Innovative Projects Realized

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

31914 Completed Projects

3006
AB
5256
BC
878
MB
703
NL
913
SK
9488
ON
9949
QC
98
PE
629
NB
1215
NS

Projects by Category

Quantifying the performance of 3D-printed concrete prisms under axial loads

Three-dimensional (3D) concrete printing is an additive manufacturing process in which concrete is deposited layer by layer to construct building elements. Over the past two decades, 3D concrete printing has advanced substantially, enabling the construction of complex geometries with reduced costs and short construction times. These advantages have motivated significant research on the behavior of 3D-printed concrete (3DPC) elements. There is still a need to quantify how 3DPC prisms with different geometries perform under axial loading, which, in turn, will help us understand and advance design of larger 3DPC structural members, such as columns and walls. The proposed research aims to investigate, experimentally and numerically, the axial performance and failure modes of 3DPC prisms with different shapes and material characteristics. This research project will help develop strong and productive collaboration between the research team members at the University of Saskatchewan and the United Arab Emirates University by establishing a research partnership focused on innovative construction technologies and training of an HQP. The partnership will help both teams to benefit from each other’s facilities and expertise. The outcomes will support the development of safer 3DPC structures and contribute to emerging standardization efforts in Canada and internationally.

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Faculty Supervisor:

Belal AbdelRahman

Student:

Partner:

United Arab Emirates University

Discipline:

Engineering

Sector:

Construction; Manufacturing and Construction

University:

University of Saskatchewan

Program:

Globalink Research Award

Testing the responses of lobsters to sustainable new baits

The American lobster Homarus americanus is the most valuable seafood resource in Canada, accounting for over one third of all seafood production. Typically, lobsters are captured in baited traps using fish, with the specific bait varying by region and harvester. In Eastern Canada, herring and mackerel are most often used. Harvesters have to purchase bait, and costs have increased substantially in recent years as fish stocks have declined. In some cases, fisheries have even been closed due to overfishing, making traditional bait not only more expensive, but also environmentally unsustainable. The search for alternative, sustainable baits is therefore imperative. Oberland Agriscience is currently producing insect protein for animal feed and as an alternative protein source for humans. They are now beginning to investigate whether this material could also be used as an alternative, sustainable lobster bait. The intern will investigate lobsters’ behavioural responses and preferences to both the currently used fish baits and Oberland’s new insect-based bait recipes. These initial lab-based experiments are intended to pave the way for field trials to confirm the laboratory findings. If successful, the new bait would represent an important new product for Oberland and provide harvesters with a new sustainable lobster bait.

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Faculty Supervisor:

Iain McGaw;Russell Wyeth

Student:

Partner:

Oberland Agriscience

Discipline:

Life Sciences

Sector:

Agriculture; Manufacturing; Professional, scientific and technical services

University:

Memorial University of Newfoundland

Program:

Accelerate

Quantum Readiness and Investment Signaling in Early-Stage Startups Using NLP and Evidence Scoring

This project builds a reproducible Python framework to evaluate how quantum startups signal technical readiness and commercialization viability to investors. Using NLP and structured evidence extraction from pitch decks/websites/press releases, the intern will classify claims (hardware, error correction, benchmarking, partnerships, IP, talent) and generate an interpretable “Quantum Readiness / Signal Quality” score. Outputs support due diligence research and sector policy analysis.

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Faculty Supervisor:

Sidney Shapiro

Student:

Partner:

National University of Sciences and Technology

Discipline:

Computer science

Sector:

Technology; Quantum Science; Finance and Insurance

University:

University of Lethbridge

Program:

Globalink Research Award

Examination of the reaction kinetics and internal porosity of 8 resin based composites placed in a patient simulator

This project will improve how tooth-coloured fillings are placed and hardened in everyday dentistry. Using advanced infrared spectroscopy, the team will track how eight modern filling materials react when cured with powerful blue light, showing when the reaction starts, how quickly it proceeds, and how completely each material hardens. High-resolution micro-computed tomography (micro-CT) will also be used to examine fillings placed in artificial teeth to detect tiny internal air bubbles or gaps in the fillings that cannot be seen on standard X-rays. By comparing 8 different materials and placement techniques, the study will identify combinations that harden well and contain fewer voids, helping fillings last longer, reduce emergency visits, and lower dental costs for Canadians.

