Preparation of Quantum Machine Learning Datasets with Quantum Advantage and Challenges using State-of-the-art Classical Machine Learning

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 […]

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Intact : Évaluation de l’incertitude en tarification

La mesure de l’incertitude dans les prédictions est considérée clé pour prendre des décisions informées à partir des données. Ceci améliore également la transparence et la confiance dans les prédictions d’un modèle. Ceci peut également influencer le design expérimental et la balance entre l’exploitation d’une solution et le besoin d’exploration et de collecte de données […]

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Object Tracking for High-Speed Pick-and-Place Robot

The demand for eCommerce and online orders has risen rapidly in recent years, this drives the need for highly efficient and automated item sortation systems. Kindred AI is a technology company with the objective to bring artificial intelligence and robotic technologies into the workforce of eCommerce, parcel and order fulfillment. As a part of the […]

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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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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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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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Conception et implémentation d’une infrastructure infonuagique pour l’exécution des simulations fondées sur des algorithmes d’intelligence artificielle.

DesignBot propose une solution logicielle dans le but d’amener un support aux concepteurs dans leur travail créatif ! L’idée est d’intégrer les technologies d’intelligence artificielle générative dans le processus de travail des concepteurs. En améliorant la collaboration entre l’humain et la machine, DesignBot permettra d’amener pas à pas les concepteurs à créer des concepts hors […]

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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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Contact-Rich Visuotactile Manipulation

Robotic manipulation involving contact-rich tasks continues to be a challenging, yet critically important, research problem with many potential applications, including domestic assistance, automated agriculture, and advanced manufacturing. Many of these tasks involve both unstructured environments and complicated dexterous manipulation. Existing approaches that rely on purely visual sensors and predefined models are brittle and prone to […]

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