Innovative Projects Realized

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

31620 Completed Projects

2978
AB
5221
BC
856
MB
696
NL
899
SK
9419
ON
9858
QC
98
PE
619
NB
1192
NS

Projects by Category

Détection et modélisation 3D d’objets à partir de nuages de points LiDAR acquis avec des systèmes de télémétrie mobile selon une architecture sans serveur

Les cartographies et modèles urbains en 3D sont des représentations indispensables afin de visualiser et d’augmenter l’environnement dans les applications exploitées par des utilisateurs mobiles, qu’ils soient des professionnels (ex. ingénieurs civils, …) ou des citoyens. Les dernières années ont vu un développement remarquable des systèmes de télémétrie mobile (i.e. LiDAR), installés sur des véhicules terrestres, afin de répondre à de tels besoins croissants de données 3D de grands territoires à très haute résolution. Le présent projet vise à concevoir et développer une approche de traitement et gestion des données 3D acquises avec ces systèmes, depuis la réception des nuages de points jusqu’à la visualisation du modèle 3D. L’approche envisagée exploitera l’intelligence artificielle et les réseaux de neurones profonds. Ce projet permettra au partenaire de renforcer ses capacités à proposer des cartographies HD de l’environnement urbain et des services dans les domaines de la conduite autonome et des jumeaux numériques.

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Faculty Supervisor:

Thierry Badard;Sylvie Daniel;Sylvie Daniel;Thierry Badard

Student:

Partner:

Jakarto

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Université Laval

Program:

Accelerate

Infrastructure Corrosion Assessment Magnetic Method (iCAMM) technology for macro and micro defect detection of rail track

Because of the usefulness of non-destructive testing in the assessment of different types of materials, they have attracted widespread interest in the last years. Non-destructive testing (NDT) is a descriptive term used for the examination of materials and components in such a way that allows materials to be examined without changing or destroying their function. NDT plays a crucial role in everyday life and is necessary to assure safety and reliability. For instance, they are widely used in detecting defects in steel rebar in reinforced concrete. The main goal of this project is to go further and reach a NDT way to evaluate macro and micro defects on the rail road. The proposed technology is based on a Passive Magnetic Inspection (PMI) .A passive method means there is no direct magnetic field generated and applied, nor is there any electrical current passed through the system (i.e., the rail track).

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Faculty Supervisor:

Shunde Yin;Giovanni Cascante;Maurice Dusseault

Student:

Partner:

InspecTerra Inc.

Discipline:

Engineering

Sector:

Transportation and warehousing

University:

University of Waterloo

Program:

Accelerate

Conception et optimisation d’un laser à fibre haute puissance (kW) intégrant un réflecteur de pompe multimode

Sans que la plupart d’entre nous ne le sachent, les lasers sont devenus des parties intégrantes de notre réalité. Ils se retrouvent dans des biens de consommation de la vie de tous les jours, mais ils ont surtout de nombreuses applications industrielles. Parmi les différents types de lasers, le laser à fibre optique se démarque pour des raisons de robustesse, de performance, de coût et de facilité d’utilisation. L’objectif de ce projet est de concevoir et d’optimiser un laser à fibre haute puissance (kW) intégrant un réflecteur de pompe novateur pour en améliorer les performances. L’intérêt premier de TeraXion Inc. réside dans le développement, la démonstration et la commercialisation de composants photoniques innovants basés sur la technologie des réseaux de Bragg, et offrant le potentiel de réduire le coût des systèmes lasers à fibre haute puissance tout en augmentant leur efficacité

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Faculty Supervisor:

Martin Bernier

Student:

Partner:

TeraXion Inc (Québec, QC)

Discipline:

Physics

Sector:

Manufacturing

University:

Université Laval

Program:

Accelerate

La ruelle bleue-verte comme modèle de gestion durable des eaux pluviales et composante d’une ville résiliente: une étude de la création de valeur, à l’échelle locale et municipale, dans une perspective de cycle de vie et une approche de monétisation

