Devhaus Corporation operates 20 early child education centers across 5 countries including Canada, USA, Singapore, Cambodia and Philippines. To further implement its principle of Observation to Education, Devhaus is partnering with York University research team to develop an Artificial Intelligence Recommender System to help teachers across the world select optimal lesson plans for each kid […]

Hockey has long been shown to be among the least predictable of all professional sports. Recent developments in data collection methods have created the demand for more detailed and advanced predictive modelling techniques to extract value from and apply the data to real world problems. This project focuses on predicting important outcomes in hockey at […]

In this project, our goal is to set up a framework of data collection to support user profiling which could be used to identify influential users in decision-making. The profile will be built based on the information of individual users obtained by collecting user activities in rewarding challenges that encourage employees, customers and partners to […]

Models used for Wildfire catastrophe insurance as of today are not considering substantial information, such as geographic information and environmental constraints. The objective of the project is to establish a theoretical framework and an empirical process to enhance Aviva Canada’s current Wildfire Economic Capital (EC) model, to be able to determine the amount of capital […]

In a historic United Nations (UN) summit, world leaders adopted 17 Sustainable Development Goals (SDGs) as a universal call to action to address the global challenges we face by the year 2030, including those related to poverty, inequity, environmental degradation, prosperity, and peace and justice. Together, the UN and their partners have underscored the importance […]

The explosion of data from personal phones, apps, and sensors have enabled powerful machine learning algorithms to help computers identify, categorize, and evaluate information without the help of humans. However, teaching computers how to identify, categorize, and evaluate information usually requires feeding the computers a lot of data pre-labelled by humans. The pre-labelling process is […]

Analytical applications in large organizations across even intermediate time ranges are often made complex, costly or even impractical due to temporal inconsistencies in the available data. The ever-changing nature of organizations causes categorical labels in data to change over time. This is particularly true for HR data, as the organization adjusts to changes in skillsets, […]

Deep neural networks are effective at image classification and other types of predictive tasks, achieving higher accuracy than conventional machine learning methods. However, unlike these other methods, the predictions are less interpretable. While accuracy may be enough for applications where errors are not costly, for real world applications, we want to also know when the […]

In the near future the way that we encrypt and authenticate information online may not be safe. For this reason, we need to create new tools that will enable secure communication for many coming years. The proposed research is to create such tools from a certain algebraic object called isogenies. These are functions that take […]

Various forms of usability testing can be used to optimize interface design and maximize human-computer interaction principles . A well-integrated, intuitive interface has the capacity to improve human efficiency, mitigate errors or lapses and improve situational awareness. Usability methodologies such as heuristic evaluations and cognitive walkthroughs can be performed at any point in the design […]

D-Wave’s quantum computer is good at solving a specific type of problems known as Ising spin problems. However, in order to solve one of these spin problems, you must first solve another hard problem—embedding the spin problem on D-Wave’s quantum processor. From the land of discrete mathematics, this embedding problem falls into a well studied […]

Power prices are a significant contributor to the overall risk of almost any large-scale industry. In particular, energy companies such as TransAlta who are active participants in many regional power markets have a strong interest in understanding the long-term risks they are exposed to. This project seeks to develop a model that will help TransAlta […]