Electrical Load Forecasting

Load forecasting is an essential activity for a company like Hydro-Québec. It is necessary for objectives as varied as the management of production or the management and maintenance of the electricity network. Any significant forecasting error can result in reliability issues, loss of opportunity, or additional costs to the business. On the other hand, a […]

Read More
Assessing and Addressing Health Disparities Related to Utilization of Preventive Care Services in Ontario

Health disparities arise as a result of long-standing societal disadvantage and discrimination. As machine learning models become more popular in the healthcare sector, understanding of current health disparities becomes even more critical. Without careful management of existing biases, the models can inherit and amplify health disparities, leading to highly undesirable clinical outcomes. This project focuses […]

Read More
Real-time object recognition on wearable devices

The goal of the project is to implement real-time state of the art object recognition models on wearable devices. These devices aim to help people living with a visual disability by providing a description of their outdoor environment and offer navigation guidance. This would improve the experience of the users by allowing them to perform […]

Read More
Audience Allocation to Retail Geo-clusters

Based on the user’s geo-location, timestamp and other attributes (eg. time of day, past visit history and app behavior categories, etc.), a machine learning algorithm can be developed to find which cluster the users belong to. Overall, the data of geo-location and timestamp are used to roughly locate the potential clusters. This project will involve […]

Read More
Off-Policy Reinforcement Learning (RL) for a Production Robotics Application

Kindred offers eCommerce retailers a solution to assist with rapid order fulfilment from their distribution centres. The solution (SORT) is a combination of a so-called put-wall and a humanoid robot. The robot picks up items from orders, scans them, and puts each item in a cubby of the put-wall according to the scan code. The […]

Read More
Question-to-question semantic similarity for Question Answering System

Question Answering (QA) system automatically answer questions raised by users in natural languages, and it is a crucial component of a human-machine conversation system. A typical QA system collects human written question-answer groups and structures them in a database system. However, in order to answer questions that are semantically similar to the questions stored in […]

Read More
Understanding cell-cell interactions with deep learning-based profiling

The aim is to understand how fibroblasts, the most common connective tissue in animals, and cancer cells interact with each other through image analysis. These co-culture imaging screens, containing fibroblasts and cancer cells, will help identify novel signaling mechanism involved in cancer. The objective is to apply deep learning techniques to these image-based assays to […]

Read More
VR-based testing station for impairment screening

In this project, a VR-based testing station for impairment screening will be implemented. The station includes a Virtual Reality (VR) goggle (to be updated to Augmented Reality, AR, later), biophysiological measurement sensors, and an integration algorithm to integrate the result of measurement with scene construction of the VR system to implement dynamic scene rendering. The […]

Read More
Indirect Domain Shift for Single Image Dehazing

Deep convolutional neural networks (CNNs) have been tremendously successful in many high-level computer vision tasks, e.g., image recognition and object detection. Although recent works have shown that it is also possible to learn an end-to-end CNN model for low-level vision tasks, e.g., image dehazing, the resulting performance is still not completely satisfactory. For high-level vision […]

Read More
Quantitative biomarkers from Magnetic Resonance Imaging

Magnetic Resonance Imaging (MRI) is the non-invasive method of choice for diagnosing and studying neurodegenerative diseases such as multiple sclerosis (MS). However, conventional MRI that is currently used in clinics cannot provide a reliable measure of neuronal health. More specifically, it cannot distinguish healthy from diseased myelin, a key component of neuronal tissue that is […]

Read More
Development of Efficient Methods Preprocessing Large Lidar Data Sets for Application to Road Design and Optimization

Technological improvements, competition in the survey services industry and the increased use of UAV’s (drone) has driven down the cost of LiDAR acquisition. As a result, LiDAR is rapidly gaining popularity in application in road planning and design. LiDAR data sets typically contain tens of millions of points. Efficiently processing this data efficiently presents challenges […]

Read More