Innovative Projects Realized

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

29670 Completed Projects

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Projects by Category

Feedback mechanisms in Extended Reality Applications

The objective of this research project is to combine different forms of user feedback mechanisms (haptic, olfactory, force, auditory) to better recreate simulated environments and increase the impact of extended reality (XR) training platforms for both users and collaborative robots. As such the research question that is being investigated during the research project is: How do feedback mechanisms impact knowledge transfer of XR applications? The intern will be responsible for supporting the current research in extended reality. Specifically, the intern will assist in creating physical models and prototypes for XR experiences. They will extend the current VR platform used in the training of machinery operators to include new forms of feedback and determine their effectiveness. From this research we expect to gain new knowledge on how feedback mechanisms help with knowledge retention and user performance of VR training platforms.

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Faculty Supervisor:

Tsz Ho Kwok

Student:

Partner:

Politecnico di Milano

Discipline:

Engineering

Sector:

Education

University:

Concordia University

Program:

Globalink Research Award

Tunable Topological Features in Microring Arrays

Topological features can arise when you combine materials or lattices of different configurations at the interface. Individual
elements of the lattice can be engineered to select modes which do not propagate into the rest of the system (by splitting them),
and the rest would be able to, using Floquet optical ring resonators.
We propose to study a different scheme of a photonic topological insulator, one which would allow us to tailor which modes are
protected by topology, and which ones are not. In essence, this could be akin to changing discretely between one kind of system
(i.e, an insulator) to another (a conductor). This would allow us to effectively change the system’s behavior without changing the
geometry in real-time, relying only on the wavelength of the selected mode(s).

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Faculty Supervisor:

Pablo Bianucci

Student:

Partner:

University of Maryland

Discipline:

Physics

Sector:

Quantum Science

University:

Concordia University

Program:

Globalink Research Award

Socio-economic inequalities in longevity indicators in Belgium since the 1990s

We will use the recently developed Belgian indices of multiple deprivation (BIMDs) in combination with all-cause and cause-specific mortality data to investigate the SE inequalities in longevity indicators. Our main goal is to compare the levels and trends of life expectancy, median and modal ages at death across geographical areas in Belgium with different deprivation levels, measured by the BIMDs. Our findings will reveal the absolute and relative differences in these three indicators between and within the Belgian areas with different deprivation levels, and show us their trends since the year 1991. As the recent gains in longevity are mostly due to lower mortality at the higher ages, studying the past trends in modal age at death by the major causes of death can reveal signs of deceleration of acceleration, suggesting either future longevity gains or losses.

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Faculty Supervisor:

Nadine Ouellette

Student:

Partner:

Université Catholique de Louvain

Discipline:

Sociology

Sector:

Education

University:

Université de Montréal

Program:

Globalink Research Award

Prosocial development across childhood

Prosocial behavior is essential for a functioning society. Although studies show an early onset of prosocial behaviors, there is no
comprehensive theory on its development and underlying mechanisms. The visit to Dr Dunfield’s lab, which will be made possible with the help of the GRA, is embedded in a superordinate research project with the goal to decipher the mechanisms of early prosociality in preschool children. This project examines the prosocial tendencies of three- to seven-year-old children in terms of actual behavior, underlying norms, and empathic concern. In addition, a number of cognitive and motivational factors that are theorized to predict prosociality will be assessed. At the end of the visit, the interns hope to identify key influences that account for interindividual differences in the performance of prosocial actions. Improving the current understanding of the development of prosociality will benefit both basic research and society at large by providing a starting point for deriving interventions to promote cooperative behavior.

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Faculty Supervisor:

Kristen Ann Dunfield

Student:

Partner:

Ludwig-Maximilians-Universität München

Discipline:

Sociology

Sector:

Education

University:

Concordia University

Program:

Globalink Research Award

Computational analysis of the impact of varying cathode catalyst layer microstructural parameters on transport properties

