The vision for the VERDICT platform is to become the first choice for online event adjudication support in the global VTE research community, which will in turn contribute to the Network’s mission of promoting and facilitating clinical VTE research that is collaborative, methodologically rigorous, and yields valid results. This innovation project is focused on building […]

A proposal for a collaboration where Sarah Johnson would work as an intern to Evolution Wake Park, providing the local small business with valuable expertise learned and sought from the Smith School of Business. This internship would work to improve the structure and behind the scenes business operations of the fun and exciting park, as […]

The project’s aim is to develop SlicerAR, free open-source software infrastructure for rendering native scenes (medical images, anatomical structures, etc.) on the augmented reality devices within the 3D Slicer (www.slicer.org) medical image analysis platform, to allow end-user applications to display anatomical models overlaid on the real-world view.

For an average investor, prior to making an investment, they would conduct the following steps: ideation, comprehension, validation, and execution from different platforms – each servicing a specific need and is overcomplicated for the average user. On top of that, it would take months before someone found their suite of tools, platforms, and brokerages they’d […]

Innovative Investment Education Investing has never been easier, but the retail investment journey is broken. This is even more difficult to answer because investors are overwhelmed with information, don’t trust most online sources, and it feels like it is a solo endeavor. An intuitive platform that supports retail investors through their entire investment journey, from […]

Investing has never been easier, but the majority of individuals still are reluctant to invest and those that do still face a fundamental problem. “What should I invest in?” It’s because the investment journey for a retail investor is broken and Utradea is proven to solve it. For an average investor, prior to making an […]

Around half of the world’s population are living in some form of earthen building. Compressed earth blocks are widely known as a low-cost material that has high thermal capacity, low environmental impact, and ease of construction. The project will address three items: material characterization, development length of steel reinforcing bars and performance under freeze-thaw cycles. […]

Network parameter configuration is crucial for optimizing performance in a cellular network. Often, such parameters are too numerous and their interdependence too complicated for them to be efficiently configured by human experts. Therefore, it is of great interest to study network parameter configuration as a machine learning problem. We aim to expand on the machine […]

In this project, SaaSCan will leverage and expand its market research data on Canadian SaaS startup metric performance to create an innovative, online-self assessment tool. Unlike some other tools that require founders to upload detailed financial data or complete complex financial spreadsheets, the SaaSCan “Metrics Sherpa” tool will enable founders to type in data points […]

Volatility is an important variable for liquidity management. It is used to time the submission of buy and sell orders and their aggression levels in stock markets, bond markets, and derivatives markets. Volatility is also an important variable in the pricing of derivatives. Market participants will use volatility estimates to improve the quality of their […]

In Canada’s 2030 Agenda for Sustainable Development, one of the goals is to take urgent action to combat climate change and its impacts. According to this agenda, the target is to reduce Canada’s total greenhouse gas (GHG) emissions by 30%. In order to transition to renewable energy, solar and wind power in combination with energy […]

Anomaly Detection (AD) is a key research problem in the fast-evolving area of Intelligent Transportation Systems. To proactively detect faults, AD methods are applied to detect deviation from regular behavior, which can also be caused by environmental factors such as weather conditions, neighbouring trains, and track curvature. Thales Canada has unlabeled data from their Next-Generation […]