Innovative Projects Realized

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

30156 Completed Projects

2861
AB
5059
BC
812
MB
673
NL
842
SK
8957
ON
9368
QC
96
PE
579
NB
1120
NS

Projects by Category

Predictive dosimetry in radiopharmaceutical therapy using advanced artificial intelligence, physiologically based pharmacokinetic modeling, and imaging data

Cancer is a leading cause of death worldwide. One of the main ways to remove cancer cell is targeting them using beta and alpha particle radiation. These kinds of radiations can be reached to the cancer sites by attaching them to special drugs that have specific binding sites on their cells. However, there is no accurate method to find how much radiation dose is required to remove these cells. As such measuring accurate dose received by cancer cells is not a straightforward method. In this era, we need to personalize therapy in terms of prediction of the dose. In this study, we try to predict dose using AI and imaging data, as well as models that describe the behavior’s of drugs in the body.

View Full Project Description
Faculty Supervisor:

Arman Rahmim

Student:

Partner:

BC Cancer

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Professional, scientific and technical services

University:

The University of British Columbia

Program:

Elevate

Generation and characterization of induced pluripotent stem cell (iPSC) lines from genetically engineered mouse model and differentiation potential

Tissue-resident fibroblasts and their attendant activities are central drivers of a diverse range of diseases. The overarching theme of this proposal is to develop novel fibroblast reporter lines that will enable us to identify
tractable therapeutic targets to modify fibroblast activity. To identify such targets, we are proposing to carry out high throughput screens (i.e., small molecules, gRNAs, siRNAs, etc.) in fibroblasts engineered to express a
reporter reflective of the desired phenotype. For the purposes of this proposal, we plan to generate induced pluripotent stem cell (iPSC) lines from fibroblasts isolated from a genetically engineered mouse model (GEMM).
Fibroblasts from these mice contain two reporter genes that will enable us to follow various aspects of the fibroblast phenotype. The project contains two aims: 1) generation and validation of iPSCs from mouse embryonic
fibroblasts of a GEMM; 2) generation of fibroblasts with the desired phenotypic properties from the aforementioned iPSC lines. Once validated, these iPSC lines will serve as “a well-validated, off-the-shelf” supply of fibroblasts for screening purposes. In short, this project will generate new iPSC cell lines to support a unique platform directed towards developing fibroblast-targeted therapeutics to treat disease.

View Full Project Description
Faculty Supervisor:

Chad Bousman;Steven Greenway

Student:

Partner:

Stem Cell Network;Mesintel Therapeutics Inc.

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Calgary

Program:

Accelerate

Vers une amélioration continue de la gestion des systèmes de qualité en industrie pharmaceutique: l’informatisation des processus la bonne alternative de la documentation

Dans l’industrie pharmaceutique, la qualité des médicaments est de plus haute importance car elle touche des enjeux plus larges en termes de santé publique. Alors une démarche qualité est indispensable car elle est considérée comme un pilier de l’entreprise.
Les organismes pharmaceutiques ont tendance de mettre en place un système de management de qualité qui est l’ensemble des activités par lesquelles ils définissent, mettent en oeuvre et revoient leur politique et leurs objectifs qualité conformément à leur stratégie, et celui-ci est nécessaire à la maitrise et l’amélioration des divers processus.
Alors, dans le but d’avoir l’excellence opérationnelle dans la gestion quotidienne des systèmes qualité, on vise dans ce projet à optimiser les systèmes qualité en mettant en place des outils plus fiables qui rendent les processus plus performants. L’informatisation est l’une des principaux moyens qui permettrait des systèmes beaucoup plus flexibles et réactifs, d’autres approches d’optimisation de la gestion de la qualité vont être discutés dans ce projet tels que la cartographie des processus et l’établissement des KPIs.

View Full Project Description
Faculty Supervisor:

Marc Servant;François-Xavier Lacasse

Student:

Partner:

Galenova

Discipline:

Physics

Sector:

Manufacturing; Professional, scientific and technical services; Wholesale trade

University:

Université de Montréal

Program:

Accelerate

Zero-to-Hero: Data Augmentation with LLMs and Human Feedback

Intent classification is a highly popular task within research communities and industries. Having a system that can classify intents of emails or messages from users can lead to a wide range of applications such as ticket routing and issue resolution. However, training such models require a large set of labeled data that might not be readily available. In this project work, we aim to present a system where only a few examples are required to be given for each intent. At each cycle we train an intent classifier and use a large language model (LLM) to generate extra examples using the examples in the dataset. Those generated examples are carefully selected as humans are involved to verify them. Concretely, the LLM generates a set of examples that are ranked based on scores given by the models involved in the system. To have more diversity and variations in the generated examples, we allow the LLM to generate new examples using previously generated examples. This system has the potential to train a powerful intent classification method with extremely low human effort that could significantly speed up the process of addressing customer requests.

