Projets novateurs réalisés

AI-Driven Carotid Ultrasound Advancements: Redefining Stroke Risk Assessment in 3D

Stroke, a leading global cause of death and disability, often results from the rupture of dangerous fatty deposits, known as plaques, in the neck arteries. The current method of assessing stroke risk using 2D ultrasound is limited by operator dependency and lacks a 3D structure assessment, leading to misdiagnoses and re-scans. Our project aims to overcome these challenges by developing AI-powered algorithms that enhance the accuracy of 2D ultrasound diagnostics, improving stroke risk assessments and treatment decisions. This innovative approach will position Canada as a leader in healthcare innovation, contributing to advancements in AI disciplines and promoting accessible and inclusive healthcare solutions. The partner organization, Sonaro, will benefit by gaining access to high-quality data, ensuring the accuracy of the developed models, and establishing valuable network connections within the academic institution

See One, Do One, Teach One…Value One: Integration of Artificial Intelligence in Encounter-Based Evaluation Application to Help Teaching Be More Valued

The goal of this project is to incorporate AI to complement and upgrade existing functions in myTE. We plan to invest in 3 features: thematic analysis, data interaction and web analytics. In our current version, myTE compiles all comments in learners’ feedback and presents them in their original form to the users. Using AI, the feedback can be summarized by theme, spellchecked, and paraphrased – which enhances our protection to learners’ anonymity and facilitates ease for user’s CV curation. In terms of data interaction, AI would make use of data available, such as ratings in each type of encounters, as well as teacher recordings, to make meaningful inferences on teaching quality and teaching recommendations. Finally, web analytics support continuous user interface improvement in the backend and analysis on user demographics (e.g., gender, ranking) and how they affect evaluations. We will apply machine learning to look at which functions users are capitalizing on and enhance on those, while removing or switching up some of the less capitalized features.

A Scoping Review of Training Curricula for Youth Peer Supporters in Early Psychosis Programs

This scoping review will explore the research base of the intersections of peer support training and implementation. The partner organization will benefit from this project as it will form the foundation of a longer-term goal of developing a training module for early psychosis peer support workers.

Synthesis of Novel Coumarin Derivatives with Anti-Neuroinflammatory Activity

Working with Reinforcement Learning for Robot Manipulation

Why Galaxies Spin

Our galaxy the Milky Way and our orbiting companion Andromeda are the dominant members of a small collection of galaxies, the Local Group, which is about 3 million light years across. Recently, it was recognized that the Local Group is simply a mass concentration in a thin “Local Sheet” of galaxies spanning 35 million light years. Furthermore, the largest members of the Sheet encircle us. This unusual environment may have played a role in guiding the evolution of the Local Group, and the Local Group may have influenced the evolution of the Local Sheet. The proposed research is aimed at understanding this interplay. Specifically, the spin of galaxies in analogues of the Local Sheet will be measured to study how spin axes are aligned, which in turn will enable us to learn how the Milky Way and its neighbours in the Local Sheet started spinning in the first place.

Disturbed Repolarisation-Relaxation Coupling: A Novel Mechanism of Systolic Mechano-Arrhythmogenesis

Thermo-economic analysis of Carnot Batteries

Machine Learning in Chemical Kinetic Modeling for Sustainable Aviation Fuels

Modelling the effect of pathway perturbations using Reactome

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Synthesis of Cationic tungsten(VI) species stabilized by cyanoborate anions

Cyanoborate anions, negatively charged B–CN compounds, have been well established as important building blocks in metal organic frameworks, room-temperature ionic liquids (RTIL’s), and part of metal complexes. RTIL are particularly important in green chemistry, because of absence of any toxic vapours, and in photovoltaic cells, to name only a few applications. Certain cationic species, such as WF5+ and BF2+ can only be prepared with stabilizing nitrogen-bases, which coordinate to the cations donating electron density. Furthermore, WOF3+ and MoOF3+ species have not been reported in the literature, but unpublished work has shown that they are assessable using nitrogen bases to stabilize these highly electron-poor cations. Herein, it is proposed to use cyanoborate anions to stabilize BF2+, WF5+, MoOF3+ and WOF3+ centres resulting in unique RTIL’s with large anions. In addition, the resulting compounds’ fluorinating properties would be of interest.

Internship in the field of Artificial Intelligence in the context of Stream Processing