PUBLIC (est. 1988) is a not-for-profit print periodical exploring the intersection of art, design, technology, and culture. This research project advances that history by looking at the future of print culture as today’s artists are increasingly making and exhibiting work in online spaces. How can PUBLIC promote engaging and accessible conversations around artists working exclusively […]

The project, “AI/ML Data Analysis of Fashion Consumer Trends in Social Media: An Impact Report for Canadian Businesses,” aims to analyze fashion consumer trends on social media platforms and produce an impactful report for Canadian businesses. The intern will employ and develop advanced data analysis techniques to collect and process data from various social media […]

The intern will participate in an interdisciplinary project on advanced manufacturing strategies for autoinjectors, which have become increasingly popular due to their convenience and reliability in administering medications. While the Epipen is a well-known example, other medications, such as Noxalone, use this delivery system. The scale and extent of autoinjector manufacturing in Canada are unclear, […]

Foqus has built a software solution that can speed up MRI scans and is applying for regulatory clearance to commercialize the software. This project focuses on the sales process of the product and facilitates taking the software to the market.

Improving road safety has a direct impact on the lives of drivers as well as the costs incurred by companies operating commercial vehicles. One important aspect of road safety is timely and effective vehicle maintenance. By forecasting vehicle maintenance needs and predicting breakdowns before they occur, valuable insights can be provided to drivers and fleet […]

Many real life decision consider a multitude of criteria, one such example is in healthcare where the patient’s condition, available resources, chance of recovery, cost etc all need to be consider when administrating care. An analytic hierarchy process makes the multi-criteria decisions by first converting the problem into a set of mathematical constraints by pair-wise […]

Mental disorders have a significant influence on the daily activities of Canadians. Musical intervention can provide a non-invasive treatment through changing emotional state and creating positive mood. The main objective of this project is to provide a long-term solution for musical intervention through an optimized machine learning framework for an intelligent real-time emotion recognition and […]

Many older adults in Canada are becoming increasingly isolated from their communities. This is largely due to the fact that Canadian cities are built with cars in mind, and many older adults rely heavily on driving to get around. However, as they age and lose their ability to drive, many older adults often are unable […]

The research project, guided by Professor Stephen Smith, focuses on addressing environmental challenges related to water pollution and debris detection in the water areas, with a specific emphasis on garbage and waste detection on the water surface. The project entails a systematic literature review and analysis of various computer vision models to detect and classify […]

Machine learning attempts to model high-level abstractions in data using multiple processing layers with complex structures or non-linear transformations. Federated learning is a distributed machine learning approach that allows multiple parties to collaborate on training while preserving user data privacy. However, the data from each party is typically non-independent and identically distributed (Non-IID), which can […]

Machine Learning (ML) approaches generally consist of training an algorithm on a given dataset containing data which has to be analyzed or otherwise understood. For an ML application to be successful, careful thought must be given to ensuring that the architecture of the algorithm chosen is fit for the task at hand: some architectures are […]

The project aims to develop a state-of-the-art numerical simulator to compute transistor’s physical behaviors at deep cryogenic temperatures. First of its kind, the simulator will incorporate physical effects critical for transistor’s operations at cryogenic temperature such as inelastic scattering, while maintaining computational efficiency and robustness. The successful outcome will provide the research community a widely […]