Density-based clustering is a statistical learning technique that aims at finding high density regions in the data separated by low density regions, finding applications in virtually all fields of knowledge. Hierarchical density-based clustering goes one step beyond and finds a hierarchy of density-based clusters at different density levels according to a user-defined density smoothing parameter. […]

The primary objective of this MITACS Cluster project is to investigate, design and prototype novel techniques for the integration of security and quality of service in near field communication (NFC)- based smartphone applications. Universal NFC Cloud Connect Inc., a new start-up company based in Halifax, Nova Scotia, that ties mobile devices to location-specific events via […]

Computer simulations provide a safe alternative to taking a trial-and-error approach in the real-world. If a simulating intervention is found to be inefficient or even harmful, then it can be canceled without causing harm to real individuals. Consequently, simulations are increasingly sought after for complex social problems such as homelessness and the spread of the […]

Delphia’s business model revolves around generating insights for investing firms that allow them to make better trading decisions. It has been shown that detecting when Twitter users post about recent or future purchases has the potential to increase the accuracy of company sales forecasts, which in turn can inform stock trading strategies. This internship project […]

SS&C processes more than 80% of financial scanned and faxed documents in the US and requires large amount of manual labor in order to map information from a document into another form. Advances in neural networks applied to computer vision have produced text detection and recognition that nears human performance. This project will be leveraging […]

The multiple sclerosis (MS) clinic at St. Michael’s Hospital (SMH) is among the largest in the world. While considerable data is collected from the MS clinic in both structured and unstructured form, the ability to glean this information to assess quality of care and conduct advanced analytics such as predictive modeling is limited. In this […]

We are in the process of creating and growing a team of researchers expert in the field of machine learning and data-mining. Ultimately, our aim is to create solutions to eliminate the need to manually define personalization strategies. We are working with more than 1000 retail locations across North America and collecting large-scale datasets of […]

Citco provides financial products and services to hedge funds, private equity and real estate firms, investors, institutional banks, Global 1000 companies, and high net worth individuals in the Netherlands and internationally. The proposed research is focused on optimizing operations by automating trade resolution and reducing risk using machine learning. Outlier detection algorithms will be proposed […]

The goal is to create a conversation loop between 3D designers and artificial intelligence programs. This will help the AI provide suggestions to the designer, while the designer provides the AI with feedback. This can help make it easier for designing complicated objects as well as complicated textures that belong to the surface of 3D […]

Modern software organizations use continuous integration (CI) practices to build and test their products after each code change in order to detect quality issues as soon as possible. Unfortunately, the number of builds scales super-linearly with the number of hardware and feature configurations that should be supported. In order to avoid running out of build […]

The project will help us design a machine learning model that can determine the demand transference of our customers. The key objective of this project is to design, research, build, and experiment with machine learning models to ensure low product waste and high customer satisfaction. The model will have several impactful applications across the organization.

Despite a significant improvement in healthcare systems over the past decades, the rapid growth in the number of patients with multiple chronic diseases – called multimorbidity – stands as a complex challenge to healthcare services that are primarily designed to treat individuals with single conditions. Advances in machine learning as well as in computing power […]