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

Modélisation technico-économique électrique et hydrogène pancanadienne

De plus en plus de stratégies nationales de développement hydrogène voient le jour, et dans ce cadre, Artelys participe à un projet de recherche porté par un consortium international dont il fait partie « Hydrogen and Climate Partnership » (H2CLIP). Le projet vise à modéliser et étudier le future de l’économie de l’hydrogène, et plus particulièrement les échanges possibles entre le Canada et l’Allemagne au regard des objectifs économiques, écologiques et de sécurité d’approvisionnement.
Le stage qui s’inscrit dans ce projet R&D s’articule en deux parties. La première partie consiste à participer au développement du modèle électrique canadien déjà existant dans le logiciel Artelys Crystal. La deuxième partie consiste à modéliser des actifs de production d’hydrogène dans le même logiciel en s’appuyant sur une revue de littérature de l’état de l’art des technologies reliées à l’hydrogène.

View Full Project Description
Faculty Supervisor:

Hanane Dagdougui

Student:

Partner:

Artelys Canada

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Polytechnique Montréal

Program:

Accelerate

Modern LLVM mapping of sequential code to task-/data-flow models

The high-level goal is to develop technology to enable more C++ applications to run well on many-core architectures such as recent AMD CPUs, GPUs, and combinations thereof (APUs). We expect to improve the capabilities of compilers like clang/LLVM to identify task-level parallelization opportunities that are not able to be identified today.

View Full Project Description
Faculty Supervisor:

Angela Demke Brown

Student:

Partner:

AMD Canada

Discipline:

Computer science

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Singing to be Heard: Understanding the social, geographic, and anthropogenic factors that influence the development of humpback whale song on Canada’s North Pacific coast

Humpback whales produce stereotyped, socially learned songs on their breeding grounds, yet little is known about song development outside the breeding season, or the effects of increased vessel traffic on humpback whale communication. With access to an extensive underwater Passive Acoustic Monitoring network along Canada’s BC coast, facilitated by the North Coast Cetacean Society and Raincoast Conservation Foundation, the intern will analyze humpback song during the feeding season recorded across multiple sites over years. The intern will explore the variation of humpback song across the feeding season, and the impact of singers’ vocal interactions and vessel noise on humpback whale song. Our findings will be relevant to other whale populations facing increases in anthropogenic noise, and other marine animals that rely on long-distance acoustic signals. The project aligns with the values of both partner organizations, advancing knowledge, informing conservation measures, and protecting the ecosystems and at-risk marine mammals of coastal British Columbia.

View Full Project Description
Faculty Supervisor:

Daniel Mennill

Student:

Partner:

Raincoast Conservation Foundation;North Coast Cetacean Society

Discipline:

Life Sciences

Sector:

Other services (except public administration); Professional, scientific and technical services

University:

University of Windsor

Program:

Elevate

Identifying potentiators for improved adeno associated virus based gene therapy for the central nervous system

Gene therapies are revolutionizing medicine, providing new therapeutics for diseases that previously were untreatable. In the central nervous system in particular, gene therapies hold great promise for saving lives and improving the quality of life of children and aged patients. The most common form of gene therapy that is used to treat patients involves the use of a virus deliver the gene of interest. However, getting enough into the cells of the patients is difficult, and represent a significant challenge to creating more life saving gene therapies. Here we are testing how drugs, called vector potentiators (VEPOs™), can be used to improve viral delivery of genes to the central nervous system, providing a platform for the further development of gene therapies.

View Full Project Description
Faculty Supervisor:

Cindi M Morshead

Student:

Partner:

Stem Cell Network;Virano

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Dispositif de formation pédagonumérique sur la cyberdépendance au secondaire à l’aide de technologies innovantes

Il existe un vide de connaissances scientifiques autour de l’utilisation des hologrammes et de la réalité virtuelle à des fins pédagogiques, notamment pour l’enseignement au secondaire. À l’inverse, les savoirs débordent sur les impacts relatifs à une utilisation excessive des écrans chez les adolescents, mais peu d’étude tente de les contrer par une mobilisation concrète. Le caractère innovant de ce projet relève ainsi de l’élaboration d’une formation destinée à sensibiliser les élèves du secondaire sur le thème de la cyberdépendance à l’aide de ces technologies. Ce projet implique une étroite collaboration entre les partenaires et l’équipe de recherche pour planifier et développer cette formation ainsi qu’un modèle de formation. En ce sens, nous avons pour objectifs d’analyser l’état de la recherche sur la cyberdépendance, d’explorer les différentes utilisations des dites technologies, et de collaborer à la planification et au développement de la formation et du modèle de formation selon les intentions du projet.

