Learning from relational data is crucial for modeling the processes found in many application domains ranging from computational biology to social networks. In this project, we propose to work on developing modeling techniques that combine the advantages of the approaches found in two fields of study: Machine Learning (through graph neural networks) and Statistical Learning […]

We are proposing to help design the experimental setup to characterize chip-scale Optical Phased Arrays (OPAs). OPAs – a photonic device used for optical beam forming and beam steering – have been widely studied for LiDAR, optical sensing, free-space communication and more. Building on previously prototyped phase array antenna design at Honeywell, the team aims […]

Knowledge graphs store facts using relations between pairs of entities. In this work, we address the question of link prediction in knowledge graphs. Our general approach broadly follows neighborhood aggregation schemes such as that of Graph Convolutional Networks (GCN), which in turn was motivated by spectral graph convolutions. Our proposed model will aggregate information from […]

Automatically assessing a pilot performance during a flight training session is a capability that can enhance the flight instructor during his duty. From data gathered during a flight maneuver, we are looking for a way to automatically assess pilot performance to augment instructor performance and provide objectivity during flight training assessment.

This fundamental research project investigates semantic visual navigation tasks, such as asking a household robot to “go find my keys”. We seek to enhance the efficacy of repeated search tasks within the same environment, by explicitly building, maintaining, and exploiting a map of locations that the robot had previously explored. We also seek to exploit […]

The project aims to extend worksite safety of construction projects at Hydro-Quebec (HQ) using computer vision and a Real-Time Location System (RTLS). The case study is a substation construction project near Montreal. The main safety risks that will be targeted in the case study are related to equipment mobility (struck-by accidents) and not wearing Personal […]

API usability specifies how easy, efficient, error-preventing, and pleasant an API of a software library is from its users’ perspective. With machine learning (ML) techniques becoming increasingly powerful and pervasive, many non-programmers and casual users (e.g. domain experts in medicine or geography) started to explore ML libraries. However, many find them challenging to use because […]

In this project we aim to automatically learn an augmenter network by using an approximate online bilevel optimization procedure. We plan to learn a augmenter network that generates a distribution of transformations that minimizes the loss on a validation set. By unfolding the gradients of the training loss, we will optimize the loss on validation […]

Le projet consiste à développer des algorithmes permettant de créer des secteurs pour les clients de Fastercom. Afin d’y parvenir, différentes méthodes de Machine Learning seront évaluées et implémentées. Cette création de secteurs permettra d’améliorer la performance des algorithmes de la compagnie en découpant le gros problème d’optimisation de tournées de véhicules en petits problèmes […]

Machine learning (ML) has recently achieved impressive success in many applications. As ML starts to penetrate into safety-critical domains, security/robustness concerns on ML systems have received lots of attention lately. Very surprisingly, recent work has shown that current ML models are vulnerable to adversarial attacks, e.g. by perturbing the input slightly ML models can be […]

Ageing is a global phenomenon, which presents challenges and opportunities for many nations, including Canada, China, and Germany, the foci of the study. In addition to the impact on pensions, health care, the labour market, consumer trends, and social services, the greying population also has far-reaching implications for businesses. As the population ages, changes in […]

Machine learning algorithms are being used in a wide range of applications. It is a branch of computer science where the system can learn from the data and make decisions. Financial fraud is an increasing hazard in the financial industry, and it is important to detect a fraudulent transaction. Machine learning algorithms can be used […]