Anthropogenic greenhouse gases and aerosols resulting from the combustion of fossil fuels to power our current energy systems are the leading cause of climate change and pose human health risks, especially in urban areas. Hydrogen proton exchange membrane fuel cell (PEMFC) electric vehicles offer the opportunity to displace the internal combustion engine from medium- and heavy-duty applications. PEMFC electric vehicles already offer most of the capabilities that customers expect, such as quick start-up and refueling, long range, and high efficiency, however, research is still needed to decrease their cost and increase durability. At the heart of any PEMFC is the catalyst layer (CL), a 5 to 20 micrometer heterogeneous layer where the electrochemical reactions take place. Improving transport in this layer could result in increased power density, thereby decreasing cost, and durability. Due to its dimension and the fact that this layer is sandwiched inside other layers, direct ex-situ and in-situ measurements of transport parameters are very challenging and time consuming. The aim of this project is to develop computational analysis tools to study transport property variations with composition and mesoscale structure based on electron microscopy and stochastic reconstruction images of CLs.

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Faculty Supervisor:

Marc Secanell

Student:

Partner:

Ballard Power Systems Inc

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Alberta

Program:

Accelerate

Syntell : Contrôle qualité automatique de grains

L’agriculture est un domaine important pour la societe. En ce sens, l’intelligence artificielle vient de plus en plus aider les agriculteurs avant, pendant ou apres les recoltes, notamment pour le controle des grains qui est une etape importante apres la recolte pour assurer un grain de qualite. Le projet de stage propose par Syntell, en partenariat avec Agri-Marche, a comme objectif d’effectuer un controle qualite automatique des grains lors de leurs passages sur un convoyeur. Cela dit, ce controle qualite implique d’etre en mesure de segmenter et de classifier chacun des grains en temps reel. Ce projet permettra a Agri-Marche d’automatiser leur controle qualite sur plusieurs chaines de production, diminuant ainsi leurs coats variables.

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Faculty Supervisor:

Christian Gagné;Philippe Giguère

Student:

Partner:

SYNTELL

Discipline:

Computer science

Sector:

Information and cultural industries

University:

Université Laval

Program:

Accelerate

SBQuantum : Méthodes de compensation avancées pour intégration d’un magnétomètre quantique à des plateformes de déploiement

Derrière tout système de navigation, la carte planétaire du champ magnétique terrestre est à la base de l’attitude et de l’orientation des véhicules. Cependant, le champ terrestre évolue dans le temps et doit être mis à jour aux cinq ans afin de préserver une bonne précision de ces systèmes.
SBQuantum développe une solution de magnétométrie satellitaire basée sur un magnétomètre quantique à base de diamant et des algorithmes de traitement évolués fusionnant les entrées de multiples capteurs auxiliaires.
Le défi est de mesurer le champ magnétique terrestre avec une précision inférieure à une partie par million dans l’environnement magnétique contaminé d’un microsatellite. Ce projet vise à développer des méthodes d’apprentissage automatique afin d’utiliser les capteurs auxiliaires pour entraîner un modèle de compensation dans des infrastructures de calibre mondial.

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Faculty Supervisor:

Christian Gagné;Denis Laurendeau

Student:

Partner:

SB Quantum

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Université Laval

Program:

Accelerate

Hypoxia severity impacts on cortical activity in moderate to severe OSA patients

Obstructive Sleep Apnea (OSA) is an important respiratory disease characterized by recurrent blockages of the throat (‘upper airway’) during sleep. These blockages result in short lapses in breathing. The low oxygen levels and disruption of sleep caused by OSA contribute to many problems including: sleepiness, poor quality of life, awakenings during sleep, hypertension, heart disease, strokes, and dementia. OSA is usually diagnosed by a ‘sleep study’: patients stay overnight in the hospital and many biologic signals (i.e., brain wave patterns, heart rate, oxygen levels, breathing effort) are collected over 8 or more hours. The severity of OSA is usually measured by the apnea-hypopnea index (AHI), which is the number of times the throat closes or narrows per hour of sleep. However, the AHI does not predict symptoms of health outcomes of sleep apnea well. We believe that new ways of looking at the information collected during sleep studies might help predict what problems someone with OSA will have. The purpose of this project is to apply advanced computer techniques to information collected from a large group of patients with sleep apnea in order to develop tools that can better predict brain function in patients with sleep apnea.

