Projets novateurs réalisés

Explorez des milliers de projets réussis issus de la collaboration entre organisations et talents postsecondaires.

31 620 projets complétés

2978
AB
5221
C.-B.
856
MB
696
NL
899
SK
9419
ON
9858
QC
98
PE
619
NB
1192
NS

Projets par catégorie

Assessing Risk for Hazardous Driving and Accident Propensity

Road safety affects everyone, and companies are looking for ways to identify the risk factors for their fleet drivers, and to reduce the chance of accidents. This project will build on Geotab’s existing methods for assessing driving risks, and develop new techniques to better identify risky drivers and risky behaviours. The project will focus on predicting a safety score that is more meaningful to fleet managers and more indicative of risky behaviours. The produced safety scores will help fleet managers decide which driver(s) are more at risk, and take appropriate actions accordingly.

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Superviseur du corps professoral :

Andrei Badescu;Sheldon Lin

Étudiant :

Partenaire :

Geotab Inc

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services; Transportation and warehousing

Université :

University of Toronto

Programme :

Accelerate

Design and development of a need analysis method based on cognitive mapping techniques

Analyzing needs is essential in any innovation project. A product/service should be designed and developed according to users’ needs so that it could be successful in the market and satisfy its users. However, it is not just the users who are interacting with a product. Designers, developers, project managers, business analysts and other stakeholders might be interacting with the product and will thereupon have needs to be considered. Thus, it is important to deeply analyze the needs and the interrelationships among them to empathize with users and stakeholders while detecting their points of conflict. Cognitive maps are powerful tools in visualizing enormous amounts of data in a network and combined with a data analysis method, they could act as a decision support for designers and developers in innovation projects. Hence, the main objective of this project is to propose a needs analysis method based on cognitive mapping acting as a decision support in the product/service development process.

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Superviseur du corps professoral :

Fabiano Armellini

Étudiant :

Partenaire :

Canadian National

Discipline :

Engineering

Secteur :

Transportation and warehousing

Université :

Polytechnique Montréal

Programme :

Accelerate

Better forecasting of weather-related operational shutdowns in forestry activities on Vancouver Island, British Columbia, Canada.

Forestry operations on Vancouver Island are carried out in a region of difficult, mountainous landscapes with very large amounts of rain and snow falling in the area. Heavy precipitation, especially liquid rain falling on snow, can cause not only landslides and floods, but water quality issues as well. These issues affect the environment, people, infrastructure, and the economy associated with the forestry industry. To reduce the risks of landslides and flooding to forestry workers and operations, the shutdown of logging operations during wet weather occurs when enough rain has fallen to meet a shutdown . However, these thresholds have not been standardized across BC, and certainly do not reflect important local conditions; this reduces the utility and accuracy of shutdown criteria. The objective of this project is to improve the guidelines for forest operation shutdown during storms that can trigger landslides and/or floods. By investigating the large-scale weather patterns that cause problematic weather, improvements to the shutdown decision-making process will be accomplished. Financial costs can be reduced while simultaneously improving the protection of people and infrastructure in the process.

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Superviseur du corps professoral :

David Atkinson

Étudiant :

Partenaire :

Mosaic Forest Management Corp

Discipline :

Earth science

Secteur :

Agriculture

Université :

University of Victoria

Programme :

Accelerate

Identifying Microaggressions Experienced by BIPOC Engineering Students across Higher Education in Ontario

Acknowledging that discrimination and prejudice of various sorts (e.g., verbal, behavioural, environmental) continue to exist in the education system, this research seeks to address how and why microaggressions against Black, Indigenous, and People of Colour (BIPOC), within engineering departments, show up among peers in classrooms, across interactions in lab environments, group-activities, and more. This research aims to shed light on the prevalence of these microaggressions as they appear in not only in-person learning, but rather, on how they have become embedded within virtual learning environments as well. With a focus on BIPOC in the engineering community, the research includes findings based on extensive literature review, 1-on-1 interviews, and Focus Groups. Further, the research will be carried out across higher education and across Ontario’s Society of Professional Engineers’ (OSPE) growing network of engineering students and alumni. OSPE has developed a four-point action plan to address systemic bias in the culture, training, and its licensure process. This Mitacs project will provide useful information for Diversity and Inclusion Task Force (TF) members, all of whom are Professional Engineers. As well, TF members can provide the Mitacs intern with insights and input that could benefit the research.

