This project aims to improve how polymer-based solvents are modeled during freezing and solidification processes that are critical to modern semiconductor manufacturing. Building on prior experimental and theoretical studies (i.e., the collaborative work from participated institutions), the project will develop an accurate and reliable computational framework that captures how heat transfer and mechanical stresses interact […]

Quantitative LUS (Q-LUS) is a safe, real-time imaging tool that exploits the frequency dependency of imaging artifacts to extract biomarkers that characterize the lung disease. However, the direct relationship between Q-LUS biomarkers and the severity of lung injury remains insufficiently characterized. Without this grounding, Q-LUS metrics remain difficult to interpret and cannot be linked to […]

This research project explores a fundamental anomaly in fluid mechanics: the potential for simple liquids to exhibit solid-like elasticity under extreme conditions. Conventionally, Newtonian fluids are understood to lack elasticity because they dissipate deformation energy almost instantly through viscous flow. However, research demonstrated that liquid glycerol exhibits “rubber-like” elasticity when subjected to ultrafast, high-strain-rate laser […]

Transportation policy is already a health policy because the air we breathe along roads is shaped by what we drive and how we move. In 2026, Canada and the US’s renewed push for electric vehicles (EVs), which can also become an immediate public health opportunity. Yet health benefits are not automatic, because “zero tailpipe” from […]

My project will develop and pilot a practical framework to evaluate one clinical AI tool across three areas at the same time: how well it works, whether it works equally well for different patient groups, and what its environmental impact is. I will use the University of Melbourne’s Validitron simulation facility to test the tool […]

This project addresses Canada’s urgent need for sustainable extraction of strategic materials, particularly nickel and cobalt from mining waste streams, essential for electric vehicles, batteries, and renewable energy technologies. This 18-week internship focuses on developing breakthrough electrochemical technology to recover critical minerals from pyrrhotite tailings while generating green hydrogen. The research intern will work on […]

Understanding spoken language requires integrating multiple acoustic and physical properties of the speech signal into composite representations. This proposal is part of a larger international collaboration aimed at understanding how pitch—a fundamental property of language—is encoded in the brains of speakers across a wide range of languages (e.g., English, Japanese, Korean, Mandarin Chinese), each of […]

This project brings together a multi-institutional collaboration among the University of Toronto (Canada), the Technical University of Munich (Germany), and the Université de Paris Cité (France) to investigate the role of reactive hydrogenation intermediates in the catalytic hydrodeoxygenation of lignin-derived phenolic compounds. Understanding these intermediates is critical for advancing sustainable catalytic pathways for biomass valorization. […]

This community-based research project will partner with Toronto Environmental Alliance (TEA) to identify how place-based community hubs – such as community centres, neighbourhood organizations, and frontline service non-profits – can catalyze equitable climate action. This project will help us understand how to address climate change equitably. Research has shown that climate action to date has […]

Title :System-of-Systems Solution with Quantum Simulation for Monitoring, Reporting, Validation, and Verification of GHGs/Carbon Cycle in Biodiversity Ecosystems for SEPLS to Strengthen Sustainable Overview: This project aims to develop a System-of-Systems solution using quantum simulation to monitor, report, validate, and verify greenhouse gases (CO2, CH4, N2O) and the carbon cycle in biodiversity ecosystems, particularly in […]

Artificial Intelligence (AI) is increasingly used in Canada to help make decisions and to deliver public services, but research shows that AI systems can unintentionally reinforce social inequalities, leading to unfair or discriminatory outcomes for minority groups. Biases can appear when AI systems are trained on incomplete or skewed datasets, when development teams lack diverse […]

This community-based research project, undertaken through the U of T Climate Hub Catalyst Internship, partners with the Toronto Chinatown Land Trust (TCLT)-a community-controlled effort to build an inclusive, culturally competent, and ever-evolving Chinatown in Toronto. TCLT acquires, develops, and stewards land in perpetuity for community needs and benefit. Operating with the understanding that Chinatown exists […]