Towards making graphics accessible to blind people

There has been a lot of effort in making printed media accessible to low vision or blind individuals. Braille has been extensively utilized to make text accessible to the blind. Software that automatically converts text to speech has also been employed for this. However, the existing solutions are not adequate for conveying graphical information to […]

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Item Identification for Robotic Pick and Place Applications

This research project aims to develop a robot pick and place model that can be used in Kindred AI’s robotic arms to improve efficiency and reduce production costs. The intern will work closely with the partner organization’s experts in computer vision and MLOp to design and build new models, modify existing ones, and experiment with […]

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The Fertility Partners 2023

The Fertility Partners is the business partner of choice for distinguished IVF and prenatal care providers, working together to identify and institute best practices so they can deliver fulfilling outcomes and exceptional experiences to patients and their families. Since the platform started less than 3 years ago projects for this Mitacs internship are assisting in […]

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Representation Learning with Time Series Data

The proposed research aims at learning better representations for multivariate time series (MTS) data, which can be applied to various important real-life applications such as weather, traffic, and electricity forecasting. Better forecasting accuracies for these tasks could help with efficient risk aversion and decision making, and save costs for decision makers. The proposed research will […]

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Supporting Virica’s Inorganic Growth Objectives

“Supporting Virica’s Inorganic Growth Objectives” is primarily a strategy project which will lead to actionable insights to promote Virica’s goal of expanding our VSE library through inorganic methods. Initially, the project will entail research into the current viral sensitizer space, with the goal being to identify Virica’s competitors and other companies that hold IP on […]

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Optimizing Deep Learning Models for Edge Devices in Threat Detection for Computer Vision Applications in Smart Cities and Retail

During the internship, the selected candidate will focus on developing edge computing solutions that can recognize and alert the relevant personnel in real-time in case of potential security threats (e.g. theft, robbery) and safety issues (e.g. employee accidental falls). This would help retailers to prevent or respond quickly to incidents, reducing losses and improving safety […]

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PaceZero BSI 2023

PaceZero – Impact Due Diligence Framework Development. This project will further develop an Impact Due Diligence process map for Impact measurement analysis.

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Prototyping, validation, and optimization of an innovative solar-air heating system for window applications (Phase 2)

The increased pressure of natural resource depletion and environmental issues have largely promoted the search for renewable energy sources such as solar energy. Solar heating systems that use air or fluid to transfer the heat energy from solar irradiation to the indoor environment have surfaced as green solutions with high energy conversion efficiency (70%). However, […]

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Olivia Xu – Ethics First: Fostering Social Responsibility in AI Development and Deployment through Intercultural and Interdisciplinary Collaboration

The proposed project aims to address ethical challenges associated with AI technologies by researching and promoting intercultural and interdisciplinary collaboration. This intercultural and interdisciplinary collaboration entails drawing insights from people who come from different cultural backgrounds, study different disciplines (engineering, philosophy, sociology, law, etc) and work in different sectors (industry, academia, non-profit, etc). With the […]

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A Machine Learning Framework for Exploring Mortality in Developing Countries with Verbal Autopsies

This research project, backed by Unity Health Toronto and the Centre for Global Health Research (CGHR), aims to explore the use of machine learning in predicting causes of death using verbal autopsy data from low-to-middle-income countries. Verbal autopsy is a cost-effective and efficient method for documenting deaths in regions with limited resources. By employing advanced […]

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