Pathology and disease diagnosis using artificial intelligence and machine learning: Supervised and unsupervised deep-learning based methods on data from medical imaging procedures and patient chart analysis

Machine learning applications in healthcare have shown excellent inroads in medical imaging sciences in recent years. Our research aims to improve upon and open up doors into several different pathology diagnosis applications using artificial intelligence. Contemporary research into some of these applications has shown better diagnostic capacity than expert-level clinicians. Our research into artificial intelligence […]

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Modelling Light Transmittance for the Human Heart using Computational Modelling Techniques in the Effort to Apply Optogenetics for Heart Defibrillation.

Optogenetics is a new and rapidly growing field of bioengineering that allows to control physiological functions of genetically modified cells using light. Applying this novel technique in cardiac applications opens the door to the development of the next generation of cardiac devices, such as contactless implantable cardioverter defibrillators (ICDs). A challenge with the potential use […]

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Novel fuel cell materials and designs for high performance

Polymer electrolyte membrane fuel cells are a promising solution to addressing climate change, as they can produce emission free energy on demand using hydrogen as fuel. Despite their benefits, many challenges remain in the way of widespread commercialization of these devices. Specifically, components such as the gas diffusion layer (GDL) and catalyst coated membrane (CCM) […]

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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 […]

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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 […]

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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 […]

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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 […]

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Enhanced Perception for Autonomous Truck Mounted Attenuator (ATMA) to Increase Work Zone Safety

This project makes an existing Autonomous Truck Mounted Attenuator (ATMA) system fully operational for Canadian harsh weather conditions and develops an augmented perception framework to enhance motion planning of the control system. The primarily focus of ATMA is ensuring the safety of highway workers and transportation infrastructure in work zones. On successfully understanding the existing […]

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Reinforcement Learning Based Constrained Control Applications

The main issue of the proposal hinges on the application of Data driven approaches for Model Predictive Control (MPC) applications. MPC is an optimization based control methodology well known in literature which is extremely popular when considering constrained control problems. The main drawback of MPC is the need of an accurate model plant to solve […]

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Enquête sur la commercialisation des nanotechnologies au Canada

Les objectifs de ce projet visent à déterminer l’impact de la collaboration université-entreprise sur la commercialisation des nanotechnologies, à déterminer l’impact du financement public de la recherche universitaire et à travers des contributions directes aux entreprises sur la commercialisation, et à étudier les effets des retombées de connaissances ‘capturées’ par les entreprises avec ou sans […]

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A robot control strategy for automated compound sanding of gypsum plasterboard

Nowadays, many building contractors use modular construction, where various parts of a building are partially or completely built on an assembly line and then put together on the delivery site. Building interior modules often involve building and finishing plasterboard walls, including closing joints between panels and hiding fasteners or defects. To do so, a gypsum-based […]

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