L2M – AI-MD Validation Proposal

AI-MD is an AI-driven symptom checker that allows people to monitor their health and scan their body for suspected illness and disease. Millions of people are using symptom checkers online every month that only allow them to describe thier symptom information using text or checking off boxes. Not only are these tools not accurate, but […]

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Automation of next generation photovoltaic measurement capabilities

The proposed research project at the Turak Functional Nanomaterials Research group at Concordia aims to enhance the efficiency of solar energy data measurement and analysis from emerging solar cell technologies. In a world increasingly focused on sustainable energy sources, efficient utilization of solar power is paramount. The lab manages vast data, including complex images of […]

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L2M – ACTIVELY SOBER AI MODEL FILTER FOR INFLUECES IN SUPPORT OF ALCOHOL CONSUMPTION

The Actively Sober app is an ambitious project that combines advanced artificial intelligence with a keen understanding of cultural nuances to address the widespread issue of alcohol misuse. By employing AI algorithms that continuously scan digital platforms to identify and block alcohol-related content, the app aims to create a supportive environment for users, helping them […]

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Automated Software Vulnerability Patching using Dynamic Symbolic Traces

Deep learning (DL) has emerged as a viable means for identifying software bugs and vulnerabilities. The success of DL relies on having a suitable representation of the problem domain. However, existing DL-based solutions for learning program representations have limitations – they either cannot capture the deep, precise program semantics or suffer from poor scalability. We […]

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Développer des modèles pour la détection d’évènements de bas-niveau basés sur les textures des codes haptiques

D-BOX conçoit et fabrique des systèmes de mouvement haptique pour le cinéma maison et le cinéma en salle qui offrent une expérience immersive en générant des effets de mouvements et vibrations synchronisés avec l’action à l’écran. Les formes d’ondes d’effets haptiques utilisées pour activer les sièges sont actuellement générées manuellement à travers un processus fastidieux […]

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Génération de modèle 3D par IA au sein d’une PaaS de rendu 3D temps réel.

Chez 3dverse, nous sommes persuadés que débloquer le potentiel de la 3D en temps réel est la clé pour faire avancer l’innovation. C’est pourquoi notre équipe construit la première véritable plateforme de rendu 3D en temps réel (PaaS). Nous savons que cette technologie aura un impact décisif et changera la façon dont les gens visualisent, […]

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Analytic tools for assessing the predictability and trustworthiness of social AI systems

As Artificial Intelligence (AI) becomes more developed and integrated into society, it will no longer consist of single isolated systems, but networks of AIs interacting with humans in socio-technical systems interwoven into the functioning of our society. When systems have many interacting components, they start to interact in unexpected ways and become hard to predict […]

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Design and evaluation of congestion control algorithm for fluctuating bandwidth at extreme condition scenarios of 5G-advanced and 6G mobile networks

The applications of the future will require support for ultra-low delay, high bandwidth, and multiple data streams into the gigabit-per-second range. 5G-Advanced and 6G networks with the assumption that width bandwidth will be available through the utilization of high-frequency spectrum. However, this increased bandwidth comes at the cost of unpredictable scenarios, such as sudden changes […]

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Using Machine Learning to Predict Clinical Outcomes in Users of the Digital Health App, Manage My Pain

ManagingLife developed Manage My Pain, an app that lets users track and analyze their pain for better self-management of symptoms. ManagingLife aims to predict clinical outcomes (e.g. anxiety, depression, pain interference) and identify contributing factors from its 85,000 users. The goal is to create a validated, explainable machine learning model that can forecast clinically relevant […]

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Developing auto-annotation of actions in movies assisted by a haptic track

D-BOX is designing and manufacturing home theater and movie theater motorized seats. These seats are used to create an immersive environment for users by generating movements and vibrations that are synchronized with the action in the movies. Right now, making these seats vibrate in the right way takes a lot of manual work. This project […]

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