Organizations have traditionally struggled with asset management as a result of not having a complete picture of the location and state of their physical assets. This is largely because critical information such as how an asset was built and should operate is locked in highly technical diagrams and unstructured documents. Asset Vision is a new […]

Voice of the Customer (VoC) is how companies hear and listen to customer feedback about their brand, products, and services. Voice of the Customer solutions convert gathered feedback into valuable data and insights at scale. Data-driven VoC analytics programs are proven to increase customer lifecycle value and lower customer churn. Companies in various industries including […]

This study builds upon work to define the decision process firms use in deciding to move their IT Services work to less urban regions such as Atlantic Canada. This Mitacs project seeks to build upon this work and analyze the ancillary benefits of such projects within the community (beyond the direct economic benefits). Policy objectives […]

Cost estimation is a critical part of manufacturing. It has a significant role in determining the feasibility of decisions including design stage, planning and production methods. Especially, it is useful for subcontracting processes that GRAD4 conducts where the features of parts are submitted and bidding is the way of the deal between suppliers and buyers. […]

Currently, data analytics services are not only expensive, but also often require days of delay for the data analytics report to be generated. The project focuses on making use of a user’s voice query as an input to create a data analytics response by aggregating data from a database. The successful implementation of the project […]

Machine learning has ushered many breakthroughs in areas such as computer vision, natural language processing, speech recognition, and recommendation systems. The models used in these applications contain many parameters that need to be learned and training often requires massive amounts of computation. As such in recent years graphics processor units (GPUs) have seen wide adoption […]

The existing approach to building Machine Learning models includes gathering all the data from customers in one place and then running the training procedure using it. However, there are no guarantees personal data won’t be leaked by the one training the model. So, the customers face a difficult decision of either allowing companies to gather […]

Video Games require a vast array of different computations to present the desired experience. These computations must be completed consistently to make the software responsive to the user. The industry trend towards many separate processors (multi-core) in the same physical device and the emergence of network based ‘cloud’ computing have created many opportunities, but also […]

The purpose of this research is to develop a solution that uses Artificial Intelligence and Predictive Analytics to Improving the Efficiency in Customer Interactions and Investment Selection.

Current procedure for monitoring securities market in Canada relies heavily on tips from outside and hard coded rules and thresholds. This approach leaves many suspicious cases out of investigation (i.e. false negatives). We introduce a data mining approach to identify irregularities in securities market. These irregularities are known as suspicious cases that might be associated […]

PC Optimum was originally built as a rewards platform. As we are moving in the path to engage more meaningfully with our customers by way of personalized & interactive experiences (content), we are building a targeting engine as a solution to surface personalized content tailored for each individual customer. The problem we are solving then […]

Information gathered from internet sources has high variance and different types of noise. This causes out-of-distribution problems with downstream ML modules such as category classification and keyword extraction. The extremely large size of internet-scale datasets requires a solution that is efficient and scalable. The objective of this project is to develop a start-of-the-art anomaly detection […]