Innovative Projects Realized

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

30508 Completed Projects

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

Projects by Category

User research, design, and creation of an inclusive digital physical and mental wellness game

The physical and mental health of Canadian youth is one of the greatest issues facing the country today. This project partners Mitacs with X Movement to create a digital game that promotes emotional, physical, and social wellness for kids. A special emphasis is being placed on inclusion across many marginalized groups such as disabled people, racialized people, and those in low income communities. The project will follow a three stage format. First, we will consult with users to make sure the digital game can be as inclusive as possible. Second, we will design prototypes of the digital game. Finally, we will develop the digital game so it can be used by children, their families, and educators across Canada.

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Faculty Supervisor:

Sara Grimes

Student:

Partner:

X Movement

Discipline:

Sociology

Sector:

Education

University:

University of Toronto

Program:

Accelerate

Neurological structures extraction and analysis for spinal disease diagnosis and intervention

31 pairs of spinal nerves, containing both sensory and motor nerve fibers, serves two important
functions: pathway for sensory, motor impulses and are essential for spinal reflexes. Damage of spinal
nerves has been one of the major concerns in diagnosis, treatment and spinal intervention. This project
proposes to promptly and accurately extract neurological structures from MRI images. Once achieved,
the partner organizations can use this for surgical planning and treatment. It will greatly improve their
efficiency and reduce complications during surgical interventions.

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Faculty Supervisor:

Keng Yeow Tay

Student:

Partner:

London X-Ray Associates

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology

University:

Western University

Program:

Accelerate

Minimiser les efforts d’annotation lors du développement d’un modèle prédictif en traitement des langues

Développer un modèle prédictif en traitement automatique des langues requière la création d’un corpus annoté : un texte et des annotations que l’on tentera de reproduire automatiquement. Il s’agit d’une activité à la fois complexe (les annotations sont souvent du ressort d’un expert) et coûteuse (annotations méticuleuses à produire en grande quantité). Le projet vise à développer une expertise pour minimiser les interventions (annotations) permettant d’obtenir un modèle prédictif d’une qualité donnée.

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Faculty Supervisor:

Philippe Langlais

Student:

Partner:

LexRock AI

Discipline:

Mathematics

Sector:

Administrative and support, waste management and remediation services; Information and cultural industries

University:

Université de Montréal

Program:

Accelerate

Digitized neuroanatomical map of the human saphenous nerve

Overactive bladder (OAB) is an incurable, chronic medical condition that is characterized by symptoms of urgency, frequency, nocturia and urinary incontinence. It affects approximately 18% of adults and over 30% of the elderly population. Saphenous nerve stimulation is a novel therapy aimed at treating OAB patients. It offers an alternative to bladder medication, which can have severe side effects such as dry mouth, cognitive impairments and hypertension. And, unlike sacral nerve stimulation, this novel treatment can be delivered to patients in a noninvasive manner. Recent clinical trials show that saphenous nerve stimulation can effectively reduce OAB symptoms in patients (e.g., 75% response rate), but the findings suggest that more effective and consistent activation of the SAFN can further improve clinical outcomes. To this end, the goal of this project is to create a high-resolution digital map of the human SAFN that will, in turn, be used to implement highly realistic computational (finite element) models aimed at simulating innovative forms of peripheral nerve stimulation in humans.

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Faculty Supervisor:

Anne Agur

Student:

Partner:

EBT Medical

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Système d’aide à la décision pour le ciblage des populations pauvres et vulnérables

Dans les pays en voie de développement, des enquêtes sont utilisées pour mesurer le niveau de pauvreté des ménages. Pour étendre cette information à l’ensemble de la population, il est nécessaire de prédire la pauvreté des ménages à partir des enquêtes et d’imputer cette prédiction à chaque ménage du recensement. L’utilisation de ces données permet aux gouvernements et aux agences d’aide au développement de mieux cibler les populations les plus pauvres. Les outils de ciblage sont d’une importance capitale pour améliorer le ratio bénéfices/coûts des interventions. Afin d’améliorer les outils disponibles pour le ciblage des populations pauvres et vulnérable, l’objectif de ce projet de recherche sera de rendre disponible à partir d’une plateforme web les indicateurs estimés à partir des mégadonnées (enquêtes et recensement des populations) et les modèles prédictifs afin d’aider à la prise de décision dans un contexte d’aide au développement. La création d’un système d’aide à la décision, et plus particulièrement un tableau de bord analytique permettra de proposer des analyses du ciblage des interventions sur des groupes spécifiques définis selon leurs caractéristiques ou selon leur localisation géographique.

