Prediction models and longitudinal outcome analysis for child and youth psychiatric acute care admissions or access to high-intensity community-based services: machine learning models to identify risk factors, quantify service capacity short-falls, and promote appropriate transitions into the adult system of care

This research project aims to improve the care of children with severe mental health or substance use disorders by developing a ML model that can predict which children are most likely to need hospitalization. The project will analyze data from various services, including transitions into the adult mental health/addictions system and examine hospital admission outcomes […]

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Innovative Website and Web Application Development for Law Enforcement

Forrest Green, in collaboration with Saint Mary’s University, will work with the intern to successfully develop and implement new web solutions and module for Police Services across the country. The intern will work on innovative dashboards to support crime trends and crime data (external) as well as aggregated officer data for use of system analysis […]

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Scalable Team-Based Learning – Structure Editor, GUI Editor and Teacher Dashboard

Parents, teachers, administrators, and senior governments all recognize the importance of K-12 Computer Science (CS) education in preparing tomorrow’s citizens for both future job opportunities and social issues caused by information technology. For example, Ontario’s 2020 math curriculum adds both coding and Social-Emotional Learning (SEL). McMaster Start Coding (http://outreach.mcmaster.ca) is one outreach program who has […]

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Time Series forecasting for 6-month market demand prediction

Fiddlehead Technology is taking the art and science of predictive forecasting to a new level, working with machine learning to find elegant solutions to some of the fast-moving consumer goods (FMCG) industry’s most complex problems. Fiddlehead is employing big data analysis and forecasting to revolutionize the food and beverage supply chain, solving the hard problems […]

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Amélioration de l’estimation de la limite de vitesse pour un système de gestion active de la vitesse pour une flotte de véhicules

E-SMART commercialise un produit qui offre aux flottes de camion une façon innovatrice d’assurer la conformité aux panneaux de limite de vitesse de leur véhicule. Les principaux clients sont des flottes de camions aux États-Unis et aux Canada. Pour contrôler la vitesse du véhicule, E-SMART s’interface directement entre la pédale d’accélération et l’ECM d’un véhicule. […]

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AI-powered Solutions for Complex Systems

AI tools based on deep learning has recently been suggested for many complex problems where a large amount of data is available. We will be working similar AI tools but problems from very different domains, namely, airport delay management after disruption and predicting prices of fresh produce under challenging climate conditions. Establishing a recovery flight […]

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Data Architecture & Integration

The goal of this data project is to architect and integrate XYONs key data sources from disparate systems into one central repository or EDW (Enterprise Data Warehouse). Using enterprise-level data extraction transformation layer (ETL) integration, the aim is to connect our e-commerce platform to ERP, CRM, and our API gateway, which connects to a multitude […]

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A human-centered approach to the design and implementation of advanced health technologies using Cognitive Work Analysis (CWA)

While there have been several literature reviews on the performance of digital sepsis prediction technologies and clinical decision-support algorithms for adults, there remains a knowledge gap in examining the development of automated technologies for sepsis prediction in children. Pediatric sepsis is a major cause of mortality of children worldwide. However, there is still a lack […]

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Intelligent analytics for hyperspectral image dimension reduction

This research project focuses on improving the analysis of hyperspectral images, which capture images with many narrow spectral bands. Hyperspectral images have many challenges due to their high dimensionality and data redundancy. To overcome these challenges, the researchers aim to develop an advanced intelligent analytics framework for hyperspectral dimension reduction (HDR) using disentangled representation techniques. […]

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Enhanced Tool Support for Gradle Build Systems

The main goal of the project is to discover if program analysis approaches can be adapted to the context of Gradle build systems. Thus, during the research it is planned to implement support for Gradle build systems within an existing program analysis toolchain that have been developing at the University of Waterloo. (currently specific to […]

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Cloud-Based Image Processing for Real-Time Robotics in Manufacturing

The goal of this project is to explore how cloud-based processing of image data can be utilized in real-time robotics applications, specifically in advanced object tracking. The challenge is to balance the need for considerable computing resources with the cost of deploying such resources with each robot arm. This is where cloud-based processing offers a […]

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Prédiction des bactéries hôtes de phages grâce à l’analyse des profils de méthylation de génomes bactériens et viraux par apprentissage automatique.

L’objectif général du projet est le développement d’outils de prédiction des bactéries hôtes des phages par apprentissage automatique. Le premier objectif consistera à développer un prédicteur reposant sur les profils de méthylation dans les séquences métagénomiques bactériennes et virales, grâce à des réseaux de neurones avec des mécanismes d’attention, et des prédicteurs de similarité basés […]

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