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

A probabilistic cluster expansion based approach for predicting synergism of mixtures of compounds in treating cancers

Combination therapy has been one of the cornerstones for combating cancers. Even though the survival rate of cancer patients after receiving combination therapy is improved dramatically, there are still many unsolved issues to prevent us from claiming combination therapy is a cure for cancers. Those issues include it does not apply to all types of cancers; there are increased risks of side effects, and it requires long developmental time and huge costs. One approach to resolve these issues is applying multiple-compound multiple-target paradigm directly during discovery processes, which exactly is the backbone of the partner organization’s proprietary drug discovery technology. Yet the technology lacks an appropriate and efficient way to predict the effects of combinations. Therefore, the proposal aims not only to improve this technology but also resolve issues in combination therapy.

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Faculty Supervisor:

Jack Tuszynski

Student:

Partner:

SinoVeda Canada Inc

Discipline:

Physics

Sector:

Agriculture; Manufacturing; Professional, scientific and technical services

University:

University of Alberta

Program:

Elevate

Addressing Endogeneity in count data using a two-stage copula generated regressor approach

This research project addresses a common problem in studying medical data: understanding the true effects of different treatments when the data is not from a controlled experiment. Specifically, we are looking at patients with systemic lupus erythematosus (SLE) and the number of infections they get. Often, traditional methods need special, hard-to-find data to ensure accurate results. Our new method skips this requirement by using advanced statistical techniques to account for unmeasured factors affecting the results. By applying this method to SLE patient data, we aim to see how Glucocorticoid influences infection rates. This research could lead to better treatment strategies, improving patient care. The partner organization will benefit from a practical and widely applicable tool to analyze complex medical data more accurately, even when ideal data conditions are not met.

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Faculty Supervisor:

Hui Xie

Student:

Partner:

Arthritis Research Canada

Discipline:

Mathematics

Sector:

Professional, scientific and technical services

University:

Simon Fraser University

Program:

Accelerate

“But…I don’t feel recovered”: Enhancing concussion care in partnership with youth who have experienced ‘prolonged recovery’

Youth concussion rates are rising nationally. Accordingly, efforts are being made to enable the recovery of injured youth. However, little is known about what recovery ‘is’ from the perspective of youth (eg, the care youth need to support recovery). This represents a major gap in knowledge of youth concussion. This research project will partner with youth living with ‘prolonged’ recovery to produce urgently needed insights into their concussion care experiences. It will also refine a research design that leverages the expertise of youth to inform a more supported approach to concussion care that attend to diverse visions of recovery. In the context of a film screening event, 8-10 participants (15-24 years) living with concussion (=4 weeks) will view short films of ‘recovery’ produced by youth in a related project. Participants will then engage in a focus group to explore their reactions to the films, their own care-related experiences, and how the care they received did (or did not) meet their priorities. The knowledge generated is expected to contribute to a (re)visioning of care that accounts for diverse experiences of ‘recovery’. Outputs will include an actionable list of recommendations for youth-informed concussion care and plain language summaries that will be shared widely (with youth, families, clinicians, general public), and housed on the partner organization’s website. Longer term, this research has the potential to reorient concussion care to the real-world needs and priorities of young Canadians. This research will affirm Holland Bloorview as a leader in youth-centered concussion research, supports, and services.

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Faculty Supervisor:

Gail Teachman

Student:

Partner:

Holland Bloorview Kids Rehabilitation Hospital

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology; Retail trade

University:

The University of Western Ontario

Program:

Elevate

Prévision de la charge électrique dans un système de contrôle en boucle fermée

La prévision de la charge, ou de la demande électrique, est une activité fondamentale pour les utilités électriques et en particulier pour Hydro-Québec. Dans un contexte opérationnel, elle vise à prévoir sur un horizon de temps relativement court, typiquement 24 ou 48 heures la quantité d’électricité qui sera consommée par un ensemble de clients donnés. Ce problème a été étudié depuis longtemps sous plusieurs angles et une grande variété de solutions pour le résoudre ont été proposées. Lorsqu’un modèle produit des prévisions, celles-ci peuvent ensuite être utilisées afin de prendre différentes décisions opérationnelles : démarrer ou arrêter des générateurs, augmenter ou diminuer les transactions d’énergie sur les marchés voisins, accélérer ou retarder l’entretien planifié d’équipements, charger ou décharger des stocks d’énergie, ou encore recourir à l’effacement d’une charge flexible pendant une période donnée. Ce projet de recherche vise à concevoir un module autonome de prévision de la demande dans un contexte en boucle fermée, c’est-à-dire un agent dont le comportement évolue en fonction des conséquences de la prise de décisions opérationnelles. Le module devra entre autres gérer le cycle de vie des modèles de prévision disponibles et s’adapter à des contextes changeants en continu.