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Faculty Supervisor:

Mickael Germain;Yacine Bouroubi

Student:

Partner:

Apexmachina Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Université de Sherbrooke

Program:

Accelerate

Fabrication of HTV-SR/ATH/DE/FS Nanocomposites Emerging Damage-tolerant Volumetric Superhydrophobicity Followed by Assessment of the Icephobic, Self-cleaning, Thermal, and Electrical Properties for Application to High-voltage Insulator

Given the detrimental effect of the ice and pollution accumulation on the high-voltage insulators, fabrication of superhydrophobic surfaces having icephobic and self-cleaning is highly demanded. Superhydrophobic surfaces possessing low surface energy materials with favorable surface roughness have attracted tremendous attentions in both science and technology. However, lack of favorable mechanical durability of such appealing materials has confined their mass production and commercialization. Since the conventional insulators are getting replaced by the polymeric ones, specifically silicone rubber having low surface energy, this project aims to develop a damage-tolerant superhydrophobic silicone rubber nanocomposite possessing icephobic/self-cleaning properties capable to be utilized for high-voltage insulator application. In this regard, three different micro and nanoscale particles will be used to not only create volumetric superhydrophobic nanocomposite but enhance icephobic, self-cleaning, thermal, and electrical properties of silicone rubber. The optimized combination of these particles will bring about the hierarchical roughness required for superhydrophobicity as well as the flame retardancy, tracking, and erosion resistance of the nanocomposites.

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Faculty Supervisor:

Gelareh Momen;Reza Jafari

Student:

Partner:

K-Line Insulators Limited

Discipline:

Engineering

Sector:

Manufacturing

University:

Université du Québec à Chicoutimi

Program:

Accelerate

Le processus de transfert des données lors du livrable des actifs bâtis: comment les outils technologiques répondent aux demandes du client dans le contexte des normes en vigueur.

Ce projet tentera d’observer la mise en application des normes de gestion des données du bâtiment (ISO19650) lors du transfert des livrables numériques d’un actif. Le contexte de cette étude de cas suivra le transfert des données provenant d’une équipe de conception/construction et allant vers une équipe d’opération et de maintien des actifs. L’efficacité de la plateforme de gestion des données utilisée (Dalux Handover) dans le cadre de cette étude de cas sera évaluée en fonction de sa capacité à transmettre et utiliser les données requises par le client. L’hypothèse proposée suggère qu’il sera possible d’optimiser les exigences de données numériques formulées par le donneur d’ouvrage en vue de leur utilisation avec la plateforme de gestion de données.

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Faculty Supervisor:

Ali Motamedi;Érik Poirier

Student:

Partner:

BIM Québec

Discipline:

Engineering

Sector:

Other services (except public administration); Real estate and rental and leasing

University:

École de technologie supérieure

Program:

Accelerate

Climate-related Disclosure Best Practices

Mantle314 is developing a software platform (Manifest) that will help companies to learn, assess, manage and disclose climate-related risks and opportunities. Mantle314 is currently working on minimum viable product (MVP) experience which will be the first step toward automating an end-to-end climate change-related planning and disclosure process. This first experience will help a company to assess its own disclosure against climate leaders and peers, and create TCFD-aligned outputs for internal and external communications and reporting.
To understand the current state of play of what good climate-related disclosure looks like, as part of this project, interns will be reviewing climate content from a sample of companies using the Mantle Assessment methodology to research sector specific practices as it concerns TCFD Recommendation implementation and climate actions. The aim is to find climate leaders and define best practices for each sector. This research and its content will be used in MVP for benchmarking and showcasing best practice.

