Quantum Machine Learning for cybersecurity

La cybersécurité est devenue une préoccupation majeure pour les entreprises et les organisations en raison de la croissance exponentielle des menaces en sécurité informatique. Internet est un élément critique qui est devenu un réseau universel de communication. Les attaques réseau, y compris les attaques par déni de service distribué (DDoS), sont considérées comme l’une des […]

Read More
SecureMed

The healthcare sector generates an enormous amount of sensitive data, ranging from patient medical records to billing information. The mishandling or unauthorized access to such data can lead to significant legal, financial, and ethical consequences. Despite increasing awareness of the importance of data security, healthcare institutions often still employ outdated or inadequate encryption methods, posing […]

Read More
Building Decarbonization Planning Applying Machine-learning Techniques to Building Data

In response to the escalating demand for clean tech and energy-efficient structures, our project focuses on revolutionizing building data processing for swift decarbonization planning. We tackle the challenge by parsing diverse data from mixed media documents and fine-tuning pre-trained large language models (LLMs) for optimal data query accuracy. Our approach integrates text parsing, tokenization, and […]

Read More
Enhancing technical drawing analysis with semantic segmentation and OCR technologies

This project aims to enhance the work with technical drawings in manufacturing is done by using advanced computer techniques to automatically identify and read text within these drawings. This means turning detailed plans and sketches into digital data quickly and accurately, without manual input. For the partner organization, this innovation promises to greatly speed up […]

Read More
Prompt Privacy in the era of Large Language Models

In recent years, large language models (LLMs) have significantly impacted text-related tasks, including translation, code generation, and answering questions. However, due to their computational demands, these models are typically available only through closed doors-APIs, with opaque operations that obscure data usage. This creates privacy concerns for users who frequently engage with these models, as their […]

Read More
A hybrid AI platform for Streamlining Evaluation (HAIPSE) of Applications

This project is meant to develop a Hybrid AI Platform for Streamlining Evaluation (HAIPSE) of applications assisting the partner organization, The NIB Trust Fund, in processing the two categories of funding applications. The NIB Trust Fund supports education programs of the First Nation and Métis individuals and organizations aimed at healing, reconciliation, and knowledge building. […]

Read More
Multicriteria Optimization of Agricultural Machine Operations

Careful operational planning is essential for making agriculture autonomous and sustainable. The movements of agricultural equipment in the farm can be optimized to increase productivity and reduce costs and greenhouse gas (GHG) emissions. The aim of this project is to develop and productize advanced optimization algorithms to determine the best end-to-end machine routes, positions of […]

Read More
Timed-Aware Proof Assistant for ASTD, CCSL and Event-B

Le numérique est désormais omniprésent dans nos activités quotidiennes. Nombreuses de nos actions sont numérisées, analysées et assistées par un ordinateur. Or, nous produisons de plus en plus de logiciels et les bugs (ou souvent les défauts de spécification) sont largement sous-estimés. La tendance en effet et à produire des mises à jour (parfois quotidiennes, souvent hebdomadaires) plutôt […]

Read More