Deductive verification is a subdiscipline of computer science which ensures software reliability and safety by formally modeling and proving program behavior. It is currently difficult to apply by non-experts and scales badly with program size and complexity. Pluggable type systems, which annotate variables and sub-programs with types that describe their expected values and behavior, offer […]

The project aims to help standardize the analysis of time series data by creating an analysis and reporting framework by which time series data regardless of its size, frequency, and/or source can be normalized, analyzed, and reported.

Within the past decades, there has been a significant growth in the electric power systems that have resulted in a large increase in the development of transmission and distribution lines. Distribution system is the final connection between the utility provider and the customers and constitutes a major component of the power system. However, since most […]

Pharos has a data fusion platform for geospatial and spatiotemporal data. This project will extend the platform to cover additional data sources, such as flood risk data, and allow for the on-demand calculation of decision-relevant metrics. This requires an investigation of the underlying data, methods to combine sources, and development of pipelines for efficient automation. […]

Robotic experimentation platforms can enable faster materials discovery and optimization through automation, high throughput experimentation and standardization. However, an exhaustive search of a vast materials space with varying compositions, formulations, and processing conditions is prohibitively expensive. Machine learning algorithms are widely used to learn from experiments performed by automated experimentation platforms and suggest the most […]

Honest Empathy Innovations Inc. aims to build sustainable mental healthcare solutions with groundbreaking development and innovation in machine learning. We plan to build a next-generation machine learning platform that Canadians can access for their mental health with this project. Our solution is supported by the Canadian Mental Health Association, NEXT Canada, and Yukon Government. Our […]

Using machine learning, this project will seek to enhance customers’ online shopping experience by intelligently selecting product photos based on the user’s information and knowledge about the product. Computer vision will be used to label images and gain information automatically.

The design of usable public health information systems is critical in areas such as healthcare. In this project an analysis of the usability of a pan-Canadian public health information system will be conducted. The approach will involve application of usability engineering methods to identify issues and areas where the system’s user interface could be modified […]

The Glacier test facility was established to conduct testing of aircraft turbofan engines under icing conditions. Engine manufacurers from across the globe use the Glacier facility to earn airworthiness certification for their products. A range of icing conditions is prescribed by airworthiness authorities, and required air temperature is produced under naturally occurring conditions. Air temperature […]

The Dawson Group is a construction and transportation company that ranges between 600 to 700 employees seasonally – depending on the companies’ workload (awarded projects, seasonality with highway construction, winter snow plowing) and also normal turnover, we have many onboards and offboards in our organization each year. With many employees coming and going, it places […]

AtmanCo est une entreprise œuvrant dans le domaine du développement du potentiel humain. Des tests psychométriques sont conçus afin de mesurer le profil psychologique d’un individu. Ces tests sont utilisés en entreprise dans les contextes d’embauche, de gestion d’équipes et de développement des compétences. L’équipe de développement de Solutions TLM, en collaboration avec AtmanCo, travaille […]

The intern is expected to develop a pipeline for training large machine learning models on drug-like molecules to learn a broad understanding of biochemistry. This pipeline involves developing a model that can learn on many biological and quantum mechanical tasks concurrently while evaluating and improving the structure of the model using low-cost approaches from recent […]