Workforce scheduling algorithms are used by businesses around the world, including hospitals, factories, and retail stores, to determine when and where employees should come to work. Usually, the needs of organizations change over time, but the scheduling algorithms used in these systems usually do not change. Kronos is an industry leader in scheduling software, and […]

We will build a prototype system that can be used to give a personalized recommendation for the ideal fitness/weight loss regimen for a consumer given their personal health record data. This will be based on building a relational probabilistic model that is based on standard medical ontologies, initially on expert knowledge, and can make predictions […]

Long-term monitoring and modeling energy consumption behaviors is a daunting task for decades. This project aims to achieve efficient energy consumption data collection and processing using wireless sensors and cloud platform together, focusing on large scale enterprises that consume large amount of energy, e.g., electricity, gas. By tackling the challenges through algorithm design and system […]

Access-control policy management is an increasingly hard problem from both the security point of view (is the policy “safe”?) and the functionality point of view (does the system still work as expected?). Even when a policy is considered both safe and functional, each addition, deletion or modification of the policy has the potential to break […]

Within a watershed, data are collected on various aspects of water (amount, withdrawals, returns, contaminant concentrations) by multiple groups, yet rarely shared at the basin scale. To reduce data “siloing” and make collected data available to multiple users interested in water management within a watershed context, data from multiple sources must be combined. Advancing Canadian […]

Previously in an internship with MITACS, researcher found a piecewise linear model to approximate the dependent variable. The genetic algorithm was employed to approximate the value of sales, as the dependent variable against changes on marketing efforts, as the independent variables. The outcome became a program that can approximate the actual data with three lines. […]

Machine learning is a subfield of artificial intelligence that aims at producing computing models from observations (data), with no explicit coding made by humans. Recent advances have illustrated a strong potential of machine learning, with the potential of being a disruptive technology in many domains. For the current project, we are investigating techniques for making […]

The proposed project contributes to the development of a product for use in public spaces to provide LED lighting which is made interactive through sound responsiveness. This sound responsiveness is made possible through the use of modern micro-computers which can be programmed to use sounds in the environment to create different lighting effects. Unfortunately, this […]

Mobile games have been dominating the Canadian video game industry over the past few years. However, the growing number of game releases creates an increased necessity to focus on quality in order to stick out of the mass. While storytelling has proven to greatly increase user engagement in PC and console games, it is rarely […]

Acquisition and tracking of human body is a key research problem in the fields of computer vision, computer graphics, and biomechanics. We propose a system that can used to create personalized human body model in normal room environment using just a single RGB-D camera. We want our system to be robust against illumination variations and […]

Virtual worlds, like Second Life, have been adopted by researchers to assess students’ understandings of the knowledge they have learned. Students’ performances of solving the challenges and quests in the virtual worlds can be treated as their overall mastery of the taught concepts and skills. However, the answers of the questions like “do they have […]

The ensemble of the human brain wiring configuration is known as the connectome. Using diffusion magnetic resonance imaging, we can approximate the connectome and use it to increase our understanding of normal function and of neuro-diseases. However, the complex interactions between each steps from brain images to the final wires give rise to many potential […]