This project explores the feasibility of using a hybrid sensing system that combines Near-Infrared Spectroscopy (NIR) and Electronic Nose (E-Nose) technologies, enhanced by machine learning, to detect early signs of spoilage and contamination in stored grains. By analyzing changes in grain structure and gas emissions, the study contributes to ongoing research on reliable, non-destructive, and […]

The increasing severity of climate change and glacial pace of emissions reform is requiring the development of new strategies for atmospheric CO2 drawdown. One of the approaches that has been gaining traction is Ocean Alkalinity Enhancement (OAE), a method that increases the physical absorption of atmospheric CO2 into the ocean by dispersing alkaline materials in […]

The rapidly increasing global use of cannabis and the increasing potency of ?9-tetrahydrocannabinol (?9-THC), the primary psychoactive component, necessitate rapid, sensitive, and portable detection methods for drug screening. Traditional chromatographic and spectroscopic techniques, while accurate, have limitations that hinder their use in point-of-care (POC) and real-life scenarios. Electrochemical sensors offer a promising alternative due to […]

The main objectives of the project are designing, developing, and integrating a high-resolution electromagnetic mapping instrument, with interchangeable sensor arrays or sensor suites for single-sided access, non-contact characterization of materials, by evaluating different electromagnetic properties (i.e., electric conductivity, magnetic permeability, dielectric constant) while using an intelligent modular architecture. Sustainability of new and improved manufacturing methods, […]

This project aims to enhance proficiency estimation in large-scale assessments by improving missing-data imputation techniques. Specifically, the study focuses on refining Multiple Imputation with Denoising Autoencoders (MIDAS)—a deep learning-based approach—by incorporating item response time as an additional contextual feature. Unlike traditional item response theory (IRT) or regression-based methods, which rely on strong assumptions, the proposed […]

Quantum imaging is a microscopy technique that uses special properties of light to observe smaller features and have higher sensitivity than classical methods, especially in low-light or noisy environments like deep tissue imaging. It uses special quantum properties, such as entanglement, which is often called “spooky action at a distance” and photon-number squeezing, which is […]

Recent studies in quantum computing have demonstrated that the localized unitary Jastrow (LUCJ) ansatz, a promising electronic structure method capable of running on near-term quantum hardware, can surpass exact solutions on classical hardware by using quantum-centric supercomputing. However, scalable and efficient methods for initializing the LUCJ ansatz remain underexplored in current research. We propose a […]

Through semi-structured interviews with current Mexican indigenous migrant men and women and extended family members, my dissertation inquiry focuses on how indigenous peoples – men and women – in Mexico have experienced (and continue to experience) the transition from subsistence to commercial agriculture. The core objective of my doctoral research is to bridge the existing […]

Dans un contexte hivernale de plus en plus changeant, il devient primordial de se doter de méthodes de détection efficaces. Ce projet vise à développer et valider des méthodes de détection des contaminants dans les produits de dégivrage aéroportuaires afin d’optimiser leur efficacité et réduire leur impact environnemental. En combinant des approches analytiques avancées et […]

Dhiyati Inc. is a prominent Canadian education consultancy in Toronto, that connects students with over 300 diploma and certification programs from private career colleges across Ontario. By leveraging its extensive network, Dhiyati plays a vital role in bridging the gap between education and employment, ensuring students acquire the skills necessary for success in the Canadian […]

The project at L’Arche Fredericton aims to create a sustainable and long-term monthly donor program to support individuals with intellectual and developmental disabilities. The intern will help develop digital fundraising strategies, manage donor relationships, and use data-driven approaches to increase engagement and retention. By the end of the project, the goal is to establish a […]

Xello is a leading college and career readiness platform designed to engage K-12 students in career exploration, academic planning, and skill development. It provides educators with data-driven insights to support student success, helping school districts make informed decisions. To maintain its market leadership and enhance user experience, Xello seeks to improve its survey platform. The […]