Innovative Projects Realized

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

30156 Completed Projects

2861
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5059
BC
812
MB
673
NL
842
SK
8957
ON
9368
QC
96
PE
579
NB
1120
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Projects by Category

Participatory Mapping for Assessing Social Cumulative Effects of Extractive Industries in Rio de Janeiro, Brazil

This project will explore how extractive industries, such as offshore oil and gas, have affected the Maria Joaquina Quilombola community in Rio de Janeiro, Brazil. Using participatory methods, such as community workshops and mapping, the study will document how the community has experienced social cumulative effects. The project seeks to enhance understanding and evaluation of these impacts on Quilombo communities, with the goal of improving assessment, monitoring, and mitigation strategies. More broadly, the study addresses the persistent neglect of social and cumulative impacts and offers a case study to inform best practices in impact assessment. Collaboration between Concordia University and the State University of Rio de Janeiro (UERJ) will strengthen research partnerships between Canada and Brazil, facilitate knowledge exchange on participatory assessment methods, and support future academic collaborations.

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Faculty Supervisor:

Sebastien Caquard

Student:

Partner:

Universidade do Estado do Rio de Janeiro

Discipline:

Sociology

Sector:

Education

University:

Concordia University

Program:

Globalink Research Award

Check Fraud Network Detection Using Graph Neural Networks (GNNs)

(1) Partner Activities: Nasdaq Verafin is a global leader in financial crime management, providing advanced fraud detection and anti-money laundering solutions to financial institutions. The company processes millions of transactions daily, including check-based payments, to identify suspicious patterns and prevent financial crimes.
(2) Challenges: A critical challenge in check fraud detection is identifying sophisticated fraud rings that operate across multiple accounts and institutions. Traditional rule-based systems analyze transactions in isolation, missing network-level patterns where fraudsters use stolen or counterfeit checks systematically. Single-transaction analysis results in high false positive rates and fails to detect coordinated fraud schemes involving altered payees, check washing, and organized fraud rings.
(3) Anticipated Benefits: This GNN-based approach will provide Nasdaq Verafin with a powerful network-aware fraud detection capability, enabling identification of fraud rings and coordinated attacks that conventional methods miss. By analyzing checks within their relational context—incorporating image similarity, account relationships, and transactional patterns—the system will significantly reduce false positives while improving detection of organized fraud schemes. This innovation will enhance Verafin’s competitive advantage, strengthen its fraud prevention platform, and provide clients with more sophisticated protection against emerging check fraud tactics, ultimately reducing financial losses across the banking industry.

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Faculty Supervisor:

Terrence Tricco

Student:

Partner:

NASDAQ Canada Inc

Discipline:

Computer science

Sector:

Finance and Insurance; Information and cultural industries

University:

Memorial University of Newfoundland

Program:

Accelerate

Intelligent OCR Routing System for Cheque Processing

(1) Partner Activities: Nasdaq Verafin is an industry leader in developing advanced anti-financial crime solutions, helping financial institutions worldwide detect and prevent fraud and money laundering through its sophisticated data analysis platform.
(2) Challenges: The primary challenges this project addresses are the significant operational cost associated with processing millions of cheque images for fraud analysis. Relying exclusively on premium, paid OCR services is expensive and not scalable. The previous project successfully created a system to mitigate this, and the challenge now is to evolve that system into a more intelligent and granular solution to maximize efficiency.
(3) Anticipated Benefits: The economic benefits for Nasdaq Verafin are direct and substantial. The initial research established a baseline demonstrating significant cost reductions in OCR processing by intelligently routing a large portion of images to open-source engines. This continuation project will deliver even greater savings by developing a more granular, field-specific routing system and a dynamic, machine learning-powered feedback loop for continuous optimization. This innovation will not only lead to further direct cost savings but also improve the scalability and efficiency of Nasdaq Verafin’s platform, strengthening its competitive advantage by making core services more technologically advanced and cost-effective.

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Faculty Supervisor:

Terrence Tricco

Student:

Partner:

NASDAQ Canada Inc

Discipline:

Computer science

Sector:

Finance and Insurance; Information and cultural industries

University:

Memorial University of Newfoundland

Program:

Accelerate

Réseaux de neurones graphiques pour le routage d’énergie dans les réseaux électriques intelligents

This project aims to make power grids smarter and more efficient by using a type of artificial intelligence called Graph Neural Networks along with Deep Reinforcement Learning. Just like a GPS finds the best route for a car, our system will find the optimal paths for electricity to travel, especially from clean but unpredictable sources like solar and wind. This will help reduce energy waste, lower costs, and make the power supply more reliable for everyone. For the participating institutions, this collaboration creates a powerful link between Canadian and Algerian researchers, combining their expertise to produce cutting-edge research, train highly skilled students, and strengthen their global reputation as leaders in artificial intelligence and sustainable energy technology.

