The abradable rub strip (ARS) material’s main function is to minimize the clearance between blade tips and the fan case, thereby increasing the overall engine efficiency. Under tensile and compressive loading, the abradable material behaves different, and has a significant post-failure compaction under compressive loading. Therefore, its characterization is complex and requires a wide range […]

The research project aims to develop a portable, wireless interface for implantable medical devices that monitor brain activity in patients with conditions such as epilepsy and motor disorders. This new software will allow for continuous, unrestricted measurement of brain activity, enabling doctors to collect high-quality data in patients’ natural environments. The interface will wirelessly transmit […]

Fraud prevention tools play a critical role in real estate transactions. Even though digital fraudsters employ all newly available tools to find loopholes in the existing technological ecosystem, the information systems involved in real estate transactions typically lag behind in terms of digital identity verification and management. In order to facilitate industry adoption of the […]

Le projet vise a developper des strategies permettant de combiner plusieurs modeles d’intelligence artificielle (IA) etudies au sein de l’ecosysteme d’intelligence artificielle de l’equipe de prevision de la demande de !’unite prevision des apports et de la demande d’Hydro-Quebec. Ces modeles combines permettront d’obtenir de meilleures predictions a court terme de la charge sur le […]

Prostate cancer is the third deadliest cancer in men and early detection is crucial. PSMA is a protein that is highly present in prostate cells, making it a promising target for imaging and treatment. Total metabolic tumor volume (TMTV) is a measure of tumors’ characteristics, but it is currently not measured in clinical settings due […]

Understanding the current panorama of threat actor groups worldwide is critical to building efficient cybersecurity programs. Information about threat actor groups’ motivations, tools, tactics and techniques they use to attack, and the type of targets they have in their sights provide valuable information to cybersecurity teams. To achieve this goal is essential to generate intelligence […]

As cyber adversaries are becoming more creative, analysts are required to figure out more innovative ways to detect them to be able to respond before it’s too late. To detect any underlying threat inside a system, data logs are collected showing events and activities occurring inside the system. Adversaries nowadays are capable of evading detection […]

As generative models become increasingly prominent in machine learning, the need for accurately detecting out-of-distribution data has become crucial. The primary objective of this research is to develop an approach that can identify when the program encounters data that is vastly different from what it was trained on. In machine learning, programs may make errors […]

This research project focuses on developing an automated system to search and analyze time-series tabular features in the financial institution’s machine learning pipeline. The goal is to identify relevant features and improve efficiency in the decision-making process. The project will begin by prototyping a system to support automated feature search patterns and researching feature search […]

PUBLIC (est. 1988) is a not-for-profit print periodical exploring the intersection of art, design, technology, and culture. This research project advances that history by looking at the future of print culture as today’s artists are increasingly making and exhibiting work in online spaces. How can PUBLIC promote engaging and accessible conversations around artists working exclusively […]

The COVID-19 pandemic has forced children to quickly adapt to home-based or virtual learning; however, a number of researchers have identified challenges and difficulties with applying and using technology. More importantly, there has been a significant rise in the rates of mental illness occurring as a result of COVID-19 and children are now experiencing increased […]

Machine learning attempts to model high-level abstractions in data using multiple processing layers with complex structures or non-linear transformations. Federated learning is a distributed machine learning approach that allows multiple parties to collaborate on training while preserving user data privacy. However, the data from each party is typically non-independent and identically distributed (Non-IID), which can […]