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 […]

This research project, a collaboration between ServiceNow and ÉTS Montréal, aims to improve generative AI (e.g. artificial intelligence models that learn to generate data), which can impact various creative and knowledge-based industries like graphic design, content creation, and research. The project aims to create advanced generative models that can generate a variety of data types, […]

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.

In recent years, weather has been recognized as an important factor that can have a significant impact on consumer behavior in certain industries. Predictive models that incorporate weather data can help industries to adjust their inventory and marketing strategies to optimize sales. This research project focuses on using machine learning and data analytics to determine […]

A typical language test usually consists of four parts: speaking, listening, reading, and writing. Both audio and text data from the test takers will be collected and used by the automated scoring system. During the test, some test takers will intentionally/unintentionally provide abnormal answers, which may contain memorized content, repeated sentences, and meaningless or off-topic […]

To validate structured trade contracts for language and economic term correctness, the existing document understanding systems use machine learning methods, natural language understanding, and text analysis, to extract data elements from financial documents. This can be expanded to a wide variety of financial documents, especially customer-provided reference material. The project focuses on document information extraction […]

This research project focuses on the integration anonymized signals from sensors. The capture of this data and application provides enhancement and personalization and additional clarity of information to optimize the value of benefits and features for FutureCite membership services.

The partner company (AMD) is a major innovator in the field of computer graphics and visualization, they manufacture Graphical Processing Unit (GPU) which are used by many gamers around the world. While playing video games, gamers tend to perform out-of-band actions such as saving the last few minutes of gameplay after a challenging fight in […]

In order to navigate the world, an autonomous agent must build a causal model to understand the effects of its actions. In many tasks (automated car driving, automated medicine), collecting causal data, by performing arbitrary actions for the sake of measuring their effect (interventions), can be impractical, expensive and even unethical. On the other hand, […]

La photopléthysmographie (PPG) est une méthode non invasive mesurant les changements de volume sanguin dans les tissus. Cette technique permet de dériver des métriques physiologiques importantes, telles que la fréquence cardiaque, la saturation en oxygène et la pression artérielle. Cependant, pour des résultats fiables, il est crucial de prendre en compte les différences physiologiques des […]