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Faculty Supervisor:

Khadidja Henni

Student:

Partner:

École nationale supérieure d'informatique

Discipline:

Computer science

Sector:

Sustainability and the Environment; Energy and Utilities; Green/Alternative Energy

University:

Université TÉLUQ

Program:

Globalink Research Award

Partage des voies cyclables : défis et solutions pour une mobilité inclusive

Ce projet vise à mieux comprendre comment différentes personnes cohabitent sur et autour des voies cyclables : cyclistes, piétons, personnes en fauteuil roulant ou utilisant une aide à la mobilité, personnes aveugles ou malvoyantes, et utilisateurs de trottinettes. Avec la popularité croissante du vélo et de la mobilité active, ces espaces deviennent des lieux où se rencontrent des besoins, des vitesses et des vulnérabilités variés. Cela peut créer des situations d’inconfort ou d’insécurité, par exemple aux intersections, aux arrêts d’autobus ou dans les zones partagées. Pour éclairer ces enjeux, le projet réalisera une revue des connaissances existantes : quelles difficultés sont vécues par les usagers? Quelles solutions ont déjà été mises en place ailleurs, que ce soit dans l’aménagement, la signalisation, la réglementation ou la sensibilisation? Les résultats permettront à la Ville de Québec et au Regroupement des organismes de personnes handicapées de la Capitale-Nationale de mieux adapter les infrastructures cyclables pour qu’elles soient sécuritaires, accessibles et inclusives. Ultimement, ce projet contribue à promouvoir une mobilité durable qui tient compte de toutes et tous.

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Faculty Supervisor:

François Routhier

Student:

Partner:

Ville de Québec

Discipline:

Sociology

Sector:

Administrative and support, waste management and remediation services; Public administration; Utilities

University:

Université Laval

Program:

Accelerate

Measurements using a setup to demonstrate the decoy-state approach.

The internship project, performed in collaboration with a theorist group at the University of Calgary, will demonstrate the decoy-state approach to analyze simple – but non-trivial – circuits with 2-3 inputs and outputs utilizing bulk photonics components. The intern will assist the team with building a setup and perform the measurements needed for the analysis. This work will involve the use of fast electronics (arbitrary waveform generators, amplifiers, time-taggers), optical/phtonic components (optical fibers, power meters, phase- and intensity modulators, couplers), single-photon detectors, and coincidence analysis tools. The intern may also be involved in the decoy state analysis depending on time and progress

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Faculty Supervisor:

Daniel Oblak

Student:

Partner:

Université Paris Cité

Discipline:

Physics

Sector:

Education

University:

University of Calgary

Program:

Globalink Research Award

Récupération des minéraux critiques et stratégiques (MCS) à partir des résidus miniers et du drainage minier de sites abandonnés au Québec

La gestion responsable des rejets solides et liquides représente un enjeu majeur pour l’industrie minière. Ce projet vise à développer des solutions innovantes pour le traitement des eaux minières contaminées, en mettant l’accent sur la récupération des minéraux critiques et stratégiques (MCS) tels que le cuivre et le zinc. Ce projet de recherche s’articule autour: i) du développement et de l’optimisation de procédés de récupération des MCS à partir des eaux minières; et ii) de la valorisation des résidus de post traitement, afin de les transformer en ressources secondaires pour des applications industrielles.
La méthodologie s’appuie sur la collecte et la caractérisation physico chimique des eaux minières contaminées suivies d’essais expérimentaux en laboratoire pour évaluer les performances des procédés de récupération sélective (i.e., précipitation (bio )chimique sélective, sorption). Les retombées attendues de ce projet de stage sont : l’identification du potentiel en MCS présents dans les eaux minières provenant de parcs à résidus miniers non restaurés ; l’identification des procédés et conditions opératoires favorables à la valorisation sélective des MCS présents dans les eaux minières ; la diminution des impacts environnementaux liés à la valorisation de ces MCS.

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Faculty Supervisor:

Mehrez Hermassi

Student:

Partner:

Université de Lorraine

Discipline:

Earth science

Sector:

Education

University:

Université du Québec en Abitibi-Témiscamingue

Program:

Globalink Research Award

Intelligence Artificielle multimodale pour la classification précise, le sexage et l’évaluation de l’hybridation des poissons afin de retracer leur lignée parentale, soutenir leur préservation et contribuer à la taxonomie moderne

Le projet de recherche proposé vise à développer un système basé sur l’Intelligence Artificielle multimodale pour analyser à la fois les images morphologiques et les données génétiques de poissons appartenant aux espèces Diaphanus et Heteroclitus. L’objectif est de permettre l’identification automatique des espèces, de déterminer le sexe des individus et d’évaluer le degré d’hybridation afin de retracer leur lignée parentale. Ce système permettra une classification plus précise des poissons, y compris ceux difficiles à distinguer visuellement, et contribuera à mieux comprendre leurs relations évolutives. Les avantages attendus sont multiples : améliorer la surveillance et la préservation des populations de poissons, soutenir la conservation de la biodiversité aquatique, fournir des outils scientifiques pour la taxonomie moderne, et proposer une approche technologique innovante combinant vision par ordinateur, intelligence artificielle et bioinformatique.

