Développement d’un algorithme de retrait de la voix dans une trame audio pour la génération de signaux haptiques

L’entreprise D-BOX oeuvre dans le domaine du divertissement et de la réalité augmentée grâce à ses sièges avec rétroaction haptique qui offrent une expérience sensorielle plus riche, que ce soit pour l’industrie du cinéma ou celle des jeux vidéo. Bien qu’il soit possible d’annoter manuellement la trame haptique pour une scène de film, il est […]

Read More
Realistic and High-Performance Rendering Renewal

The goal is to investigate the realistic appearance models for complex reflectance properties, modeling reflectance, masking and inter-reflection at many scales. In the end, comparison and basis-space representation will be leveraged to develop an interactive rendering application for pre-visualization and in-game portrayal of complex materials.

Read More
Leveraging Stacks of Predictors for Efficient Inference and Uncertainty Estimation

Given the ever growing neural networks being developed and the abundant empirical evidence that model/data scale play an important role in enabling high-quality models of data, inference cost becomes a bottleneck to the deployment of state-of-the-art automated predictors. To address that, this research project aims to develop algorithms that can predict outcomes by combining predictions […]

Read More
The Psychological Underpinnings of Church Conflict: Analysis of the Ukrainian and Moscow Churches situations in Ukrainian Orthodoxy

This comprehensive study aims to explore the root causes of the ongoing conflict between the Ukrainian and Moscow churches through a multidisciplinary lens. Drawing on literary and religious psychology analysis, the article examines the complex historical, cultural, and psychological factors that have contributed to the conflict, providing a nuanced understanding of the ongoing tensions between […]

Read More
Exploring Alternatives with Design Analytics Interfaces: A Human-Centered Approach for Integrating Generative Design and Performance Assessment with Machine Learning-Based Surrogate Modelling

Designing built environments is a complex process that involves generating and evaluating alternative solutions using computational tools. In the Architecture, Engineering, and Construction (AEC) industry, designers use generative design methods to explore a larger number of alternatives and ML-driven rapid performance prediction to identify potential issues early on. However, separating these tasks hampers creative flow […]

Read More
Enhanced Tool Support for Gradle Build Systems

The main goal of the project is to discover if program analysis approaches can be adapted to the context of Gradle build systems. Thus, during the research it is planned to implement support for Gradle build systems within an existing program analysis toolchain that have been developing at the University of Waterloo. (currently specific to […]

Read More
Who are the ‘good Russians’ for Ukrainians during the full-scale war? Attitudes of the Ukrainian society to the Russian opposition in the social media space

The research project aims to examine the attitudes of Ukrainians towards Russians, particularly about the concept of ‘good Russians’ during the ongoing full-scale war. The study will include the exploration of the socio-historical background of Russian-Ukrainian relations, as well as the analysis of the changes in attitudes before and after the Russian aggression in 2014. […]

Read More
Detecting Phishing Websites using Machine Learning Techniques

The project “Detecting Phishing Websites using Machine Learning Techniques” aims to develop a method that can accurately identify and block malicious websites. Machine Learning algorithms will be used to analyze various website features, such as URL, page content, rank and other indicators to determine if it is a phishing site or not. By identifying and […]

Read More
Data-Driven and Synthesis-Guided Generalization in CHC-Solving

The intern will be working on a research project aimed improving scalability and applicability of automated reasoning tool called SPACER by improving the way it deals with special data types. Overall, the goal of this project is to make SPACER a more effective and reliable tool for verifying program correctness.

Read More
Individual problem solving: experiments on open-ended problems

Open-ended problem solving plays an important role in industrial innovation, product development, strategy formulation, and many other applications. The study will use experimental methods to investigate the behaviour of individuals while solving open-ended problems, and will entail the gathering and analysis of both qualitative and quantitative data. Individual problem-solving tasks will be given to participants […]

Read More
Building and testing a simulator of human-computer interface for small modular nuclear reactors

The project is dedicated to the explore how the effective interface for a small modular nuclear reactor should look considering human factors and current digital technology design trends. The research will review the significance and application of modern human-computer interaction techniques to ensure a better user experience and to achieve substantial safety and operational benefits […]

Read More
Advancing Generative Models for Vision and Language: A Collaborative Study with ServiceNow Research and ÉTS Montréal

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, […]

Read More