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Faculty Supervisor:

Richard Price

Student:

Partner:

Ivoclar

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program:

Accelerate

Preventing Double Encryption in VPN Software

A VPN establishes an encrypted connection between a client and a VPN server. When the client communicates with a remote site, all IP traffic passes through this connection. The server acts as a gateway, redirecting client traffic to the remote site or traffic from the remote site to the client. Such a VPN provides various forms of confidentiality (for exchanged data, source and destination IP addresses). However, most communications today rely on TLS (e.g., HTTPS), which results in double encryption of data. The idea of CryptOnce is to evaluate the performance impact of double encryption and to introduce a modification to VPN software that avoids it while maintaining the same level of confidentiality.

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Faculty Supervisor:

Thomas Pasquier

Student:

Partner:

Institut National Polytechnique Toulouse

Discipline:

Computer science

Sector:

Education

University:

The University of British Columbia

Program:

Globalink Research Award

Designing better-connected, climate-smart marine protected areas in the high seas

Climate change and biodiversity loss are intertwined global problems; failure to address one often exacerbates the effects of the other. The world is moving towards ambitious global targets in conservation and sustainable development to address these global crises (e.g., the Kunming-Montreal GBF’s ‘30 by 30’ initiative, UN’s BBNJ Agreement). With these global commitments, implementing new MPAs will be inevitable; thus, there is a unique opportunity to design new MPAs with climate change in mind. However, science has been slow to translate advances in climate-change ecology into concrete measures on the ground. This project aims to help bridge this gap by drafting a framework for identifying Important Climate Areas, which are candidate priority areas that should be considered in conservation plans to effectively conserve biodiversity amidst climate change, focusing on the high seas— areas beyond national jurisdiction, comprising >60% of the global oceans. Both the University of Queensland (home) and Dalhousie University (host) have a breadth of conservation research that is applied on-the-ground and has influenced policy, both nationally and internationally. This project aims to produce policy-ready materials that could inform the implementation of the BBNJ Agreement, which could further bolster the impact of the research from these universities.

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Faculty Supervisor:

Anna Metaxas

Student:

Partner:

The University of Queensland

Discipline:

Life Sciences

Sector:

Education

University:

Dalhousie University

Program:

Globalink Research Award

Wild Bodies and Erdogic Systems

This project studies how simple, low-cost robots that bounce off walls instead of using sensors or computers can still explore unknown spaces and find targets, helping advance safe and affordable technologies for tasks like mine detection and environmental monitoring.

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Faculty Supervisor:

Yeganeh Bahoo

Student:

Partner:

University of Oulu

Discipline:

Computer science

Sector:

Education

University:

Toronto Metropolitan University

Program:

Globalink Research Award

Unlocking global fish ecological trait knowledge through Artificial Intelligence

This project will use artificial intelligence to read information about how fish live directly from their images. By training AI models on global databases of fish images, body-shape information and climate data, we will predict important ecological traits such as where species live (rivers, lakes), what they eat, how far they move, and how they care for their offspring. Having this information is essential to understand how they might respond to threats such as climate change, habitat loss and overfishing, and how we can better protect them. The results will be an AI-based model that can predict the ecological traits of fish, likewise, global maps and open code that make this trait information easier to use for studying biodiversity and supporting conservation and fisheries management. For Dalhousie University, the project will provide new trait data and methods that strengthen its research on fish biodiversity and environmental change. For the Industrial University of Santander, it will build local capacity to apply AI in biodiversity research, create datasets, and deepen a long-term collaboration with Macroecology & Biodiversity Change Lab in Canada.

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Faculty Supervisor:

Juan Carvajal-Quintero

Student:

Partner:

Universidad Industrial de Santander

Discipline:

Life Sciences

Sector:

Education

University:

Dalhousie University

Program:

Globalink Research Award

Intact : Extraction et intégration des données d’estimés au processus d’approbation automatique

Intact : Extraction et intégration des données d’estimés au processus d’approbation automatique
Principales activités du partenaire :
Intact Assurance est la plus importante société d’assurance automobile, habitation et entreprises au pays ainsi que le choix de plus de quatre millions de consommateurs.
Problématique, défis et avantages escomptés du projet :
Intact reçoit des estimés de réparation automobile en format PDF de la part de garages. Bien que ces documents suivent un format similaire, nous sommes actuellement incapables d’exploiter efficacement l’information qu’ils contiennent pour automatiser l’approbation des estimés via l’outil ERT (Estimate Review Tool).
Les principaux défis incluent la création d’algorithmes robustes capables d’extraire les données pertinentes de ces PDFs et la mise en place d’un système permettant l’intégration de ces informations dans notre processus d’approbation automatique (ERT).
Nous proposons de développer un modèle de traitement du langage naturel (LLM) pour extraire et structurer l’information contenue dans les PDFs. Cela permettrait d’utiliser ces données dans le flux de travail d’approbation automatique, améliorant ainsi l’efficacité du ERT.

