Completed Projects

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

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13268 Completed Projects

1072
AB
2795
BC
430
MB
106
NF
348
SK
4184
ON
2671
QC
43
PE
209
NB
474
NS

Projects by Category

10%
Computer science
9%
Engineering
1%
Engineering - biomedical
4%
Engineering - chemical / biological

La prévention de la maladie de Lyme chez les travailleurs d’Hydro-Québec, dans le contexte des changements climatiques

La maladie de Lyme ou borréliose est de plus en plus fréquente en Amérique du Nord. Causée par la bactérie Borrelia burgdorferi, au Québec, la maladie de Lyme est transmise lors d’une piqûre de la tique infectée Ixodes scapularis. Dans le souci de préserver les travailleurs forestiers d’Hydro-Québec, il sera réalisé successivement une revue de littérature sur les facteurs climatiques et environnementaux favorables à la survie de la tique, suivie de la documentation des différents paramètres à prendre en compte lors de la gestion de risque en santé pour l’élaboration de mesures de prévention des travailleurs forestiers d’Hydro-Québec.

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Faculty Supervisor:

Nolwenn Noisel

Student:

Victoire Marie-Hermine Ngo Bassom

Partner:

Hydro-Québec

Discipline:

Environmental sciences

Sector:

Energy

University:

Université de Montréal

Program:

Accelerate

Drug Repurposing for Neuromuscular Diseases

SMA is a neurodegenerative disease characterised by the loss of lower motor neurons and is an incurable disease. SMA is the leading genetic cause of early childhood lethality, with an incidence of 1 in 6,000 to 10,000 live births and a carrier frequency of 1 in 35-40. Current therapeutic strategies under development are almost exclusively based on increasing functional SMN protein. Given the divergence in prognoses due to the complexity of the different SMA type designation, the application of a combination of non-SMN dependent and SMN restoring therapies, would likely be essential to treat SMA. Therefore, there is an urgent need to develop and assess new non-SMN therapeutics for this incurable disease, which could be particularly effective at early stages of SMA. Modelis’ mission is to accelerate drug discovery for human genetic diseases and they are investing a large portion of their activities to drug repurposing. The current project will allow fastening the identification of already approved drugs for SMA using simple fish models of the disease in order to translate them quickly to the clinic

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Faculty Supervisor:

Alex Parker;Pierre Drapeau

Student:

Estefania Carrillo

Partner:

Modelis inc.

Discipline:

Medicine

Sector:

Life sciences

University:

Université de Montréal

Program:

Accelerate

oN DuTy! – Innovative Program on NonDestructive Testing (NDT) – Part 2

NonDestructive Testing (NDT) is a key discipline in major industrial sectors to ensure quality and safety. Several methods are regularly employed in areas ranging from x-ray or ultrasound testing of metallic or composite components in the automotive and aerospace industries, to the inspection of petrochemical ducts using eddy currents or acoustical emissions. The present proposal combines different NDT-related subjects under the oN DuTy! training initiative supported by the NSERC CREATE, whose main objectives are of developing an enriched, unique and innovative Technical and Professional training experience in NDT for students and postdoctoral fellows through a network of leading NDT universities and industrial partners, thereby facilitating the transition of new researchers from trainees to productive employees in the Canadian workforce. The investigated subjects are at the forefront of current worldwide research efforts in NDT and deal with a variety of applications and challenges according to the actual needs of the partners.

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Faculty Supervisor:

Tobin Filleter;Anthony N. Sinclair;Pierre Bélanger;Xavier Maldague

Student:

Cong Zhu John Sun;Jorge Franklin Mansur Rodrigues Filho;Leon Chen

Partner:

Pratt & Whitney Canada

Discipline:

Engineering - mechanical

Sector:

Aerospace and defense

University:

Program:

Accelerate

Development of Solar Micro-Reactors for Steam Methane Reforming

Hydrogen is often seen as an energy carrier that can support our growing need for greener energy. However, current methods to produce hydrogen are cost prohibitive or generate large volumes of CO2, namely by the combustion of natural gas (NG) to provide heat to the commonly used steam methane reforming (SMR) process. By using established concentrated solar power (CSP) technology to provide heat instead of combustion, it is possible to reduce CO2 emission and NG consumption. A solution developed at Université de Sherbrooke uses micro-reactors to harvest the heating power of the sun for SMR. This strategy could provide a method to produce large volumes of greener hydrogen while reducing its cost. The research project covered by this proposal aims at demonstrating the economic and technological viability of this approach and is split in 4 different tasks, each of them covered by an intern.

