This research aims to create a platform that can predict the impacts of cyberattacks on various financial assets, such as bonds, stocks, and a company’s credit risk. The focus is on the impacts of cyberattacks on the prices of financial assets listed on the Toronto Stock Exchange (TSE). Still, the prediction models and tools developed […]

An important component of modern video games is the non-player character (NPC), moving entities in-game that are not controlled by a human, which may cooperate with, oppose, or otherwise interact with the player. For an NPC to interact with the game word it must often perform complex tasks that are difficult to program explicitly. Research […]

The rapid evolution of video resolution has significantly increased the video bitrate requirement, making data transfer a challenging task for data-intensive applications like video conferencing, cloud gaming and game streaming. With the rise of machine learning, studies have shown the potential of embedding conventional video compression algorithms with AI-based methods to enhance their performance. This […]

Modern compilers have increasingly large number of complex optimizations to meet the prevalent demand of using Machine Learning (ML) and Artificial Intelligence (AI) in gaming and other applications. Optimization passes are program and architecture depend. Therefore, selecting the best optimizations in the most optimal ordering is a difficult task. While leveraging ML methods in compiler […]

AR/VR may be the next frontier for online human communications and interactions. The ability to produce photorealistic avatars dramatically improves the feeling of immersion and connection in applications utilizing AR/VR. However, current methods of face capture are time-consuming and involve expensive cameras and sensors. In this project, we explore deep learning methods for generating face […]

This research project aims to improve the performance of GPUs, which are important for running machine learning algorithms. GPUs are a fundamental architecture in machine learning, and this project will use transformer-based models to learn the program structure of GPU kernels for various downstream tasks like performance projection and metrics such as GPU utilization. The […]

The proposed research project involves developing machine learning models to predict the mechanical properties of polymer composites. The interns will collect and preprocess data from various sources including open-source databases and conducting extensive experimental tests, build artificial neural network (ANN) models using advanced algorithms, and validate the accuracy of these models using test data. The […]

The proposed project intends to generate a method for identifying weeds and develop site-specific weed control prescriptions for sugarcane cultivations in Costa Rica using Remote Sensing techniques. Remotely sensed data will be captured using multispectral camera and LiDAR sensors attached to Remotely Piloted Aircraft Systems (RPAS). Images will be processed using machine learning algorithms to […]

Gene therapies are revolutionizing medicine, providing new therapeutics for diseases that previously were untreatable. In the central nervous system in particular, gene therapies hold great promise for saving lives and improving the quality of life of children and aged patients. The most common form of gene therapy that is used to treat patients involves the […]

Humpback whales produce stereotyped, socially learned songs on their breeding grounds, yet little is known about song development outside the breeding season, or the effects of increased vessel traffic on humpback whale communication. With access to an extensive underwater Passive Acoustic Monitoring network along Canada’s BC coast, facilitated by the North Coast Cetacean Society and […]

The high-level goal is to develop technology to enable more C++ applications to run well on many-core architectures such as recent AMD CPUs, GPUs, and combinations thereof (APUs). We expect to improve the capabilities of compilers like clang/LLVM to identify task-level parallelization opportunities that are not able to be identified today.

A new aqueous rechargeable battery combining an intercalation cathode with a metal anode has been developed recently. The energy density for a prototype battery is comparable or superior to commercial 2 V rechargeable batteries. There is a need to further improve the cycle performance and to reduce self-discharge effects of this battery. In this proposed […]