Artificial Intelligence in Mass Transit

Transportation systems are evolving towards intelligent transportation systems and ISR Transit is a leading provider of these systems providing solutions in fleet management. In these systems, one of the enabling technologies is wireless sensor networks in which sensors are used to obtain information about the fleets. For example, sensors are deployed on motor, brake modules, […]

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Towards quantum?encoded optical communications over existing fiber networks

Two fundamental pillars of communications/communications networks are trust and truth; in particular, we must ensure that the message (or data) that a sender wishes to transmit does indeed reach the intended receiver without being altered or eavesdropped by an unwanted party. This project focuses on demonstrating one concept of the quantum internet. The quantum internet […]

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Mitigating Snowy Owl Aircraft Collisions by Relocation

To aid in active management of Snowy Owls and other raptors at airports, it is essential to understand the spatial distribution and movement behaviour of birds both on and off the airfield. The impact of airfields on birds may be particularly pronounced because airfields provide open, undeveloped land similar to early successional habitats that are […]

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Evaluating nutritive value of low-lignin alfalfa at multiple physiological stages

In Canada, alfalfa is a widely cultivated legume forage and the principal source of protein in the diets of ruminant animals. High quality alfalfa (i.e. nutrient composition and fiber digestibility) is vital for profitable dairy production because it can reduce requirements of high-cost concentrated feeds. High fiber digestibility is associated with higher cow’s intake and […]

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New designs for Bayesian adaptive cluster randomized trials for an individualized clinical support tool with capacity to support distance follow up and treatment of depression

Depression is a common and often devastating illness that contributes to suffering for patients and families and is also the number one cause of disability globally. Many patients do not respond to their first trial of treatment, and managing depression according to best practices can be difficult for clinicians. Using the power of machine learning, […]

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Agricultural Anomaly Detection using Temporal Dynamics of Remote Sensing Data

This project is about using artificial intelligence to interpret agricultural remote sensing data. We will develop new means to integrate repeated imagery data of targeted agricultural fields to pinpoint agronomically significant anomalies (e.g., water or nutrient stress, crop pathology, weeds, etc.) and provide field managers easy to follow recommendations guiding development of the most cost […]

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The Scleroderma Patient-centered Intervention Network (SPIN) COVID-19 Cohort and COVID-19 Home-isolation Activities Together (SPIN-CHAT) Trial

People with the autoimmune disease scleroderma are vulnerable in COVID-19 due to frailty, lung involvement, and immunosuppression; they are representative of vulnerable groups in terms of COVID-19 mental health ramifications. No previous randomized controlled trials have tested mental health interventions during infectious disease outbreaks. We leveraged our existing ongoing cohort of over 2,000 people with […]

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Utilizing Materials Informatics to Predictively Engineering the Micro-Mechanical Properties of Hydraulic Turbine Steels

Cost-effective clean energy production is one of the most urgent economic and societal issues facing Canada today. Hydro-Québec is a world-leader in clean hydro-electric energy production – an essentially carbon-free source of energy. However, the repair and replacement of hydraulic turbines utilized in hydro-electric power production has two important consequences on clean energy production: (1) […]

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Positive Youth Development and Youth Sports during the COVID-19 Pandemic

The goal of the project is to understand how athletes have been affected by the COVID-19 pandemic. Through online surveys and interviews, the researchers hope to learn about the way the pandemic. They also want to know what athletes are doing to cope and how their families and coaches are supporting them. Study findings will […]

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Efficient Deep Learning Methods that Only Require Few Labeled Data

In this postdoc, we plan to focus on computer vision tasks where existing deep learning methods require lots of labeled samples to work well. Acquiring labeled samples is time-consuming and often impractical. Thus, we investigate three different classes of methods to alleviate the label scarcity problem: active learning, weakly-supervised learning, and few-shot learning. In active […]

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