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Faculty Supervisor:

David Rancourt

Student:

Jean-François Dufault;Jean-François Peloquin;Marianne Duverger;Dino Mehanovic

Partner:

CSAR Energy

Discipline:

Engineering - mechanical

Sector:

Energy

University:

Université de Sherbrooke

Program:

Accelerate

Intégration des technologies et thérapies associés aux soins de santé personnalisés (SSP)

Le secteur des soins de santé personnalisés (SSP) soulève de nombreux défis en matière d’adhésion, d’intégration et de réglementation. Il est alors nécessaire de faire l’état des défis et des enjeux concernant les SSP dans le système de santé.
Lorsqu’on parle d’intégration ou d’adhésion des SSP, on fait référence à leur utilisation par les professionnels de la santé et plus particulièrement par les médecins. Pour qu’une nouvelle technologie ou thérapie soit intégrée au système de santé, il faut qu’elle soit bien connue et bien comprise par les médecins. Ainsi, ils seront en mesure de l’utiliser en pratique courante. Cette intégration et cette adhésion sont d’autant plus facilitées par l’obtention du remboursement par les assureurs privés et par les assureurs publics. Le secteur public se fait via le régime d’assurance médicament du Québec (RAMQ). Pour obtenir le remboursement d’une nouvelle thérapie ou technologie, des agences d’évaluations des technologies doivent évaluer la valeur clinique et économique d’un produit. Ces agences se basent sur certains critères d’évaluation. Ils émettent ensuite une recommandation au ministre de la Santé et des services sociaux (MSSS) à savoir si oui ou non l’innovation devrait être remboursée par la RAMQ.

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Faculty Supervisor:

Jean Lachaine

Student:

Laurie Demers-Rozon

Partner:

GénomeQuébec Inc.

Discipline:

Pharmacy / Pharmacology

Sector:

Life sciences

University:

Université de Montréal

Program:

Accelerate

Towards an Intelligent and Secure 5G Ecosystem for the Transformation and Digitalization of Societies Through Artificial Intelligence

Artificial intelligence (AI) has transformed our way of perceiving and interacting with technology, by providing state-of-the-art solutions for challenging problems across the tech-spectrum. The main objective of this cluster of projects is to investigate, develop, adapt, integrate and evaluate state-of-the-art machine learning (ML) techniques, which are suitable for modeling and prediction using datasets collected for complex real-world telecommunications applications. Given the applications of interest for Ericsson Inc., we will focus on ML techniques:
1. to process complex operational data (time series or high dimensional) from real time large-scale wireless and IoT networks;
2. to enable intelligent decision making and data sharing and provenance, and modeling using technologies, such as blockchain, that can scale for real-time systems;
3. for lifecycle management of operating 4G and 5G wireless networks, by addressing the need for long-term deployment, self-profiling, and anomaly detection; and
4. to augment human-computer interactions for real-time decision in support of operation and management of large-scale industrial systems.
Training ML models in such cases typically leads to complex optimization problems, using massive amounts of noisy and incomplete training data.

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Faculty Supervisor:

Éric Granger;Marco Pedersoli;Chamseddine Talhi;Kaiwen Zhang;Georges Kaddoum;Kim Khoa Nguyen

Student:

Akhil Pilakkatt Meethal;Mohammad Bany Taha;Houda Khlifi;Djebril Mekhazni;Soufiane Belharbi;Paulo Freitas de Araujo Filho;Joao Victor de Carvalho Evangelista;Ha Vu Tran;Sahil Garg;Kanika Aggarwal;Bassant Selim;Alaeddine Chouchane;Wiem Badreddine

Partner:

Ericsson Canada

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

École de technologie supérieure

Program:

Accelerate

Production of cannabinoid in bioengineered microalgae

Plant natural products (PNP) are important resources for pharmaceutical and food industry. In the last decades, the market price of several PNP inflated because of the limited amounts produced in plants and the challenges in growing healthy crops. To overcome this problem, our team developed a multitool box of molecular methods to transform marine algae Phaeodactylum tricornutum.
Bioengineered microalgae are great candidates to manufacture PNP because of the relatively close behavior to plants’ compared to bioengineered bacteria or yeast. We designed and inserted genes encoding enzymes involved in cannabinoid biosynthesis. We succesfully detected the production of precursor molecules from the first part of the pathway. Now, we designed genetic constructions for the rest of the pathway to produce the final products i.e. cannabinoids. This project is a proof of concept of how microalgae could be used in pharmaceutical to encounter natural limitation of PNP. The aim to produce cannabinoids is the first step because of the trend after the law change in Canada, but the PNP could be also other therapeutic molecules of medical or nutritional importance such as Taxol or omega-3 fatty acids.

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Faculty Supervisor:

Isabel Desgagné-Penix

Student:

Fatima Awwad

Partner:

Algae-C

Discipline:

Biochemistry / Molecular biology

Sector:

Agriculture

University:

Université du Québec à Trois-Rivières

Program:

Elevate

Fine-grained Classification and Segmentation for Fashion Images

The detection, segmentation, and classification of clothes in fashion images is a well-addressed issue on deep learning research. The challenge is to achieve similar results using images taken from street and in-store sites. For such images, the variety of human positions and high diversity of clothes features decreases the results compared to the former tests. This project aims to investigate which image features and deep learning models can better execute garment detection, segmentation, and classification for in-store fashion images. The partner organization will have the opportunity to work with high qualified human resource with competence to execute high technology research. Additionally, the organization will contribute to the training of a worker in a real-life company environment thus with the capacity to act in the technology market.