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Faculty Supervisor:

Eric Beaudry

Student:

Partner:

Institut de Recherche Hydro-Québec;Hydro-Quebec

Discipline:

Computer science

Sector:

Energy and Utilities; Information and Communication Technology; Artificial Intelligence

University:

Université du Québec à Montréal

Program:

Accelerate

UI-Copilot: developing large multimodal models for open-ended web navigation

THIS IS A GENERIC TEXT PUT IN PLACE AS THERE WAS NO PROJECT OVERVIEW.

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Faculty Supervisor:

Reihaneh Rabbany

Student:

Partner:

ServiceNow Canada

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

LeddarTech : Simulation basée sur les données pour la conduite autonome

Les enjeux de données, collection et annotation, sont des points clés de l’industrie des véhicules autonomes et des systèmes d’aide à la conduite. La simulation apprise depuis les données, sans passer par une modélisation de l’environnement, est une technologie à haut potentiel pour toute l’industrie. L’enjeu principal reste la séparation du background foreground, permettant la composition de scénarios difficilement enregistrables dans le monde réel.
Ces deux sujets de stages se concentrent sur deux points essentiels, les séparations des objets par rapport au fond statique, et la réinsertion d’objets appris dans un background de notre choix. En effet, aujourd’hui de nombreux artéfacts de reconstructions ne permettent pas une qualité d’image suffisamment haute.

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Faculty Supervisor:

Christian Gagné;Jean-François Lalonde

Student:

Partner:

LeddarTech Inc

Discipline:

Computer science

Sector:

Manufacturing

University:

Université Laval

Program:

Accelerate

Jumine – Détection des anomalies sur les convoyeurs

Le transport du minerai par convoyeur dans les mines est crucial pour l’efficacité et la rentabilité. Les convoyeurs nécessitent une préparation préalable du minerai par concassage pour améliorer la durée de vie de la bande, la fiabilité du système et réduire les coûts. Comparés aux camions, les convoyeurs présentent un avantage énergétique grâce à leurs moteurs électriques à haut rendement. En collaboration avec les Mines Agnico Eagle et le Corem, Jumine a lancé OptimaVue – Flottation, qui utilise une caméra pour détecter les anomalies à la flottation et développent maintenant OptimaVue – Convoyeur, pour détecter en temps réel les corps étrangers sur les convoyeurs des mines. Ceux-ci risquent d’endommager les équipements, de bloquer la chaîne de valeur et de poser des risques pour la sécurité des opérations minières. Le système utilise les caméras déjà en place chez les clients. Ce projet est soutenu financièrement par quatre mines, le groupe MISA et par Jumine.

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Faculty Supervisor:

Christian Gagné;Philippe Giguère

Student:

Partner:

Jumine Inc

Discipline:

Computer science

Sector:

Mining; Professional, scientific and technical services

University:

Université Laval

Program:

Accelerate

Opportunités durables dans la bio-économie basée sur l’utilisation de la biomasse Boréale perturbée

Le projet de recherche sera réalisé sur le site de Muskrat Falls, le nouveau barrage électrique situé au Labrador. Ce projet rendra disponible, d’ici 2016, 450 000m3 de bois coupés en prévision de la construction du réservoir hydraulique. Le projet de recherche constitue à réaliser des études technico-économiques et environnementales (analyse du cycle de vie) sur l’utilisation de ce bois dans un procédé de bioraffinage. De plus, le projet permettra d’inclure dans les modèles économiques et environnementaux, le bois perturbés de la région de Goose-Bay (feu, insectes et vent). Le projet répondra parfaitement aux besoins du partenaire puisqu’il identifiera l’option d’utilisation du bois la plus prometteuse et la plus durable et proposera des pistes d’amélioration en considérant le bois perturbés en place dans les forêts.

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Faculty Supervisor:

Paul Stuart

Student:

Partner:

Natural Resources NL (Corner Brook);EnVertis

Discipline:

Engineering

Sector:

Forestry; Sustainability & the Environment; Natural Resources

University:

École Polytechnique de Montréal

Program:

Accelerate

Sleep for gold: a comprehensive assessment and development of sleep health recommendations for Quebec’s elite athletes

The difficulty for elite athletes to have sufficient restorative sleep is confirmed for years. This study is here to help identify the issues triggering this lack of sleep thanks to the validation of the French version of a sleep questionnaire exclusively made for athletes and a global evaluation of their sleep and performance. This research project will provide great insights of what can be done in order to improve the athletes’ performance while adjusting their sleep health. Finally, it will help coaches of the INSQ to know how to rethink their training according to each sport so their athletes sleep enough for gold.

