Problem detection and aerial mapping for construction site management

On time discovery of problems and constant monitoring of construction sites have great economical benefit. It requires the capability of highly efficient and accurate object detection and segmentation algorithms that can work with coarsely labelled training samples. The project is aimed to develop new learning-based object detection and segmentation algorithms for problem detection and mapping […]

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Automated Fatty Liver Diagnosis

Up to 30% of the population has a Fatty Liver Disease (FLD, a condition in which fat builds up in your liver). Non-invasive ultrasound assessment of this liver condition is an increasing demand in healthcare service due to its high risks leads to advanced liver diseases. However, an ultrasound-based examination has made the manual inspection […]

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LGBTQI2S Seniors’ Safety in Public Services

This project will result in a national environmental scan on LGBTQI2S seniors’ safety in health care, social care and municipal public services. It aims to identify promising policies and practices as well as systemic and structural barriers. It will also include the experiences of LGBTQI2S workers who serve seniors, a largely unexplored area. Egale Canada […]

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Multi-morbidity Characterization and Polypharmacy Side Effect Detection for designing Optimal Personalized Healthcare with Machine Learning

Despite a significant improvement in healthcare systems over the past decades, the rapid growth in the number of patients with multiple chronic diseases – called multimorbidity – stands as a complex challenge to healthcare services that are primarily designed to treat individuals with single conditions. Advances in machine learning as well as in computing power […]

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Applying Machine Learning to Predict Demand Transference

The project will help us design a machine learning model that can determine the demand transference of our customers. The key objective of this project is to design, research, build, and experiment with machine learning models to ensure low product waste and high customer satisfaction. The model will have several impactful applications across the organization.

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Statistical Learning for Financial Time Series

Given a time series of returns for a portfolio of financial instruments, develop a model that accurately predicts returns which maximize profits. The objective function will take an input of financial indicators from the previous time interval and the returns from the current time interval. These indicators can explain relationships between financial instruments in the […]

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Research into grid-forming methods for off-shore wind farms

Conventional power systems rely on synchronous machines for generation of power and also for formation of an interconnected network of generation to which loads are connected via a transmission system (known as a grid). Increasingly renewable sources of energy are interconnected to a grid via power electronic converters. These converters have been traditionally operated with […]

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Be Yourself: How to be a Positive Influencer On and Offline

It has been shown that a mother’s conduct, together with her relationship with her daughter, can directly and indirectly impact her daughter’s well-being and development (e.g., eating habits, body image, and self-esteem). Studies have shown that the mother/daughter relationship influences every stage of the daughter’s development, with particular influence in the formation of the young […]

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Multi-Channel User Linkage through Probabilistic Matching

People utilize multiple devices to complete various tasks, making their online identities fragmented. Advertising is as much about knowing when not to promote a product as it is about when to do it. For example, before being sent alcohol and cannabis ads, the user must be identifiable as being over 19. Age information may only […]

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Personalized Wealth Management Advisor based on the Analysis of Times Series Related to Financial Transactions

The aim of this research project is to develop innovative tools that will help financial institutions deliver highly personalized services to their customers. We intend to use the most recent advances in statistical learning methods and machine learning algorithms mostly in deep learning, vector embeddings and autoencoders, to leverage the power of time series models […]

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