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Superviseur du corps professoral :

Medhat Shehata

Étudiant :

Partenaire :

Ontario Society of Professional Engineers

Discipline :

Engineering

Secteur :

Professional, scientific and technical services; Real estate and rental and leasing

Université :

Toronto Metropolitan University

Programme :

Accelerate

Project B: Support indication selection for HyperMabs’ developmental therapeutic by building translational rationale for target prevalence.

HyperMabs is a protein engineering company focused on the development of therapeutics for diseases with high unmet need including Covid-19.
The role of the Translational Science Team is to discover and develop biomarkers that indicate pharmacodynamic response to the company’s therapeutics as well as support the relevance of the targeted biological pathways in diseases of interest (indication selection).
The goal of the two MITACS projects within HyperMabs’ Translational Science Department is to develop and validate scientific methods (i) for sample collection to gain insight into pharmacodynamic biomarkers and (ii) to analyse the relevance of the company’s drug targets in a range of diseases. The results of the project will add value to the company’s ongoing efforts in rapidly developing drugs for serious diseases.

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Superviseur du corps professoral :

Elias Georges

Étudiant :

Partenaire :

HyperMabs Inc

Discipline :

Life Sciences

Secteur :

Professional, scientific and technical services

Université :

McGill University

Programme :

Accelerate

Project A: Feasibility study for the use of saliva samples to understand the Pharmacokinetic (PK)/Pharmacodynamic (PD) relationship for a developmental therapeutic

HyperMabs is a protein engineering company focused on the development of therapeutics for diseases with high unmet need including Covid-19.
The role of the Translational Science Team is to discover and develop biomarkers that indicate pharmacodynamic response to the company’s therapeutics as well as support the relevance of the targeted biological pathways in diseases of interest (indication selection).
The goal of the two MITACS projects within HyperMabs’ Translational Science Department is to develop and validate scientific methods (i) for sample collection to gain insight into pharmacodynamic biomarkers and (ii) to analyse the relevance of the company’s drug targets in a range of diseases. The results of the project will add value to the company’s ongoing efforts in rapidly developing drugs for serious diseases.

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Superviseur du corps professoral :

Elias Georges

Étudiant :

Partenaire :

HyperMabs Inc

Discipline :

Life Sciences

Secteur :

Professional, scientific and technical services

Université :

McGill University

Programme :

Accelerate

Application of a novel cryptographic filesystem to high-security domains

Aerial full-motion video, marine systems and space-based earth observation share key characteristics: they involve critical infrastructure, they rely on sensitive information and they require strong data provenance. We have applied cryptographic techniques — derived from both historic security protocols and newer blockchain systems — to create a novel research cryptographic filesystem in a previous Mitacs project, and now we will apply that filesystem to these three problem domains. This will require the development of new research ideas and new software based on cutting-edge tools and techniques, and it will enable us to secure critical data for the safeguarding of Canada and its interests. It will also position for future commercialization, generating significant economic activity in the high-tech, aerospace and marine systems sectors.

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Superviseur du corps professoral :

Jonathan Anderson

Étudiant :

Partenaire :

C-CORE

Discipline :

Engineering

Secteur :

Mining; Professional, scientific and technical services

Université :

Memorial University of Newfoundland

Programme :

Accelerate

Forestry Industry Sustainable Practices and Collaboration in the Howe Region

While the partner organization for this project is the Howe Sound Biosphere Region Initiative Society (HSBRIS), the intent of this project is to concurrently benefit Forestry companies working in the Howe Sound and Canadians as a whole as we strive in our commitment to the UNSDGs.
Bioshpere regions are mandated to promote SDGs, educate, and foster collaboration to make the region more sustainable. This project will directly help the HSBRIS fulfil these goals by bringing together stakeholders in the forest industry to learn about SDGs, share best practices and encourage collaboration to solve sustainability challenges. The Intern will compile a directory of Forestry Companies (harvesting, trucking, sorting, booming and silviculture) working in the Howe Sound Biosphere region, then gather information on best practices and industry challenges. Results and knowledge will be shared with all participants through stories of best practices, a formal report and an opportunity to gather socially (following COVID protocols).

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Superviseur du corps professoral :

Jane Raycraft

Étudiant :

Partenaire :

The Howe Sound Biosphere Region Initiative Society

Discipline :

Business

Secteur :

Other services (except public administration)

Université :

Capilano University

Programme :

Accelerate

Federated Learning for Language Models

The existing approach to building Machine Learning models includes gathering all the data from customers in one place and then running the training procedure using it. However, there are no guarantees personal data won’t be leaked by the one training the model. So, the customers face a difficult decision of either allowing companies to gather their data to improve the products or restrict information sharing to ensure privacy. In this project, we eliminate the need to make such a decision by developing a system that would analyze the customers’ data without them sending it anywhere. We employ Federated Learning techniques, which allows training machine learning models on the data but not allowing the company to see the data. Our system targets Natural Language Processing applications: one of the most privacy-sensitive yet highly demanded areas of Machine Learning. To further foster customers’ trust, we use additional privacy methods to ensure no information can be inferred from the communication between customers’ devices and the company’s servers.