Avec les changements climatiques, il est attendu que les pluies seront plus abondantes (Alliance des ruelles bleues-vertes, 2018), ce qui risquerait d’engorger les systèmes municipaux de gestion de l’eau, qui subissent déjà une pression dans les centres urbains (Bruebach, 2019), notamment à Montréal. Or, ce projet s’intéresse au concept de ruelle bleue-verte comme infrastructure pour gérer les eaux pluviales des quartiers montréalais et les détourner des systèmes municipaux. La ruelle bleue-verte détourne les eaux récupérées sur les toitures résidentielles pour les faire percoler à travers un parcours notamment végétal. Cette recherche utilise la méthodologie de l’analyse de cycle de vie, qui mesure les impacts potentiels d’un produit ou d’un service, de la conception à la fin de vie. Ce projet tente aussi d’associer une valeur monétaire aux impacts sociaux et environnementaux potentiels de telles installations innovantes, pour vérifier s’il s’agit d’une solution intéressante pour bâtir une ville résiliente.

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Faculty Supervisor:

Cécile Bulle

Student:

Partner:

Les Ateliers Ublo

Discipline:

Sociology

Sector:

Sustainability & the Environment; Water; Environmental Science and Technology

University:

Université du Québec à Montréal

Program:

Accelerate

Alternative Values Analysis and Cumulative Impacts Assessment in Clayoquot Sound

The research would look at the amount of revenue that would be lost by not harvesting timber from
sensitive areas in the Clayoquot sound region . It would also look at the viability of using non timber
products as a substitute for timber harvesting. Currently the non timber products under consideration
are Carbon Offsets, Resorts that would encourage eco tourism and Cultural tourism. This research
intends to provide the First Nations communities located in the Clayoquot Sound reg ion with data to
make informed decisions on their land use.

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Faculty Supervisor:

Tom Lawrence

Student:

Partner:

Ecotrust Canada

Discipline:

Business

Sector:

University:

Simon Fraser University

Program:

Accelerate

Retail Supply Chain Predictive Analytics

The project aims predict the demand of customers for small and medium size businesses. Forecasting models will be developed analyze historical data to understand patterns and correlations. Machine learning will be applied to determine how the accuracy can be improved over existing statistical methods, such as Fourier Regression Analysis which is commonly used in retail demand chain management. The demand forecasting model will examine customer behavior and the context surrounding that behavior, including upcoming holidays, the weather, or a recent event such as COVID-19. The key benefit of the project is to help business better navigate many challenges due to demand uncertainty. In particular, it will support businesses to develop effective strategies to improve the management of resources.

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Faculty Supervisor:

Jing Chen;Michael Zhang

Student:

Partner:

Analyticy Technologies;Flashana Technologies Inc

Discipline:

Business

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

Dalhousie University; Saint Mary's University

Program:

Accelerate

Investigations into the mechanism of action and potential in idiopathic pulmonary fibrosis of the novel ruthenium based therapeutic BOLD-100

Idiopathic pulmonary fibrosis (IPF) is a chronic and fatal disease lung disease with unknown cause. There are limited treatment options for IPF and investigations into new treatment options is needed. BOLD-100 is a clinical-stage small molecule that is currently being investigated as a treatment option in oncology and viral infections. The pathway that BOLD-100 impacts, the unfolded protein response, is important in IPF and therefore this project’s objective is to use preclinical models to test whether BOLD-100 can affect development of IPF. The interns will gain experience using a range of different models to test an industry backed compound and will interaction with industry veterans at the partner organization, Bold Therapeutics. Bold Therapeutics will benefit by utilizing the expertise of the Ask laboratory to potentially expand the potential of BOLD-100 into IPF.

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Faculty Supervisor:

Kjetil Ask

Student:

Partner:

Bold Therapeutics

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

McMaster University

Program:

Accelerate

Development and Validation of a Protein-Protein Interactions Modeling Platform for Rapid Affinity Predictions and Pharmaceutical Applications

Developing a drug for new diseases cannot only be challenging but also time consuming. From the identification of a druggable target to a compound which can improve a condition it usually takes more than 12 years. Since there is basically an infinite number of possible compounds which can be turned into a drug it is literally the problem of finding a needle in a haystack. The trial and error method of making molecules in the laboratory and testing their efficiency has been proven successful for over a century. However, with ever growing numbers of druggable molecules, diseases and classes of drugs, this traditional workflow has become too time consuming. Efficient computer models can help rationally pre-select a much smaller number of potential drug candidate compounds which can then selectively been tested. This internship aims at testing and enhancing the predictability of a computational tool capable of guiding the development of a new emerging class of drugs, stimulating the human immune system. These drugs, called antibodies, can cure the condition by finding and interacting with their target.

