PIC computer studies of plasma wave instabilities in the exhaust plume of the VASIMR propulsion engine

My proposed research project is devoted to Particle-in-cell (PIC) computer simulations to study the plasma waves instabilities in the exhaust plume of the Variable Specific Impulse Magnetoplasma Rocket (VASIMR) device. VASIMR is a type of electric propulsion plasma device, using the plasma as propellant, potentially for a long-term space mission with a much higher specific […]

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Reinforcement Learning for Predictive Sports Analytics

Our project develops novel machine learning algorithms for interpreting complex, multi-agent scenarios in sports analytics. The collaboration with our industrial partner SPORTLOGiQ will tackle open problems in deep reinforcement learning to build novel capabilities in sports analytics for ice hockey. Deep reinforcement learning is a breakthrough technology with prominent successes in games such as Go […]

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Composing without forgetting

In this project, we propose a continual learning approach to face the problem of catastrophic forgetting in online image classification problems. Concretely, we propose a model that learns how to mask a series of general modules in a deep learning architecture, so that generalization emerges through the composition of those modules. This is of vital […]

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Smart Atlantic Buoy Redundancy Model

This research will provide a prediction of sea conditions at a given location based on measurements from meteorlogic and oceanographic ‘smart’ buoys in the general area. The motivation is to provide redundancy in the measurement of sea conditions for safe navigation within the Halifax Harbour when the main smart buoy in Halifax Harbour fails or […]

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Deep Fraud Detection

Financial fraud is a serious issue that is taking place globally and causing considerable damage at great expense. Statistical analysis and machine learning tools can help financial institutions detect different types of fraud. In some cases however, mislabeling and the cost of classification may actually increase the volume of ‘false positives’ for supervised methods. As […]

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Machine/Deep Learning applied in P&C insurance representations

The purpose of this project is to allow the company to have access to useful insurance representations, encoding the diversity of contexts found in larger markets. This is expected to boost the performance of predictions for tasks learned in small data and highly variable target setting.

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Cinema VR: between borders

The aim of this research is to understand the recent encounter of cinema with a specific type of technology called Virtual Reality (VR) and which gives rise to new arrangements: cinema remakes itself or becomes another and the virtual environment lends to cinema its orthogonal ability to elevate the senses. Therefore, if this recent mode […]

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Biomimetic functional coating for flux control

We would like to develop slippery liquid infused surfaces for molding applications. Molding technology is of great importance in industry and understanding the wetting behavior of molding liquids (polymers/metals) is of fundamental interest and non-trivial as well because of the involved phase transition from liquid to gel/solid upon cooling. Thus, both wetting and post solidification […]

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Failure-Tolerand Connectivity Maintenance for Robot Swarms

In many real-world applications, robots need communication between each other to coordinate. For the information to propagate, robots need to be connected, i.e. there has to be a communication path between all the robots in a team. We have designed a decentralized connectivity-preserving algorithm and validated using the ARGoS multi-robot simulator. The connectivity-preserving algorithm has […]

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Advanced Applied Probabilistic Programming

Autonomous cars are one example of a compelling next-generation artificial intelligence technology. In order to safely navigate through the world, cars must plan long-range routes and short-range paths, perceive the world around them, and act according to a safety-first policy that takes into account the intent of agents in their surrounding world. While not strictly […]

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Non-invasive automated assessment of tonic attention (vigilance) of commercial airline pilots during simulated flights

With the goal of increasing the safety of civilian air flight, the detection of a decrease in pilot attention is becoming an important need in civilian aeronautics. Multiple models used for the detection of hypovigilant states have been developed over the years in experimental conditions, but barriers still exist limiting current use. First, some of […]

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