The goal of this work will be to explore different ways to visualize and interact with knowledge extracted automatically from very large heterogeneous document collections. This extracted knowledge will be in the form of a multi-attribute graph of extracted entities and relationships between them. These relationships will be associated with both temporal and spatial information. […]

This is a continuation of a MITACS sponsored study for the Chief Information Officers Association of Canada, Ontario Chapter, to assist its members in long term career planning and development. It will refine and further validate a model for advancement from CIO to CEO, by interviewing CEOs who have successfully made the transition. In total, […]

CRISP is an international Deloitte development initiative aimed at helping some of our largest clients understand and managed corporate risk. CRiSP stands for “Cognitive Risk Sensing”, and it centers around using large sources of mostly unstructured data (i.e. 10% sample of all of Twitter, thousands of news aggregators, etc.) to understand and forecast risk for […]

Addictive Tech Corp is a fast-growing ad-tech company. They use real-time advertisement bidding software which is massive and sophisticated. The actual dynamics involved in any given bid are complex and hard to predict. This makes writing test logic for such a system cumbersome and catching all corner cases next to impossible. Because of the scale […]

Currently, some public and private organizations have implemented various identification verification solutions to manage identity authentication. The idea of using a third-party identity provider (IdP) to access a relying party (RP) is not new, and both RP and IdP have their benefits as they can only be connected once in a federated identity ecosystem. While […]

The Pungle payments-as-a-service platform delivers low cost, real-time, friction free business disbursements, peer-to-peer (P2P) transfers, and B2B supplier payments. Pungle’s mission is to enable businesses with a digital payments platform that provides real-time disbursements and transfers. The problem that arises with digitization of business payments is higher risk for fraud due to its electronic nature. […]

With the fast-growing size of machine learning datasets, it has become increasingly important to store them in a reliable and distributed manner. Large scale distributed file systems such as GFS, HDFS and Amazon S3 have the capability to store large scale of data reliably. However, these distributed file systems have an intrinsic shortcoming: they provide […]

The project attempts to tackle an important challenge in Artificial Intelligence (AI), to give a machine an ability to comprehend multiple documents like humans do. These can do the redundant or preliminary reading-based research performed in many domains. The project aims to create a system which can read, understand, and answer queries and/or summarize multiple […]

Kindred’s Sort product is a robotic system that operates in e-commerce distribution centers to sort and handle apparel and general merchandise. The deployed system is controlled through a combination of artificial intelligence and human-in-the-loop teleoperation. The proposed project involves applying techniques from artificial intelligence (specifically machine learning and reinforcement learning) to improve the ratio of […]

The goal of this project is to develop new models to optimize the treatment of cervix cancer using radiation therapy. We will develop two models to achieve this goal. The first model will model the uncertain nature of the tumour evolution as a function of time, which will help us predict the position, shape, and […]

Alzheimer’s is the most common form of dementia which worsens over time. Current therapeutic against Alzheimer’s disease provides only symptomatic treatment. This limited effectiveness provides us with an opportunity to direct our research efforts towards developing new agents to prevent or retard the disease. Studies have shown that very small amount of tetrahydrocannabinol (THC), a […]

The primary objective of the project is to approach the problem of understanding true causality of vehicle accidents and scientifically determining which vehicles and drivers are at highest risk of an accident from a machine learning perspective. Geotab has a number of identified collisions in X, Y and Z planes, and much more. The research […]