Geotab‘s dash cams deliver a clear and complete picture of harsh driving events and provide crucial video evidence in the case of collisions and insurance disputes. It is essential to ensure the dashcams work well and capture high quality footage. The object of this project is to automatically detect dash cam installation faulty and monitor […]

SpassMed’s ShockRanger is a primary product that utilizes vital signs from patient monitors to provide healthcare providers with meaningful signals for clinical decision-making. SpassMed is seeking one or more methods that can accurately forecast shocks, particularly Septic shock, among patients in ICUs. In addition, SpassMed aims to develop models for effectively classifying patients into their […]

Road safety affects everyone. In an effort to reduce accidents, we need to understand both the driving behavioural patterns that are predictive of accidents, and the environmental factors involved. In order to analysis risks, at first, collect a rich set of data: including Latitude/Longitude, engine RPM, accelerometer data in the X, Y, and Z plane, […]

The task of predicting salaries for a given job title and seniority in a specific region is challenging due to the complexity of various factors as well as the sensitivity of salary data. It’s hard to get an accurate sense of what people are getting paid in many regions in the world and getting harder […]

Smoking and all other forms of tobacco exposure are known to cause extremely detrimental health effects. It is the leading cause of preventable morbidity and mortality worldwide, and quitting smoking can increase life expectancy by as much 10 years. Tobacco is associated with poor reproductive health outcomes, cardiovascular disease, lung cancer, diabetes, blindness, and much […]

Ecomtent focuses on developing vertical-specific generative AI models for e-commerce brands, offering a self-service tool to allow customers to generate an unlimited number of high-quality images in any scenario. To this end, we leverage a textto- image model which will be trained to recontextualize any image via a simple text prompt. In particular, we seek […]

Traditional cancer treatments have followed a “one size fits all” approach, which limits efficacy and often results in significant side effects. This research project aims to develop an approach to predict the impact of cancer missense mutations on the drug-protein interactions of cancer treatments. The approach will use the patient’s own genomic profile and will […]

Artificial Intelligence in Modern Hospitality will analyze the effects and business applications of AI in various aspects of the hospitality industry, including but not limited to food & beverage, travel & tourism, lodging, and recreation. Specifically, it will analyze how AI fits into various consumer profiles, allowing for greater flexibility, efficiency, and profitability for companies […]

The intern will take part in a multifaceted project surrounding sustainability in industry and clean advancements in advanced manufacturing techniques within a multitude of different sectors. The intern will perform an in-depth study on Canada’s status regarding advanced manufacturing and utilize social media platforms to relay novel information to promote interest, engagement and an entrepreneurial […]

This research will explore machine learning methods in order to devise a control scheme for robotic manipulators(Candarm3) in the context of space exploration. The objective is to develop an early prototype for an autonomous learning agent which can carry out standard control tasks without any operator supervision. The primary machine learning methods that will be […]

Nowadays, many of the movie characters whose performances move us on screen are at least in part digital. From superhero stunts to de-aged beloved actors and actresses, visual effects artists have to create digital characters and painstakingly reproduce performances to convince audiences. New Deep Learning (DL) technologies are emerging to help alleviate the processes. For […]

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 […]