View Full Project Description
Faculty Supervisor:

Olga Vechtomova

Student:

Partner:

ServiceNow Canada

Discipline:

Computer science

Sector:

Artificial Intelligence; Technology; Information and Communications Technology

University:

University of Waterloo

Program:

Accelerate

Omy Laboratoires : Segmentation clientèle

Omy Laboratoires vise à offrir des soins topiques responsables, sains et personnalisés à ses client.e.s et
futurs client.e.s, à chaque étape de leur vie. Dans cette perspective de soins personnels et personnalisés,
Omy cherche à améliorer la compréhension de sa clientèle courante et à venir, en étudiant les différents jeux
de données collectés sur sa plateforme d’analyse d’images cutanées. Plus particulièrement, Omy cherche à
déterminer les caractéristiques déterminantes de la pérennité de sa clientèle et les segments les plus propices
pour sa croissance.
Dans ce contexte, OMY vise :
1. à expliquer ses performances de rétention de sa clientèle en déterminant les caractéristiques des client.e.s
qui persistent et les actions à entreprendre qui maximise cette rétention;
2. à déterminer les caractéristiques des différentes clientèles potentielles à développer en priorité.
Pour ce faire, OMY vise à étudier les données collectées lors des premiers contacts clients et leur première
évaluation dermique automatisée. Une attention particulière a été portée à ce que l’étudiant n’accède pas aux
images des utilisateurs mais bien aux caractéristiques extraites de ces images par des algorithmes
développés par un autre partenaire.

View Full Project Description
Faculty Supervisor:

Christian Gagné;Marie-Pier Côté

Student:

Partner:

Omy Laboratoires

Discipline:

Computer science

Sector:

Manufacturing

University:

Université Laval

Program:

Accelerate

Machine learning augmented simulation of urban wind flows

Engineers that design and enhance buildings widely rely on computer simulations to understand wind flows. Wind flows around buildings can affect human safety, comfort, structural safety, and the surrounding environment.
Therefore, accurate and fast simulation of urban wind flows is critical to ensure safe, comfortable, and sustainable designs. If architectural engineers have access to a fast and accurate tool for simulating urban window flows, they can rapidly iterate and design the most energy efficient and sustainable buildings. Though robust, the current methodology for fast urban wind flow simulations often is inaccurate, meaning that slow and expensive simulations are required, slowing down the design process. The goal of this project is to use machine learning to improve current fast methodologies, thereby giving architectural engineers enhanced capabilities to design the safer and more sustainable buildings of the future.

View Full Project Description
Faculty Supervisor:

Fue-Sang Lien

Student:

Partner:

Rowan Williams Davies & Irwin Inc

Discipline:

Engineering

Sector:

Construction and infrastructure; Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

Design and Analysis of a Platform to Connect Patients, Providers, and their Social Networks

The healthcare system in Canada and world-wide is suffering increased pressure due to an aging population and increased rates of chronic disease. Research shows that self-management and social networks are key indicators for reducing utilization and cost and improving outcomes of healthcare systems. Lifeguard Health Solutions Inc. has developed a mobile health application that uses technology to connect patients with their providers, their trusted support network, and their peers to improve self-management and social network strength. Through a before and after pilot study in a select disease patient group, we will analyze the effects of the application on patient education,
patient satisfaction, and levels of adherence and compliance to prescribed care plans.

View Full Project Description
Faculty Supervisor:

Hannah Wong

Student:

Partner:

Lifeguard Health Networks Inc

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

York University

Program:

Accelerate

Extrapolating Lessons Learned from Mitigating Emerging One Health Disease Threats: Avian Influenza, African Swine Fever and Foot and Mouth Disease

Many lessons from previous pandemics help to guide future outbreaks. This project reviews the avian influenza outbreak in Canada and applies some of the lessons learned to help mitigate the potential outbreaks of African swine fever and foot and mouth disease using a One Health approach.

