This project address the so-called Quantum Marginal Problem from a mathematical, physics and computational perspective. It develops the mathematical theory of optimal transport adapt to quantum states in order to make fundamental advances in physical aspects and computational algorithms solving the quantum marginal problem.

When Kinaxis trains its machine learning models, it does so on two time scales. Every week or so, it looks at around 10 billion sales records and tries to learn the rapidly-changing “parameters” that best describe this data. Every 3-6 months, it updates 10 thousand collections of “hyperparameters” that govern the parameter-learning process. Kinaxis would […]

This research project aims to develop a comprehensive predictive framework for heat treatment furnaces to enhance operational efficiency, product quality, and environmental sustainability. The project focuses on creating a data preprocessing pipeline tailored for big machinery sensor data, innovative AI-enabled anomaly detection models, real-time furnace operation analysis, and quality prediction models. Key objectives include obtaining […]

Understand the performance of wood shearwalls with respect to heightened seismic loads especially for multi-storey wood structures. The proposed project is conducted in collaboration with the Canadian Wood Council as the industrial partner, and it aims to address the impact of extending the light frame wood shearwalls to taller buildings especially as it pertains to […]

This research project enables internship personnel, guided by their industry sponsors, to develop advanced software features for designing and operating vast solar power farms. Creating a digital twin of the system, these computational models apply the latest solar technologies to efficiently harvest light from the whole environment (sun, sky, and ground) under the complex shading […]

The proposed project studies the vibration behaviour of innovative mass timber floor systems, focusing on cross-laminated timber (CLT) floors supported by CLT beams and timber-concrete composite (TCC) floors with notched connections. Using laboratory testing and numerical modelling, the research aims to enhance the understanding of how these floors respond to dynamic loads, including the effects […]

This research investigates the fusion of multi-source geospatial data to overcome key scaling limitations in automated property assessment. The primary research problem addresses object occlusion in satellite imagery, where features can obscure ground-level surfaces and prevent accurate area measurement. We propose and evaluate a novel machine learning approach that geometrically fuses satellite imagery with ground-level […]

Nitrous oxide (N2O) is a powerful greenhouse gas with a global warming potential 298 times that of CO2, significantly contributing to climate change through agricultural activities, particularly the application of fertilizers. Accurate and scalable prediction of N2O emissions is essential for sustainable agriculture and climate mitigation. Current methods, such as LSTM-DLM neural networks proposed in […]

Surfactant Protein B (SPB) deficiency is a rare genetic disease where surfactant B is not produced in the lung, proper breathing fails and lungs collapse. The disease usually presents early in life, and unless lung transplantation is performed, no other approaches have provided long-term cure. Yet, lung transplantation is not an ideal approach either, as […]

Ethics Bowl Canada (EBC) is a not-for-profit that operates exclusively for the advancement of education. It’s purposes include (a) promoting and developing the teaching of critical thinking to the public in a way that is compatible with the standards of excellence of academia and (b) advancing education by providing a public forum for students and […]

Many effective Convex Optimization techniques face a common bottleneck: the resolution of large, sparse systems of equations. Despite the important advances in the state-of-art at theoretical and algorithm development, a significant challenge persists in the tendency to overlook the commercial viability of these algorithms. Recent strides in computer hardware, driven by advancements in AI and […]

Internationally, physical activity levels among children and youth are declining, while sedentary behaviours are increasing, leading to the global rise in non-communicable disease. This project aims to contribute to childhood physical activity promotion in Canada and worldwide, and to the international diffusion of scientific knowledge concerning childhood physical activity though three actions: 1. the evaluation […]