The Impact of Emerging Technologies on Defense Policy

How technology relates to Canadian national defence policy, strategy, and planning is not well understood. To date, much of the research on emerging technology in the military focuses on concerns over ethics, privacy, human rights, and governance, largely overshadowing equally important research on the way technology intersects with military strategy and tactics, defence recruitment and […]

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Graph-based learning and inference: models and algorithms

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 […]

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Cognitive Radio for Multimedia Traffic in Wireless Mesh Networks

In a cognitive wireless mesh network, licensed users (PUs) may borrow surplus spectrum from other PUs and rent them to unlicensed users (SUs) for getting some revenue. For such spectrum sharing paradigm, maximizing the revenue is the key objective of the PUs, while that of the SUs is to meet their requirements and getting a […]

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Dense gas in the galaxy merger NGC3256

Any physical processes that we aim to study in space have probably been influenced at some point by the process of star formation. Whether it be the interstellar gas and dust, the formation of clusters of stars, or galaxy evolution, star formation plays a role as a strong driving force for the physics behind these […]

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Link Prediction on Knowledge Graphs with Graph Neural Networks

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 […]

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Data Science in Pilot Performance Assessment

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.

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Exploiting Experiences and Priors in Semantic Visual Navigation

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 […]

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API Usability of Machine Learning Libraries

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 […]

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Approximate Online Bilevel Optimization for Learning Data Augmentation

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 […]

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Detection of corroded tringles in Michelin tires

The research project entails finding a method to detect corroded steel wires used in the manufacturing of tires at Michelin in Bridgewater. This would be achieved using methods that are proven safe for humans and the environment. Also, the detection equipment will be integrated in the existing Michelin facilities in Bridgwater, NS, Canada.

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