View Full Project Description
Faculty Supervisor:

Matthieu Petit

Student:

Partner:

Productions Six et Deux;Immersia Studio

Discipline:

Sociology

Sector:

Arts, entertainment and recreation

University:

Université de Sherbrooke

Program:

Accelerate

Advancing Generative Models for Vision and Language: A Collaborative Study with ServiceNow Research and ÉTS Montréal

This research project, a collaboration between ServiceNow and ÉTS Montréal, aims to improve generative AI (e.g. artificial intelligence models that learn to generate data), which can impact various creative and knowledge-based industries like graphic design, content creation, and research. The project aims to create advanced generative models that can generate a variety of data types, such as images, code, and language. By understanding the connections between these different data modalities, the AI systems developed will be able to better comprehend and adapt to human needs. This research focuses on producing more intelligent AI solutions that can seamlessly create and manipulate various forms of data while aligning with human preferences and requirements. By incorporating humans in the AI development process, the project aims to create AI systems that better align with how people perceive the world. This research will use cutting-edge methods and contribute to the scientific community while training a skilled research scientist and strengthening Canada and Montreal’s position in the AI ecosystem.

View Full Project Description
Faculty Supervisor:

Marco Pedersoli

Student:

Partner:

ServiceNow Canada

Discipline:

Computer science

Sector:

Artificial Intelligence; Information and Communications Technology; Technology

University:

École de technologie supérieure

Program:

Accelerate

Large-scale turbulent/turbulent entrainment of mass and momentum in planar wakes

Turbulent entrainment denotes the spatio-temporal process by which turbulent flows expand by incorporating ambient fluid into the primary turbulent flow, e.g., the growth of a volcanic plume with distance from the crater or growth of a jet of pollutants being discharged into the atmosphere or hydrosphere. This research aims to investigate the effects of free-stream turbulence on the large-scale entrainment (engulfment) of mass and momentum into the canonical turbulent wake produced by a cylinder, using simultaneous planar laser-induced fluorescence (PLIF) and particle image velocimetry (PIV) measurements. The wake region will be marked with a passive scalar that faithfully tracks the motion of the flow within the wake. Engulfed fluid can be identified as pockets of ambient fluid (regions of low scalar concentration) within the boundaries of the wake from the PLIF images. The entrained mass and momentum in these pockets are subsequently estimated using the velocity data, provided by the PIV technique. This will, for the first time, shed light on the role of engulfment in wakes subjected to a turbulent background, as compared to a quiescent ambient…

View Full Project Description
Faculty Supervisor:

Susan Gaskin

Student:

Partner:

Imperial College London

Discipline:

Engineering

Sector:

Education

University:

McGill University

Program:

Globalink Research Award

Generation of a remote sensing methodology for the identification and variable chemical control of weeds with ground equipment in sugarcane

The proposed project intends to generate a method for identifying weeds and develop site-specific weed control prescriptions for sugarcane cultivations in Costa Rica using Remote Sensing techniques. Remotely sensed data will be captured using multispectral camera and LiDAR sensors attached to Remotely Piloted Aircraft Systems (RPAS). Images will be processed using machine learning algorithms to characterize the weed type and how it emerges during the early stages of sugarcane cultivation. Results will be evaluated using field samples. Once the variety of weeds and the emerging patterns identify, site-specific, variable-rate chemical solutions or prescriptions will be developed and fed into ground machines for spraying.