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Faculty Supervisor:

Guido Simonelli

Student:

Partner:

INS Québec

Discipline:

Life Sciences

Sector:

Administrative and support, waste management and remediation services; Arts, entertainment and recreation; Health and Related Sciences & Technology; Professional, scientific and technical services

University:

Université de Montréal

Program:

Accelerate

Development of Advanced Lithium Rechargeable Batteries and Scalable Manufacturing Processes

Demand for higher-capacity batteries has been rising exponentially from industries such as zero-emission vehicles, smart grids, unmanned aerial vehicles, and many others. However, current battery technology is limited by graphite anode materials, which have a low specific capacity. Furthermore, the manufacturing process of battery-grade graphites is criticized for the amount of GHG and environmental damage created.
Silicon, with eleven times the energy density than graphite, introduces a promising avenue for innovation to enhance battery performance. However, silicon’s significant volume expansion during lithiation cycles leads to rapid degradation. Current efforts to make silicon anodes commercially viable involve complex, energy-intensive, and costly manufacturing processes. These challenges require innovative materials engineering, advanced manufacturing, and sustainable practices.
We aim to develop a scalable, cost-efficient, and greenhouse gas emission-reducing manufacturing process for silicon-based anode materials. In this research, we will develop techniques applicable to different aspects of manufacturing processes, including utilization of industry byproduct materials, surface engineering of silicon particles, thin and conforming carbon coating, and energy-efficient heat application. The processes will be evaluated by battery electrochemical performance, energy consumption, greenhouse gas generation, and manufacturing costs.

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Faculty Supervisor:

Seonghwan Kim

Student:

Partner:

MakeSens Advanced Battery Materials

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Calgary

Program:

Accelerate

Geoconservation and site monitoring of the geoheritage of Discovery UNESCO Global Geopark

UNESCO Global Geoparks are a comparatively new designation with the focus being clearly on protection of Geoheritage, but also its promotion in the form of Geotourism Geoeducation and sustainable development. Since 2015 some 213 geoparks have been designated including one in Newfoundland Discovery UNESCO Global Geopark, which is based around the fact that it is the home of the earliest animal fossils, and as such of Global significance. The fact that Discovery covers a wide area not within a national or provincial park creates a need to document and address geoconservational challenges that might compromise the designation. The potential threats to the fossil sites relate to climate and climate change as well as human activities. The project aims to survey the sites in Fall 2024 to provide a baseline with which change over the period of intense storm and freeze-thaw activity occurs (Fall through Winter). The methodology involves creating photogrammetric models of the fossil sites and surrounding soils and beaches, we will also install solar powered cameras that will take one photo a minute throughout the day every day to document the extent of wave action but also footfall from visitors to the fossil sites and any other activities (e.g.

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Faculty Supervisor:

Duncan McIlroy

Student:

Partner:

Discovery UNESCO Global Geopark

Discipline:

Earth science

Sector:

Public administration

University:

Memorial University of Newfoundland

Program:

Accelerate

Hybrid Quantum-Classical Image Processing by Merging Enhanced Flexible Qubit Representation for Quantum Images equipped with Probability Distribution (EFQRQI-PD) and Machine Learning for Enhanced Accuracy

Image processing principles and techniques represent a significant advancement in modern technology, offering invaluable contributions to numerous sectors. Despite their efficacy, conventional AI and ML-based image processing algorithms encounter inherent limitations that obstruct their scalability and performance. The main aim of the proposed research project is to develop image processing algorithm based on quantum computing and machine learning principles, utilizing amplitude encoding for transition between classical bits and qubits. This initiative seeks to meet the urgent requirement for developing effective image processing techniques by crafting a system capable of efficiently predicting unseen patterns. By achieving this goal, the project aims to significantly enhance the efficiency and accuracy of image processing tasks, thereby enabling more informed decision-making and promotion developments in various fields reliant on visual data analysis. The team involved in this project has an existing research partnership. This partnership is focused on advancing the field of quantum image processing and creating theoretical algorithms. This partnership involves joint research, sharing of knowledge, and co-authoring papers in respected academic journals and conferences.

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Faculty Supervisor:

Ajmery Sultana

Student:

Partner:

Vellore Institute of Technology

Discipline:

Computer science

Sector:

Quantum Science; Technology; Artificial Intelligence

University:

Algoma University

Program:

Globalink Research Award

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