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Faculty Supervisor:

Eric Hervet;Anne-Marie Dion-Côté

Student:

Partner:

École Nationale Supérieure d'Ingénieurs de Tunis

Discipline:

Computer science

Sector:

Artificial Intelligence; Biotechnology; Natural Resources

University:

Université de Moncton

Program:

Globalink Research Award

L2M – MSK Tissue Preservation Portable System – Regenerative Medicine

Elev8 is working with L2M to help launch there MSK therapeutic device for tissue regeneration and longevity in the sport, military, and aging tech space.

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Faculty Supervisor:

Judi Laprade;John Tran

Student:

Partner:

DMZ Ventures Inc

Discipline:

Physics

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Business Strategy Internship

Enabling Computer Supported Collaborative Learning (CSCL) Assistant to Access ChatbotLLM Service for Engaging in the Group Discussion with Students

A web system, Computer Supported Collaborative Learning (CSCL) Assistant that supports teachers to have their students grouped and work on tasks together via discussion, is currently used by a university. At this moment, CSCL Assistant uses chatbot to participate into a group discussion with the help of ChatGPT and Google Gemini. ChatbotLLM (https://chatbot.vipresearch.ca), is IEEE Northern Canada Section’s Capstone Project Award winner project, is a system to automatically train chatbots on the materials uploaded by users. ChatbotLLM is not only capable of learning from material in traditional formats like PDF, PPT(X), DOC(X), and TXT, but also can reading XLS(X), image-scanned based PDF, images in PDF, DOC(X), and PPTX, and even MP3 with the help of Google’s Speech Recognition library. Different from other Generative AI tools or systems, ChatbotLLM would tell users “NO, I don’t know” if it cannot find any relevant content for user’s question from the given materials uploaded. This project aims to design and develop communication way between the two systems, CSCL Assistant and ChatbotLLM, so the chatbot in CSCL Assistant can access ChatbotLLM Service to provide high quality and authentic content in the group discussion.

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Faculty Supervisor:

Maiga Chang

Student:

Partner:

National Dong Hwa University

Discipline:

Computer science

Sector:

Education; Information and Communications Technology (ICT)

University:

Athabasca University

Program:

Globalink Research Award

L2M- TATOM

We will validate TATOM (Tumor-on-a-chip assembly to observe metastasis), a miniature human-on-a-chip platform mimicking cancer metastasis for drug testing. Through customer discovery and market analysis by initially interviewing critical parties in the sector. Through these interviews, we will assess commercial viability, identify user needs, and finally refine the business model to accelerate translation to clinic and market.

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Faculty Supervisor:

Poul Sorensen

Student:

Partner:

I-INC

Discipline:

Life Sciences

Sector:

Health and Related Sciences and Technology; Pharmaceuticals; Biotechnology

University:

The University of British Columbia

Program:

Business Strategy Internship

Mapping Safety Motivation at Work: Untangling the network of causes and consequences

A workplace injury can harm livelihoods and the mental health of employees, yet despite decades of safety interventions, work injuries remain a critical issue in Canada. This raises a critical question: What motivates people to be safe at work? Safety motivation—an individual’s willingness to engage in safe behaviors—is a key predictor of safety performance, making it a vital pathway for improving workplace safety. Yet, safety motivation is poorly understood and measured in diverse ways that reflect different theoretical perspectives (e.g, one-dimensional vs multi-dimensional view). This fragmented understanding limits insight into how different conceptualizations lead to different outcomes and are influenced by varying factors, creating a tangled network of findings. Thus, the proposed research aims to systematically map the conceptual landscape of safety motivation at work across theoretical frameworks using meta-analytic techniques to synthesize findings across multiple studies. Theoretically, this research will advance our understanding of safety motivation by applying a multi-dimensional lens to explain why individuals engage in safety behaviors. Practically, it offers actionable insights for designing work that fosters specific safety motives and guides the development of targeted training and communication strategies.

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Faculty Supervisor:

Ellen Choi

Student:

Partner:

University of Sydney

Discipline:

Sociology

Sector:

Education

University:

Toronto Metropolitan University

Program:

Globalink Research Award

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