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Faculty Supervisor:

Laurent Charlin

Student:

José Renato Villela Dantas

Partner:

Calixa Technologies Inc

Discipline:

Other

Sector:

Information and communications technologies

University:

HEC Montréal

Program:

Accelerate

Impact de la culture dans le développement local et social du quartier Centre-Sud, quartier des Faubourgs

L’étude que nous souhaitons mener déterminera de quelle façon la culture a une incidence sur le développement local et social du milieu du quartier Centre-Sud, quartier des Faubourgs. La présence d’artistes et d’organismes culturels est un élément essentiel à l’identité du quartier, mais aussi à son essor social et économique. La démarche permettra de mettre en évidence les dynamiques issues des initiatives portées par divers acteurs locaux, depuis la fin des années 2000, dont la mise en œuvre de projets culturels a été faite dans un objectif de développement local. Cette recherche deviendra un outil pertinent pour les différentes instances culturelles qui œuvrent dans le quartier, en leur permettant de comprendre les variables fondamentales du territoire et d’adapter leur offre en conséquence.

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Faculty Supervisor:

Juan Luis Klein

Student:

Wilfredo Arturo Angulo-Baudin

Partner:

Voies culturelles des faubourgs

Discipline:

Hospitality and tourism

Sector:

Information and cultural industries

University:

Université du Québec à Montréal

Program:

Accelerate

Intelligent Non-Person Agent to Play a Game

Creating a non-person character (NPC) to play a game is becoming increasingly important. NPCs can be used in quality assurance to test a game before sending the game for certification. Being able to test a game in a way that mimics a human player would allow the test to be more accurate and would help in discovering design and implementation errors resulting in time and cost savings. Recent research work reported in the literature have focused on skill-based games. Techniques such as Q-learning and reinforcement learning are well-suited to create NPCs for skill-based games where the outcome of a skill-based game depends on the NPC strategy. Such techniques cannot be used to generate an NPC to play a slot game since game outcomes are completely determined by a random number generator. In this project, we need to develop a generative NPC. To achieve this goal, we will first conduct a literature survey in order to select the most suitable techniques for developing the generative NPC. Second, the most promising techniques will be tested, and the results analyzed.

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Faculty Supervisor:

Moulay Akhloufi

Student:

Abdoulaye Oumar Ly

Partner:

IGT

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Université de Moncton

Program:

Accelerate

Data fusion strategies for reducing the uncertainty of point cloud data

For decades, contact probes on coordinate measuring machine (CMM) have been widely used for data acquisition in coordinate metrology, mainly because of their high accuracy. However, the acquired data is a low-density set of points, because sampling using a contact probe is a slow process. Nowadays, optical 3D scanning technologies such as structured-light scanners or laser scanners are increasingly included in metrology applications for rapidly capturing high-density point clouds enabling holistic measurements of a manufactured part. The recent 3D scanners can sample millions of coordinate data points from the part’s surface in just a few seconds. However, the accuracy of 3D scanners is about an order of magnitude lower than contact probes. The aim of this research project is to develop data fusion strategies for correcting the high-density 3D scanned point clouds using the low-density set of points measured by a contact probe, resulting in point clouds with reduced uncertainty.

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Faculty Supervisor:

Farbod Khameneifar;René Mayer

Student:

Aria Ghazavi

Partner:

Pratt & Whitney Canada

Discipline:

Engineering - mechanical

Sector:

Aerospace and defense

University:

École Polytechnique de Montréal

Program:

Accelerate

Comparaison des effets d’une stratégie d’apprentissage par problème avec les rétroactions vidéo sur la prise de décisions de jeunes hockeyeurs de 12 ans

Les meilleurs joueurs prennent la bonne décision, au bon moment et peu importe le contexte. Les habiletés de prise de décisions sont essentielles au développement du jeune joueur rêvant d’atteindre les sommets de son sport. En partenariat avec l’Académie Ulysse, le présent projet vise, pour commencer, à élaborer une approche par problème pour améliorer la prise de décisions de joueurs de hockey Pee-Wee. Ensuite, le projet prévoit comparer les effets de l’approche avec ceux des rétroactions vidéo traditionnellement utilisées par les entraîneurs. Puisque l’approche par problème place les joueurs dans des situations collaboratives où ils construisent eux-mêmes leur connaissances tactiques, l’hypothèse est l’apparition d’une meilleure rétention des habiletés de prise décisions suite à la participation à une approche par problème.

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Faculty Supervisor:

Claude Dugas;Jean Lemoyne

Student:

Julien Glaude-Roy

Partner:

Ulysse Académie

Discipline:

Physics / Astronomy

Sector:

Education

University:

Université du Québec à Trois-Rivières

Program:

Accelerate

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