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Superviseur du corps professoral :

Aleksandar Nikolov

Étudiant :

Partenaire :

Microsoft Canada

Discipline :

Computer science

Secteur :

Information and cultural industries

Université :

University of Toronto

Programme :

Accelerate

Geomorphic changes in Russell Creek Experimental Watershed following a record rain on snow event

Movement of sediment through landslide activities dominates sediment transport in headwater channels, and exerts a strong control on downstream channel morphology and aquatic habitat. Landslide and debris flow activity in headwater channels is controlled in part by the intensity of precipitation events. At Russell Creek Experimental Watershed on northern Vancouver Island, high resolution, remotely sensed (LiDAR) topographic data is available from both before and after a record rain-on-snow hydroclimatic event. This unique dataset, coupled with a dense weather station network through the watershed, presents a unique opportunity to examine the geomorphic impacts of a record runoff event on debris flows, landslides, and downstream channel and alluvial fan morphology. This research will develop mitigation strategies for hazardous debris flow features which frequently close a highway on Vancouver Island, and will contribute to a growing body of research on the links between climate, hydrology, land use, geomorphology and aquatic habitat.

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Superviseur du corps professoral :

Marwan Hassan

Étudiant :

Partenaire :

Forestry BC (Prince George)

Discipline :

Sociology

Secteur :

Sustainability & the Environment

Université :

The University of British Columbia

Programme :

Accelerate

Diverging from the GPUs: The case for alternative architectures for training ML algorithms

Machine learning has ushered many breakthroughs in areas such as computer vision, natural language processing, speech recognition, and recommendation systems. The models used in these applications contain many parameters that need to be learned and training often requires massive amounts of computation. As such in recent years graphics processor units (GPUs) have seen wide adoption for the training of these large-scale models. While there has been a lot of work on GPUs, little focus has been given to other architectures for machine learning. As such, this project plans to explore a series of architectures that diverge from the beaten path of GPUs through modeling and simulation on state-of-the-art machine learning workloads. The study aims to determine the trade-offs of the architecture in terms of performance to help better design machine learning accelerators.

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Superviseur du corps professoral :

Maryam Mehri Dehnavi

Étudiant :

Partenaire :

AMD Canada

Discipline :

Computer science

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Essential Technologies for Autonomous Systems: Theory, Verification, and Applications

Autonomous Unmanned Vehicles (AUVs) are systems that are capable of maneuvering in the air, on the ground, above or under the water. There are a number of potential applications for AUVs in civilian, military, and security areas and AUVs have great potential benefits to Canada for numerous reasons. This proposed Mitacs-Alliance project aims to advance some essential technologies (cooperative control of multiple autonomous vehicles; high-precision navigation and positioning; optimal motion planning and decision-making) for autonomous unmanned vehicles in applications, such as autonomous transportation, self-driving cars, collaborative mapping, etc. The successful development of these technologies will further contribute to maintaining Canada’s status as a leading research country in the area of autonomous unmanned vehicles, and will, in addition, translate into monetary benefits for the Canadian companies who participate in these areas. This project is also important for developing expertise and talent within Canada needed for the next phases of AUVs research and development. The proposed research has the potential to enable new innovative products and services, based on autonomous unmanned vehicles, to be developed and produced in Canada. That would bring benefits of economic expansion and innovation savings.

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Superviseur du corps professoral :

Jinjun Shan

Étudiant :

Partenaire :

Quanser Inc;York University

Discipline :

Engineering

Secteur :

Education

Université :

York University

Programme :

Accelerate

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Mitacs — Retour sur innovation

Mitacs est financé par le gouvernement du Canada, le gouvernement de l’Alberta, le gouvernement de la Colombie-Britannique, Research Manitoba, le gouvernement du Nouveau-Brunswick, le gouvernement de la Nouvelle-Écosse, le gouvernement de l’Ontario, Innovation PEI, le gouvernement du Québec, le gouvernement de la Saskatchewan, le gouvernement de Terre-Neuve-et-Labrador et le gouvernement du Yukon.