaboration avec la ville de Rouyn-Noranda, vise à améliorer les opérations de déneigement des trottoirs afin d’augmenter la qualité de service tout en développant d’interfaces graphiques pour visualiser les opérations de déneigement des trottoirs en temps réel.

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Faculty Supervisor:

Chahid Ahabchane

Student:

Partner:

École nationale des sciences de l'informatique

Discipline:

Computer science

Sector:

Education

University:

Université du Québec en Abitibi-Témiscamingue

Program:

Globalink Research Award

Strategic B2B Marketing of AI/ML and other Software Solutions

Chartd is a Canadian software company from Ottawa that builds easy-to-use, cutting-edge data management solutions, emphasizing user experience, simplicity, and accuracy. Our mission is to provide our clients with user-friendly decision-making tools and automate business workflows. We are seeking a talented Marketing Intern to join our dynamic team and play a crucial role in our business software and AI/NLP projects. This internship offers an exciting opportunity for hands-on experience in various aspects of marketing (content creation, analytics, strategy), with a focus on digital marketing. The marketing intern will play a crucial role in supporting our marketing efforts and gaining valuable insights into the B2B software industry.

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Faculty Supervisor:

Linying Dong

Student:

Partner:

Chartd

Discipline:

Business

Sector:

Professional, scientific and technical services

University:

Toronto Metropolitan University

Program:

Business Strategy Internship

Education Technology Developer

Botree, a future-thinking learning and development company, is taking a significant step forward by introducing an AI-powered application to revolutionize instructional design. This project aims to update traditional training models, making them more effective for the digital-first workforce. By incorporating advanced learning theories and leveraging AI, Botree’s new application will transform research and existing content into interactive, structured learning modules. This will not only improve knowledge retention and practical application for learners but also allow Botree to scale its services efficiently. The project promises to benefit partner organizations by providing more adaptable, relevant, and effective training solutions tailored to the demands of the future workforce. The student intern will provide support in the design, testing and roll-out of this new technology by working with an AI development team and Botree to facilitate this project.

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Faculty Supervisor:

Temitope Oriola

Student:

Partner:

Botree

Discipline:

Business

Sector:

Education

University:

University of Alberta

Program:

Business Strategy Internship

Expérimentation d’affaires pour la gestion de la capacité de la SAT

La SAT est actuellement en réorientation stratégique. En effet, la SAT cherche à mettre en place une nouvelle offre de services. Pour opérationnaliser cette offre, le projet est de faire de l’expérimentation d’affaires, c’est-à-dire des expériences au sein de l’entreprise dans des environnements contrôlés, pour travailler la gestion de la capacité afin de garantir que les ressources de la SAT sont suffisantes et que leur gestion est optimale pour assurer la mise en place de ces nouveaux services. Le projet a pour objectif de faire ressortir des recommendations et des meilleures pratiques en gestion de la capacité pour la SAT.

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Faculty Supervisor:

Mickaël Gardoni

Student:

Partner:

Société des Arts Technologiques

Discipline:

Business

Sector:

Arts, entertainment and recreation

University:

École de technologie supérieure

Program:

Business Strategy Internship

Real-time Reinforcement Cage Quality Monitoring in Construction of Concrete Structures

This research will provide a real-time reinforcement cage quality monitoring framework for the construction of reinforced concrete structures, which is expected to improve the production quality of reinforced concrete products and reduce the workload of construction workers in the foreseeable future. Specifically, this research will (1) provide a rebar cage dimension measurement method based on cameras, freeing human labor from the laborious task of measuring the dimension of reinforcement cages by hand; (2) develop a new rebar cage inspection application, which can instruct workers to assemble rebar cage properly and generate rebar cage quality inspection reports automatically; (3) reveal the major challenges in the automated quality monitoring of rebar cages and show the promising directions for subsequent research; (4) present high-quality papers to improve the academic visibility of participating institutions.

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Faculty Supervisor:

Yi Shao

Student:

Partner:

Princeton University

Discipline:

Engineering

Sector:

Construction and infrastructure

University:

McGill University

Program:

Globalink Research Award

Power Quality Improvement at Sunnybrook Health Sciences Center

Sunnybrook Health Sciences Centre, a major hospital and medical research facility in Toronto, is fed from a portion of the electrical grid that is subject to numerous short power dips. These dips can cause significant issues within the hospital. A newly installed generator was found to not only produce electrical power but also help support the incoming voltage during those dips and mitigate some of the adverse effects. Research is required to gather data from specific electrical points of Sunnybrook’s power distribution system and analyse that data to create a software model of the generator’s control system. This model can then be used to create operating scenarios that optimize the generator’s ability to minimize those adverse effects and prepare for physical tests to confirm the projections.

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Faculty Supervisor:

Vijay Sood;Langis Roy

Student:

Partner:

Sunnybrook Health Sciences Centre

Discipline:

Engineering

Sector:

Clean Technology; Energy and Utilities; Sustainability & the Environment

University:

University of Ontario Institute of Technology

Program:

Accelerate

Kaili Jackson – Arbi

ARBI (Association for the Rehabilitation of the Brain Injured) is a non-profit association in Calgary which has been recognized for over 40 years as a pioneer in community-based brain injury rehabilitation. It is unique in Canada for the combination of professional and volunteer services for long-term neurorehabilitation that addresses both the physical and emotional impacts of acquired brain injury, as well as support for the family and making connections back to the community.
?The intern’s contributions to the development of educational materials for onboarding new staff and volunteers, and training in our neurorehabilitation program presents a multifaceted advantage for our organization. It also harnesses the fresh perspectives and innovative ideas of the intern will inject new knowledge, energy, and creativity into our educational materials, enriching their content and enhancing their effectiveness.

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Faculty Supervisor:

Ari Pandes

Student:

Partner:

Arbi

Discipline:

Business

Sector:

Health and Related Sciences & Technology

University:

University of Calgary

Program:

Business Strategy Internship