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Faculty Supervisor:

Gilles Peslherbe

Student:

Partner:

Chemical Computing Group

Discipline:

Life Sciences

Sector:

Information and cultural industries

University:

Concordia University

Program:

Accelerate

Deployment of motion platform control architecture for a high-fidelity driving experience in simulators

Realistic driving experience in motion simulators is a key element for the impressiveness of the VR based simulators. In the driving simulator the free motion of the vehicle is mapped to a motion platform with limited workspace by filtering out the motion and scaling it down with a motion cueing algorithm. These algorithms should be designed in such a way to give a feeling to the users as if they are driving a real vehicle.
The output of the previous stage needs to be fed to actuators of a simulator so that they can apply the required forces and torques to the system to generate the desired motion cues to the user. However, these forces are felt by the user in terms of accelerations and the media between the user and the actuators is the structure and dynamics of the simulator. Therefore, one needs to know the model of the simulator. Then, there is a need to interpret these desired feelings by the user in terms of the actuator forces and motor torques which are obtained by a set of secondary control filters. Therefore, we need to first identify a mathematical model of the platform and tune its parameters.

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Faculty Supervisor:

Amir G. Aghdam

Student:

Partner:

Touché Technologies

Discipline:

Engineering

Sector:

Manufacturing

University:

Concordia University

Program:

Accelerate

Diagnostics and Explainable Machine Learning Models

Despite the advances of Machine Learning, the models are still being considered black-boxes that are difficult to diagnose and explain. The model performance diagnostic measures are critical to the assessment of the model’s relevance, accuracy and robustness. Good models’ performance is the primary enabler of their successful deployment in real-life applications. However, even if the models perform well, it is not known why the models predict the way they do, that is, which input variables are responsible for the models’ predictions. The purpose of the research is two-prone: 1) to identify the relationship between the measures of model performance and recommend which measures should be used in the model production environment, and, 2) develop the methodology of explaining machine learning models in terms of the models’ inputs, as well as, other, potentially relevant, variables, not selected in the model.

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Faculty Supervisor:

Jia Yuan Yu

Student:

Partner:

Daesys Inc.

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Concordia University

Program:

Accelerate

Génération de modèles 3D humains à partir d’images 2D et de nuages de points

L’objectif principal est de mettre à disposition de notre partenaire industriel Bodyform3D des outils informatisés innovants afin d’améliorer et d’enrichir leurs technologies (plateforme d’acquisition et de modélisation 3D) pour répondre à des besoins dans le domaine médical avec une application pour le traitement en urgence des grands brûlés ou pour la mensuration de sujets pour la génération d’avatars.

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Faculty Supervisor:

Carlos Vazquez;Jacques de Guise;Eric Paquette;Carlos Vazquez

Student:

Partner:

Bodyform3D

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

École de technologie supérieure

Program:

Accelerate

Small molecule agonists of SHIP1 for treatment of inflammatory disease

Activation of the immune system is necessary for defense against pathogens and injury, but just as important are the processes to turn this inflammatory response once the infection or injury has been resolved. Inappropriate prolongation of immune cell activation results in inflammatory diseases such as inflammatory bowel disease, asthma and arthritis. The University of British Columbia (UBC) partners in this project have previously shown that activating the intrinsic braking system in cells, a protein called SHIP1, using small molecule compounds can reverse inflammation. We propose to optimize the chemical and biological property of these compounds so that they can be tested in humans for treatment of inflammatory disease. ZebraPeutics Inc has license these compounds from UBC to support their development and subsequent testing in human clinical trials. The work proposed in this application will support this goal.

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Faculty Supervisor:

Raymond Andersen;Alice Mui

Student:

Partner:

ZebraPeutics Inc.

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.