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Faculty Supervisor:

Najib Ayas

Student:

Partner:

Legacy for Airway Health

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology

University:

The University of British Columbia

Program:

Accelerate

Heuristiques pour la gestion des créneaux horaires de livraison

L’objectif général de ce projet est le développement d’heuristiques à la fine pointe des connaissances actuelles pour des problèmes de gestion de créneaux horaires de livraison (PGCHL). L’objectif de telles problématiques est de proposer un ensemble des créneaux horaires à offrir dans chaque zone prédéfinie de la région de livraison ainsi que le plan de livraison associé. Cette solution se doit d’offrir un niveau de service acceptable dans chaque zone et doit également être en mesure de réduire les coûts de livraison. La modélisation des PGCHL donne lieu à des formulations présentant des défis méthodologiques considérables et qui ont été peu traitées dans la littérature. Le produit de ce projet permettra à l’entreprise Clear Destination de mettre à disposition des entreprises de commerce de détail la commerce de détail la technologie de gestion des créneaux horaires de livraisons. Cette nouvelle fonctionnalite sera en mesure m’accroitre la competitivite de ces entreprises et supportera l’expansion du commerce electronique qui est un des segments qui connait la plus forte croissance actuellement.

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Faculty Supervisor:

Michel Gendreau

Student:

Partner:

Clear Destination

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

École Polytechnique de Montréal

Program:

Accelerate

Individual identification using sleep micro-architecture

Brain fingerprinting is an emerging technique that has significant potential in leveraging individual differences for the improved prediction of behaviour (e.g. memory) and clinical (e.g. neuropsychiatric) outcomes. There is evidence suggesting that certain phenotypes of sleep might be markedly trait-like, however the uniqueness of sleep architecture and microarchitecture underlying the neurophysiological activity during the sleep state has yet to be assessed in a comprehensive manner. During this project, the intern will investigate sleep microarchitecture and individual variations in automatically detected events such as slow oscillations and sleep spindles to understand their potential in predicting behavioural features such as memory consolidation.

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Faculty Supervisor:

Thien Thanh Dang-Vu

Student:

Partner:

University of Oxford

Discipline:

Life Sciences

Sector:

Life Sciences (not health); Other

University:

Concordia University

Program:

Globalink Research Award

Theory Guided Machine Learning Process Modeling of in-situ Automated Fiber Placement

Current manufacturing processes for fiber-reinforced polymer composite materials are slow and rely heavily on manual intervention for quality control. The in-situ manufacturing of thermoplastic composites using Automated Fiber Placement (AFP) eliminates secondary thermal processing, which leads to decreased manufacturing times and cost. However, to reach an industrial implementation, we must improve our understanding of the non-linear and complex relationships that exist between all process parameters. Hence, optimization of the manufacturing process can be achieved by determining the relationships between process conditions (e.g., temperature, pressure, lay-up speed) and the final part quality. To address this knowledge gap, the proposed research project will develop a data-driven model using Theory Guided Machine Learning. The data-driven model will predict the temperature history achieved during AFP manufacturing using experimental data. The developed model can be exploited for more efficient control of the AFP process resulting in improved part quality and increased throughput.

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Faculty Supervisor:

Farjad Shadmehri

Student:

Partner:

University of Washington

Discipline:

Engineering

Sector:

Education

University:

Concordia University

Program:

Globalink Research Award

A trajectory optimization-based framework for cooperative multi-robot object transportation

The proposed project on cooperative multi-robot systems addresses one of the recognized major challenges and opportunities in collaborative robotics (Cobots). For multi-robot groups, optimizing transportation efficiency for the workpiece while at the same time achieving whole-body obstacle avoidance in a cluttered manufacturing environment is highly involved due to the physical coupling of the system between the cooperating agents. The project objective is to establish a novel cooperative framework for multi-robot rigid object transportation in an unstructured environment. With the adoption of this framework, the robots should be able to coordinate their motion policies and generate individual control policy intelligently, resembling a human-human collaboration. Moreover, investigations will be conducted on the uncertainty incurred by the varying communication delay in the system with the proposed distributed topology. Experimental validations of the proposed framework will be performed on the Franka Emika Cobots in both home and host institutions.

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Faculty Supervisor:

Ya-Jun Pan

Student:

Partner:

RPTU Kaiserslautern-Landau

Discipline:

Engineering

Sector:

Technology; Advanced Manufacturing; Information and Communications Technology

University:

Dalhousie University

Program:

Globalink Research Award

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