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Faculty Supervisor:

Christian Gagné;Isabeau Prémont-Schwarz

Student:

Partner:

Intact

Discipline:

Computer science

Sector:

Finance and Insurance; Information and cultural industries

University:

Université Laval

Program:

Accelerate

Low-cost LLM inference at the Edge

Seamlessly serving Large Language Model (LLM ) inference requests/queries generated from user devices such as smartphones, laptops, tablets, etc., is critical for LLM service providers. The current approach of serving these queries using large LLMs in the cloud is expensive and incurs high latency and energy costs. More importantly, it cannot meet the growing demand for LLM-powered applications. To address this problem, we propose using edge computing infrastructure to serve the LLM queries at the first hop on edge servers using cost-effective small language models (SLMs). To mitigate the low-quality response provided by the SLMs and to maximize the utilization of the compute and memory capacity of the edge server, we propose the use of an LLM router and a scheduler, and outline the main ideas for designing these modules such that the final LLM inference response by the system is both accurate and fast. The system and the ideas developed in this project will alleviate the scalability issue of LLM inference serving systems and contribute to the ubiquitous use of LLMs.

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Faculty Supervisor:

Jaya Prakash Varma Champati

Student:

Partner:

Manipal University Jaipur

Discipline:

Computer science

Sector:

Artificial Intelligence

University:

University of Victoria

Program:

Globalink Research Award

Pathways to integrate historical knowledge into early stage ecological and regenerative design decision making

This research explores how historical ecological knowledge can inform early-stage design decision-making in ecological and regenerative architecture and landscape design. As cities evolve, much of their ecological memory becomes obscured. Wetlands are drained, waterways are buried, and native species disappear. Without long-term context, designers risk working with shallow baselines that underestimate ecological potential. This project addresses that challenge by developing a framework that identifies how historical data can be translated into tangible design input. The work integrates methods from historical ecology with regenerative design thinking to help design practitioners better understand how places functioned in the past, how they have changed, and what ecological possibilities they may hold for the future.
Through comparative case studies in Canada and the Netherlands, this research will explore the potential of historical knowledge in revealing design potential in various contexts. The aim is to contribute a structured methodology that can help design practitioners work more responsibly with landscape history, support more ambitious ecological outcomes, and cultivate deeper continuity between past and future environments.

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Faculty Supervisor:

Eric Higgs

Student:

Partner:

Delft University of Technology

Discipline:

Sociology

Sector:

Education

University:

University of Victoria

Program:

Globalink Research Award

PISE- Projet d’intégration saines des écrans-Volet enseignants primaire-Répertoires des usages-pilotage

En mai 2025, la Commission spéciale sur les impacts des écrans et des réseaux sociaux a publié un rapport soulignant la nécessité d’encadrer davantage l’usage des écrans chez les jeunes, notamment à l’école. Elle recommande entre autres de mieux former les enseignants afin qu’ils puissent utiliser le numérique de façon responsable, créative et réellement utile en classe. Ces recommandations se sont avérés nécessaire puisqu’une synthèse de 2024 montre que l’utilisation d’appareils numériques en contexte scolaire peut avoir des effets indésirables sur la mémoire, l’attention ou la compréhension. Une seconde synthèse, publiée par l’INSPQ en 2023, insiste pour que l’usage des écrans soit adapté à l’âge des élèves et au type d’appareil, et qu’il ne soit utilisé que lorsqu’il apporte une réelle valeur ajoutée. Certains pays, comme la Nouvelle-Zélande, recommandent même de limiter ces usages à 20 minutes par séance.
Face à ces constats, le projet propose de créer un outil aidant les enseignants à réfléchir à leurs pratiques numériques. Cet outil, accompagné d’une taxonomie claire des usages des écrans à l’école, permettra à l’enseignant de faire une auto-évaluation simple et nuancée des usages du numérique en classe. Il vise à soutenir des pratiques pédagogiques plus réfléchies, mieux équilibrées et bénéfiques

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Faculty Supervisor:

Andréanne Gagné

Student:

Partner:

Alloprof

Discipline:

Sociology

Sector:

Education

University:

Université Laval

Program:

Accelerate

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.