View Full Project Description
Faculty Supervisor:

Muditha Heenkenda

Student:

Partner:

National University of La Plata

Discipline:

Engineering

Sector:

Environmental Science and Technology; Artificial Intelligence; Agriculture and Food

University:

Lakehead University

Program:

Globalink Research Award

Projet CCP : Cohabitation cyclistes-piétons sur les rues piétonnes : PARTIE 2

Pour répondre aux besoins des citoyens (mobilité, loisirs, activités sociales) en respectant les impératifs de distanciation physique, la Ville de Montréal et ses arrondissements ont implanté à l’été 2021 des rues piétonnes sur des artères commerciales, donc deux ont proposé des projets-pilotes de cohabitation des piétons avec les cyclistes (Avenue du Mont-Royal et rue Wellington). L’objectif du présent projet est de documenter cette cohabitation et d’en évaluer la sécurité (pour les piétons et les cyclistes) et l’acceptabilité sociale. Les analyses qualitatives et quantitatives qui seront effectuées dans le cadre de ces stages permettront de mieux comprendre la cohabitation entre les piétons et les cyclistes dans ces nouveaux espaces qui leur sont dédiés et d’ainsi proposer des améliorations à appliquer dans les prochaines années, sur ces deux rues ou sur d’autres qui voudraient adopter la cohabitation.

View Full Project Description
Faculty Supervisor:

Marie-Soleil Cloutier;Nicolas Saunier;Francesco Ciari

Student:

Partner:

Ville de Montréal

Discipline:

Sociology

Sector:

Arts, entertainment and recreation; Public administration; Utilities

University:

Polytechnique Montréal; Université du Québec : Institut national de la recherche scientifique

Program:

Accelerate

Machine learning aided accelerated design and characterization of automotive composites

The proposed research project involves developing machine learning models to predict the mechanical properties of polymer composites. The interns will collect and preprocess data from various sources including open-source databases and conducting extensive experimental tests, build artificial neural network (ANN) models using advanced algorithms, and validate the accuracy of these models using test data. The expected benefit to the partner organization, Magna Closures, is the development of accurate and reliable models that can predict the behavior of polymer composites under different conditions, such as tensile tests and creep tests. These models can be used by the partner organization to optimize material selection and design, reduce testing costs, and improve the overall performance of polymer composites in various applications in automotive applications.

View Full Project Description
Faculty Supervisor:

Reza Rizvi

Student:

Partner:

Magna

Discipline:

Engineering

Sector:

Manufacturing; Wholesale trade

University:

York University

Program:

Accelerate

Learning GPU Code structure using Transformers for Translation and Performance Optimization

This research project aims to improve the performance of GPUs, which are important for running machine learning algorithms. GPUs are a fundamental architecture in machine learning, and this project will use transformer-based models to learn the program structure of GPU kernels for various downstream tasks like performance projection and metrics such as GPU utilization. The research will also potentially allow bidirectional translation from assembly to source code, significantly improving code optimization and generation. The proposed research has the capacity to significantly improve code optimization and generation, leading to more sustainable and efficient practices and will also be beneficial to society for reducing the carbon footprint by reducing the number of optimizations runs.

View Full Project Description
Faculty Supervisor:

Maryam Mehri Dehnavi

Student:

Partner:

AMD Canada

Discipline:

Computer science

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Efficient Avatar Generation from Arbitrary Images

AR/VR may be the next frontier for online human communications and interactions. The ability to produce photorealistic avatars dramatically improves the feeling of immersion and connection in applications utilizing AR/VR. However, current methods of face capture are time-consuming and involve expensive cameras and sensors. In this project, we explore deep learning methods for generating face avatars using arbitrary images of a subject acquired on inexpensive consumer cameras, such as smartphone selfies, from various viewing angles and at different instances. Furthermore, the attributes of the generated avatars can be edited and animated. The project’s success will provide the partner organization with capabilities allowing it to build a new innovative product in the AR/VR space.

View Full Project Description
Faculty Supervisor:

Karan Singh

Student:

Partner:

AMD Canada

Discipline:

Computer science

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Previous
1…944945946947948949950…2,513
Next

Join a thriving innovation ecosystem.

Subscribe to our newsletter now!

Subscribe