Mineral exploration and natural disaster risk reduction involve reasoning with uncertainty about complex descriptions of parts of the Earth. Such complex reasoning is traditionally carried out by human experts who, through years of training and field experience, develop specific knowledge and are able to take the right decision at the right time. This project will […]

Increased energy consumption across the world for heating and cooling indoor living spaces has been a major contributor to global greenhouse gas production. As per 2015 statistics, buildings account for 76% of global electricity consumption and approx. 35% of that energy consumption is for air conditioning, heating, and ventilation. To combat climate change it is […]

Tribute Kiosk currently operates photo booths that are touch-based in terms of their operation. However, as a result of the Covid-19 pandemic, consumers are hesitant to interact directly with high-contact surfaces. Tribute Kiosk seeks to migrate the functionality of its photo booths to a touchless format while also adding new interactive augmented reality features to […]

In this project, we will explore the new ways to design and implement a Low-Code Software Development platform that is easy to use, requires minimum software knowledge, is business logic oriented, and robust to dependency change. Specifically, we provide functional templates with detailed configuration flexibility to cover the high frequency requirements from the expected business […]

Adversarial perturbation of all the image pixels is computationally intensive and may not be realized in practice. In contrast, an adversarial patch attack where an adversary can choose to perturb a specific subset of pixels in an image, is more practical in fooling a trained image classifier or hiding a person from an object-detection model. […]

In this project, a group of scholars in computer science and business proposes using state-of-the-art machine learning methods for secondary-data-based persona construction and preference prediction. Specifically, the researchers will use recent data dimension reduction methods to process the raw data, use new machine learning models to achieve better learning results, and use self-supervised technology and […]

Recent years have seen a wealth of clinical evidence accumulate in favor of the radiomics hypothesis, wherein standard-issue oncological medical images, such as CTs, PET-CTs and MRIs, exhibit reliable fingerprints of cancer tumor genetic makeup, enabling predictions of patient prognosis, treatment resistance and side effects to be made directly from an analysis of imaging data. […]

This project will improve the learning capacities to recognize confidential information in documents of various formats. Thus, our project has to set up a technology (natural language process NLP and others) that emulates the way in which humans read a document and to process this information using inference rules and a master data.

At a high level, the goal of this project is to create a system for producing synthetic datasets based on real data. As a large financial crime detection firm, Verafin deals with large volumes of sensitive data which must be kept private, however they are also interested in collaborating with academics to gain new insights […]

The Mandatory Entry-Level Training (MELT) virtual reality (VR) truck simulator under development by Serious Labs Inc. offers a training solution for boom and scissor lifts. MELT in Alberta is a Class 1 training program in compliance with the National Safety Code Standard 16 Commercial Truck Driver Entry Level Training. The purpose of this research project […]

Mental disorders are the leading cause of disability in Canadaxiii. Unfortunately, there are significant gaps in care including a lack of support in navigating the mental health systemxivxvxvixvii. It is widely agreed by the medical community that there will be a wave of widespread need for mental health related services resulting from COVID-19xviii, which will […]

An important legal task for which natural language processing has a use-case is for assessing the risk of confusion for trademarks. By means of a thorough understanding of factors which are used by legal professionals to make decisions in this domain, we replicate the process by using state-of-the-art deep learning models for natural language processing. […]