Engineering a data-driven health-care revolution
Share this story

Carleton engineering students conducting biomedical research are on the vanguard of a data-driven health-care revolution. By using Artificial Intelligence (AI), they’re mining, processing and analyzing data on an unprecedented scale.

Kevin Dick, a Biomedical Engineering PhD student, is exploring protein interactions, seeking to identify problematic bindings that lead to illness and ultimately forge a path to therapeutic treatments to prevent them. In his research, he’s using machine learning, a type of AI that allows computers to learn without being explicitly programmed.

“We’re using state-of-the-art tools,” says Dick, who uses the Carleton University Bioinformatics Research Group’s Protein-protein Interaction Prediction Engine (PIPE) and the Scoring Protein Interaction (SPRINT) algorithm developed at the University of Western Ontario.

Cutting-edge research and innovation are core ingredients for a thriving, globally competitive economy and also help produce the breakthroughs that lead to healthier lives and communities across the province.


“Very few research groups look at interaction networks of this magnitude. The potential is almost limitless. Machine learning and AI are becoming major tools to make general research more efficient.”
Kevin Dick
Biomedical Engineering PhD student at Carleton University
More Stories
Lifelong learning, with five degrees and counting
Leveraging location to increase access to COVID-19 vaccines
Developing an easy-to-build ventilator