Large Language Model (LLM): Mobile tools for Social Media Dynamics Creation

In today’s social media landscape, users are constantly creating a variety of content, from texts and images to videos. However, producing high-quality material often requires expertise and resources that many don’t have. This is where our collaboration with PetoLab, an innovative social media app for pet enthusiasts, comes into play. We’re on a mission to […]

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Valorisation de données en viabilité hivernale (Interfaces graphiques et optimisation)

Le problème d’entretien hivernal des routes constitue un domaine de recherche crucial, où les chercheurs ont cherché à élaborer des stratégies novatrices pour gérer efficacement les ressources tout en garantissant un service de qualité. Les variations climatiques, les quantités variables de neige et les contraintes logistiques font de ce problème un terrain propice à l’application […]

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Deep Learning for Automation of 3D Pore Analysis in Micro-CT Tomographs

This research proposal focuses on addressing the prevalent challenges associated with Proton Exchange Membrane Fuel Cells (PEMFCs), specifically targeting the reduction of greenhouse gas emissions. Despite significant advancements in performance and durability, particularly in automotive contexts, the high cost associated with essential materials for optimal functionality remains a formidable barrier. Notably, advancements in cathode gas […]

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Understanding Drone Pilot Needs to Develop a VR Training System

Using drones to inspect power lines, which can involve travelling in isolated areas, makes this process faster and more secure. Yet, training drone pilots for this task is time-consuming and expensive. In this project, we propose to partner with Connect Atlantic Utility Services Corporation to develop a Virtual Reality training system for drone pilots. This […]

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AI Improved Markerless Motion Capture For Dance

Motion capture is a technology to track human motion in 3D for replication with digital tools, such as mixed and virtual reality, video games, or movies. However, full 3D tracking requires the complex and finicky setup of multiple cameras that are prohibitively expensive to individuals or small studios. This is especially difficult with complex human […]

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Advancing a Multimodal 3D Motions Library for DanceForms™

Leveraging its roots in dance and technology, Credo is building a multimodal motions platform for dance to enhance education, choreography and archival practices; the foundation being motion capture data. There are existing 3D motion capture libraries but they are either one of or many of the following: outdated, not comprehensive, poor quality, non-standard, poorly labelled […]

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élaboration d’un modèle de prévisions du comportement des utilisateurs chez Readygg

Ce projet vise à soutenir Readygg dans ses efforts en développant un système de collecte de données fiable et performant adapté aux contraintes du blockchain. Ce système permettra une meilleure compréhension et réponse aux tendances de consommation des joueurs dans l’écosystème Web3. De plus, le développement d’outils pour le suivi et l’analyse des indicateurs clés […]

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A Group Recommender System for deviantART

deviantART is the world’s largest online arts community with a huge number of users and items. They currently recommend art to users only via an algorithmic presentation of “popular” items, and an item-item recommender system presented alongside every individual piece of art. deviantART expects to use recommender systems technology to enhance and leverage the contributions […]

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Algorithmic auditing through synthetic data

Algorithm auditing refers to the study and evaluation of algorithmic systems to ensure their transparency, fairness, legality and compliance with ethical standards. Our project focuses on the acceptability of practical audits where platforms provide synthetic data about algorithms, instead of the traditional approach with external audits without considering the collaboration of the platform. Technical implications […]

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Towards Causal Deep Learning for Explainability, Robustness, and Extrapolation

In many applications, Machine Learning (ML) predictions are used to make downstream decisions. Acting on ML predictions however can change the distribution of features that the ML model relies on for predictions. The implication is that such downstream decisions procedures implicitly expect the ML model to generalize outside of the observational distribution. Unfortunately, this is […]

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Développement d’algorithmes d’IA pour soutenir le développement de médicaments oncologiques

En biologie, tout comme dans le monde des machines mécaniques, la fonction découle de la structure. Dans le domaine biologique, les “machines” sont constituées de protéines. En altérant leur structure, il est possible de leur conférer de nouvelles fonctionnalités. L’entreprise 9Bio combine une expertise de pointe en modélisation IA avec l’ingénierie structurelle biologique pour créer […]

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