Modern video games are composed of different types of artifacts, such as images, sounds, and software code. All these artifacts are developed at the same time by different teams. While the independent creation and modification of each artifact allows different teams to make changes without blocking each other from making progress, how artifacts are combined […]

Customer Relationship Management (CRM) tools help protect and develop the relationships one builds with their clients, which typically uses data analysis to study large amounts of information. These tools compile data from a range of different communication channels which include company’s website, phone number, email, live chat, and social media. This allows learning more about […]

The broad goal of this project is to create and implement a system which is able of assessing and classifying skin burns (and other types of skin lesions/wounds) using different state-of-the-art machine learning models and techniques such as EfficientNets, Reinforcement learning, saliency mappers, CAM, etc… The work that will be completed during this internship will […]

This research aims to develop an efficient machine learning model to detect COVID-19 patients by using their cough signals. The model is trained using thousands of audio recordings of cough signals from different subjects. The audio signals can be converted into spectrogram images that can be visually inspected to determine relevant regions of interest. There […]

Kent Building Supplies (referred to as Kent from hereon) has 49 retail locations across Atlantic Canada. We have started developing Robotic Process Automation (RPA). RPA significantly reduce the human intervention and generate exception-based flagging reports. We would like to continue deployment of RPA for new tasks and use unsupervised and supervised machine learning to improve […]

In this project, we propose a modular continual learning approach to face the problem of catastrophic forgetting and transfer in learning from evolving task distributions. Concretely, we propose a model that learns how to select most relevant modules based on a local decision rule for a given task to form a deep learning model for […]

This research project will create data dashboards that measure Kingston’s economic resiliency a year into the pandemic. The data will be collected from multiple organizations and sources to create a comprehensive look at the pandemic’s impact. The data dashboards will cover the areas of business and tourism, health and community, mobility and home and employment. […]

Researchers are often tasked with finding related works in their respective field, including journal entries and images that represent the work contributed, which allows researchers to summarize and expand previous contributions. Biological researchers often convey their contributions through visual illustrations, also considered gene model maps. These gene model maps are used to represent how contributions […]

Nowadays, mental health issues have become a major public health challenge. Moodie app allows patients to track their emotions, moods, routines, sleep, diet, physical activity, and associated context via journal logs. This provides the therapist with a rich pool of data for accurate diagnosis and assists with the treatment. This project aims to (1) Develop […]

Ontology induction from unstructured text is a long standing goal of Natural Language Processing (NLP). An ontology can serve a number of tasks, such as question answering, Information Retrieval to name a few. In fact, practice communities are often relying on an ontology in their daily decision making process. This is the case of IATA, […]

Le monitoring en temps réel des bioprocédés permet d’augmenter les performances et de réduire les pertes. La principale difficulté provient de la quantité limitée d’information accessible en temps réel et des phénomènes complexes et fortement non-linéaires en présence. Ainsi, les algorithmes statistiques conventionnels ne permettent pas d’interpréter adéquatement et avec la précision requise en pharmaceutique […]

Equipment failure is the primary source of unplanned downtime in industries working with rotating electrical machines. Fault detection at the early stages is an essential solution for reducing this downtime. Condition monitoring of machinery is the process of capturing and monitoring parameters such as vibrations to identify a developing fault. This project uses the data […]