View Full Project Description
Faculty Supervisor:

Cathy Bauman;Tracey Chenier

Student:

Partner:

Animal Health Canada

Discipline:

Life Sciences

Sector:

Agriculture

University:

University of Guelph

Program:

Accelerate

Un cadre pour faire progresser l’intelligence d’affaires et analytique dans les PME

Le projet de recherche vise à étudier comment les actions liées à la mise en œuvre et au développement des pratiques d’intelligence d’affaires et d’analytique (BI&A) peuvent créer de la valeur commerciale au sein des petites et moyennes entreprises (PME) manufacturières dans le contexte de l’industrie 4.0. Grâce à une approche méthodologique mixte combinant des éléments de recherche qualitative et quantitative, basée sur la recherche en sciences de la conception (DSR), la recherche vise à explorer l’utilisation de la BI&A par les PME au Québec, en analysant les pratiques et les technologies BI&A utilisées pour collecter, analyser et interpréter les données, en plus de la façon dont cela influence la prise de décision stratégique, l’efficacité opérationnelle et l’avantage concurrentiel des entreprises. Trois étapes principales seront développées : (i) Analyse et description de la mise en œuvre de la BI&A ; (ii) Collecte de données ; (iii) Analyse intégrée. La recherche vise également à étudier les principaux défis et opportunités liés à l’utilisation de BI&A par les PME, à travers une analyse des facteurs et des technologies qui influencent la capacité d’adaptation et d’innovation…

View Full Project Description
Faculty Supervisor:

William de Paula Ferreira

Student:

Partner:

Universidade Federal Fluminense

Discipline:

Engineering

Sector:

Education

University:

École de technologie supérieure

Program:

Globalink Research Award

Détection thermique acoustique du mammifère marin par drone

Ce projet a pour objectif de développer un système d’intelligence artificielle avancé capable de détecter et de classifier les baleines dans des images capturées par un drone équipé d’une caméra thermique. Pour atteindre cet objectif, il utilise des techniques de pointe telles que les réseaux neuronaux convolutionnels (CNN), la segmentation d’images, l’extraction de caractéristiques et les méthodes d’ensemble. Les réseaux neuronaux convolutionnels sont utilisés pour extraire des caractéristiques clés des images, permettant une identification précise des baleines. La segmentation d’images permet de délimiter avec précision les contours des baleines, facilitant leur analyse détaillée. L’extraction de caractéristiques joue un rôle central dans la classification et la reconnaissance des baleines. Des propriétés telles que la texture, la forme et les descripteurs de couleur sont utilisées pour former des modèles d’apprentissage automatique traditionnels tels que les machines à vecteurs de support (SVM) et les forêts aléatoires. Les méthodes d’ensemble sont également employées pour améliorer la précision et la robustesse du système, en combinant les prédictions de plusieurs modèles avec différentes architectures ou hyperparamètres.

View Full Project Description
Faculty Supervisor:

Noureddine Barka;Tawfik Masrour;Ibtissam El Hassani

Student:

Partner:

Merinov (Gaspé, QC)

Discipline:

Engineering

Sector:

Agriculture; Professional, scientific and technical services

University:

Université du Québec à Rimouski

Program:

Accelerate

Wartime Policy Making and Governance: Ukraine and Canada Higher Education Alliance

Involving some of the smartest students in Ukraine, the research project and partnership will enrich the Master of Global Affairs and Master of Public Policy programs at the Munk School. KSE students will provide Munk community a window into the Ukrainian policymaking process as well as a more general understanding of governance during conflict. Simultaneously, student presentations to senior Canadian officials will offer the Canadian government an in-depth perspective into key policy questions facing Ukraine. This will improve Canadian government capacity to assist Ukraine.
The KSE-Munk students-will examine different models of policymaking in wartime and identity appropriate models for the Ukrainian context. For their final output students will make policy proposals and write up a 10-page policy brief.

View Full Project Description
Faculty Supervisor:

Lucan Way

Student:

Partner:

Kyiv School of Economics

Discipline:

Sociology

Sector:

Education

University:

University of Toronto

Program:

Globalink Research Award

Historical Wildfire Regimes and Contemporary Wildfire Risk in Stswecem’c Xget’tem Territory

Wildfires are a complex and growing problem worldwide. In interior British Columbia, Canada, they are becoming larger, more frequent, and severe due to two centuries of settler land management and the impacts of climate change. Of the most affected by wildfire are rural Indigenous Peoples, as their communities are often surrounded by flammable forest and grassland fuels. Stswecem’c Xget’tem First Nation (SXFN) partnered with the University of British Columbia to co-generate western science on the past and present forests, fuel loads, and fire regimes close to their two communities. SXFN may use this knowledge in combination with their place-based multigenerational knowledge systems to lead forest stewardship that restores eco-cultural lands, adapts their Territory to climate change, and protects their communities and the lands and waters they rely on from severe wildfire.

View Full Project Description
Faculty Supervisor:

Lori Daniels

Student:

Partner:

Stswecem’c Xgat’tem Development Corporation

Discipline:

Earth science

Sector:

Public administration

University:

The University of British Columbia

Program:

Accelerate

Previous
1…881882883884885886887…2,513
Next

Join a thriving innovation ecosystem.

Subscribe to our newsletter now!

Subscribe