Machine learning is an active field of research and development to provide tools and technologies for finding significant patterns in data. Behind every face detection and face recognition software in digital cameras or social network websites a constantly under-development machine learning algorithm is working. Nowadays in any practical applications of machine learning we have to […]

Machine learning is an active field of research and development to provide tools and technologies for finding significant patterns in data. Behind every face detection and face recognition software in digital cameras or social network websites a constantly under-development machine learning algorithm is working. Nowadays in any practical applications of machine learning we have to […]

Automated human body pose estimation and activity recognition in videos is still one of the challenging problems in computer vision. Generally, it is becomes a significantly difficult task in real world applications due to camera motion, cluttered background, occlusion, and scale/viewpoint/perspective variations. Moreover, the same action performed by two persons can appear to be very […]

This project will investigate and develop advanced algorithms for high dynamic range projection using caustic image formation. These algorithms dynamically redirect light from dark image regions to bright regions, which addresses the problems of low peak luminance and poor black levels in current projectors. The algorithms will improve upon existing lensing methods by increasing computational […]

This research investigation aims to assess a set of well known NP-Hard problems that are currently only solvable with an approximation, and prototype implementations of a general solution to their class of problem previously developed by 1QBit. This requires a series literature and prior art reviews, prior to the development of new algorithms and code […]

This project develops programmable micro-lens arrays made from soft, temperature-responsive liquid crystal elastomers (LCEs). Using digital micromirror lithography, the research will enable lenses that can adjust their focus through controlled shape changes. The collaboration between the University of Waterloo and Kent State University aims to advance adaptive optics for next-generation imaging and sensing technologies.

Recent years have witnessed a boom in the construction of modern high-rise buildings in megacities around the world. It is important to design a high-rise building that can effectively withstand both wind and earthquake loads. Nonetheless, in current practice, the design of high-rise buildings for wind and earthquakes is done independently. Hence, there is an […]

This project aims to turn raw underwater video into decision-ready science. Our software automatically detects, classifies, and counts marine species, then delivers results in a simple web dashboard with linked video clips, maps, and exportable reports. Instead of annotating from scratch, ecologists just review and correct AI suggestions—cutting review time by more than half. Built […]

The need for better measurement of emergency response teams has been recognized as one of the key challenges that characterize the field of team work studies. Ideally, when assessing team performance, one should combine information about the nature of the team (e.g., what is the team structure?) and about its members (e.g., is one of […]

The study of complex systems using networks has become a central theme across disciplines, from social sciences and economics to biology and information systems. Graph theory, which models entities as nodes and their pairwise relations as edges, has provided a powerful framework for analyzing such systems. Graph-based methods have enabled advances in tasks such as […]

In boreal and temperate regions, dams are mainly constructed to provide ecosystem services such as hydroelectricity production. River impoundment and the alteration of natural hydrological regimes are suggested to be major disturbances to aquatic ecosystems. To meet long-term environmental objectives for sustainable development, Hydro-Quebec recently adopted the Life Cycle Assessment (LCA) approach. LCA is an […]

Physics-Informed Neural Networks (PINNs) have emerged as a powerful tool for solving PDEs, fractional equations, and eigenvalue problems, making them particularly suited for quantum mechanics, where traditional numerical methods often face computational bottlenecks. The aim of this internship is to analyse the applicability of PINNs to a broad range of quantum simulation tasks such as […]