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Faculty Supervisor:

Olaf Weber;Jason Thistlethwaite

Student:

Partner:

Mantle314

Discipline:

Sociology

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

Développement d’un contrôleur de batterie lithium-ion

Le besoin de développement d’un tel contrôleur est motivé par la disponibilité grandissante de bloc-batteries lithium-ion récupérés de véhicules électriques accidentés ou ceux dont la pile arrive en fin de vie utile.
Chaque type de cellule lithium-ion comporte des caractéristiques de charge et décharge qui doivent être étroitement surveillées pour éviter d’endommager la cellule et même provoquer un l’incendie ou l’explosion de celle-ci.
Le contrôleur, en plus de surveiller la charge et la décharge, doit également assurer le balancement des cellules, c-a-d le maintien de chacune des cellules au même niveau detension, pour permettre l’utilisation maximale de l’énergie contenue dans le bloc-batteries.
Finalement le projet va permettre à l’organisme partenaire de pouvoir fabriquer l’ensemble du système de gestion de batterie lithium-ion, lui permettant de s’affranchir de composants existants mal adaptés a ses besoins et où une possible rupture de l’approvisionnement engendrerait un arrêt de production de l’ensemble des systèmes.

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Faculty Supervisor:

Loïc Boulon

Student:

Partner:

Simon André Inc

Discipline:

Engineering

Sector:

Retail trade

University:

Université du Québec à Trois-Rivières

Program:

Accelerate

Improving Conditional Text Generation Algorithms

The aim of this project is to survey and develop methods for improving text generation algorithms. Natural Language Generation (NLG) is a subfield of Deep Learning that studies how to enable computers to write coherent texts. Current methods lack the capacity to adapt the content they generate, producing articles that are not always coherent nor factually correct. We will study ways of conditioning the algorithms to create more relevant content that adapts to the needs of the writer. The internship will be done in collaboration with MarketMuse, an AI company that specializes in content creation and is looking for new ways to improve their algorithms.

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Faculty Supervisor:

Laurent Charlin

Student:

Partner:

Marketmuse Laboratoire Canada Inc.

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

HEC Montréal

Program:

Accelerate

Low Dose Computed Tomography Imaging: Measuring effects of denoising algorithms by means of objective and subjective measurements, and algorithms parameters optimization

In Computed Tomography (CT), X-ray radiation is used to penetrate through the internal structure of
the patient body in order to produce digital images. This means patients could be exposed to certain
level of X-ray radiation dose. Accumulation of these exposures beyond certain threshold could
increase risk offatal cancer. Thus it is of paramount importance to lower the amount of radiation
exposure during CT images acquisition. However, a low radiation dose in CT images would result to
lower image quality. To maintain lower dose usage and still produce images with a high quality, one
needs to develop advanced image processing tools in order to reduce noise and enhance CT images.
This internship will attempt to bring advanced methods of Image processing tools that are specifically
tailored to reduce noise and enhance CT images to the partner ()rganization, measure the effects of
these algorithms on Image quality objectively and subjectively, fine tune parameters of these
algorithms.

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Faculty Supervisor:

M. Stella Atkins

Student:

Partner:

McKesson Canada (Richmond, BC)

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Simon Fraser University

Program:

Accelerate

Modèle intelligent de prédiction de pannes à partir de capteurs installés dans un bâtiment

Une institution de Montréal possède un ensemble de bâtiments où sont installés des capteurs de toute sorte générant quotidiennement des milliers de mesures (entre autres vibration, température, pression, ouverture/fermeture de portes). Ce projet, piloté par la compagnie Ai Outcome, vise à mettre en place un modèle automatique de détection qui permettra de prédire les pannes sur les équipements avant que celles-ci ne se produisent. Pour ce faire, le stagiaire appliquera diverses techniques d’intelligence artificielle de détection de données aberrantes sur les mesures existantes pour ensuite comparer les résultats obtenus avec les types d’événements générés par le système. Si Ai Outcome est capable de fournir de telles prévisions, ses clients bénéficieront d’une réduction de leurs coûts et de leurs risques. Le Canada pourrait ainsi devenir un chef de file sur la manière dont la maintenance est effectuée, réduisant ainsi les coûts d’exploitation des infrastructures publiques et privées.

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Faculty Supervisor:

Sylvie Ratté

Student:

Partner:

iA Résultat Inc

Discipline:

Engineering

Sector:

Information and cultural industries

University:

École de technologie supérieure

Program:

Accelerate

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