What began as a quest by neurotechnology engineer Gerard O’Leary to design an implantable device to reduce the intensity and frequency of seizures in dogs with epilepsy has resulted in the development of a digital platform predicted to transform veterinary science.

The platform, known as NXVET, streamlines the process of collecting physiological data from animal patients using AI-connected medical devices, including the patented NXSCOPE stethoscope attachment. The device automates data collection and reduces clinical documentation time by as much as 30 per cent, enabling more accurate, data-driven diagnostics.

“The Schmidt Fellowship gave me the opportunity to explore a niche area of applying AI to veterinary healthcare,” says O’Leary, who completed his fellowship under Professor Alex Mariakakis in the Faculty of Arts & Science’s Department of Computer Science, and Professor Taufik Valiante in the Temerty Faculty of Medicine’s Department of Surgery, who is also a senior scientist at the University Health Network.

“The commercial opportunity to expand the initial research into more general applications directly translated into improving our NXVET technology. Ultimately, the aim is to transform clinical workflows and extend this holistic approach to human healthcare.”

Md Abdul Halim, co-founder and CEO of CredoSense, is working to replace today’s expensive and often unreliable environmental monitoring tools with integrated, accessible solutions that deliver lab-grade accuracy through field-ready systems for precision agriculture and ecosystem management. In parallel with his work at CredoSense, Halim’s overarching research goal is to advance methane monitoring technologies—targeting a greenhouse gas more than 25 times as potent as carbon dioxide—and to develop effective mitigation strategies for climate-smart cities.

“We’re building our flagship product—a single-tool solution that integrates AI-powered plant health diagnostics with real-time analytics—designed to empower users, especially in developing regions, to make physiologically meaningful, crop-optimized decisions quickly and reliably,” says Halim, who completed his fellowship under Professor Debra Wunch in the Department of Physics and the School of the Environment in the Faculty of Arts & Science, and Professor Sean Thomas at the Institute of Forestry and Conservation at the Daniels Faculty of Architecture, Landscape, and Design.

Biomedical engineer Mehdy Dousty is paving the way for technology that predicts falls in older adults through an initiative called RadioVision. Hospital‑based fall‑risk assessments miss the real‑world hazards— slippery bathrooms, cluttered bedrooms, choice of footwear, mood‑driven movements, and overall home layout — that only an in‑home assessment can truly capture. Bridging this gap requires affordable, privacy‑preserving technologies that deliver personalized fall‑prevention insights in the home without saturating every room with a dense network of sensors.

“We’re turning invisible radio‑frequency waves into a real‑time, privacy‑preserving ‘motion map’ of the home,” says Dousty, who is working with Professor Ervin Sejdic in the Edward S. Rogers Sr. Department of Electrical & Computer Engineering at the Faculty of Applied Science & Engineering and Professor David Fleet in the Department of Computer Science at the University of Toronto and the Vector Institute. “By reconstructing residents’ full‑body poses—no cameras required—we can spot risky movements and predict exactly when and where falls might occur.