Meg Ghias is a Machine Learning Resident at Amii, where he helps industry partners turn complex healthcare data into practical, deployable AI solutions. He began his career as a manufacturing engineer, optimizing machines and production systems, until he became far more curious about the most complex system of all: the human body. That curiosity led him to an MSc in Mechanical Engineering at the University of Calgary, where he applied deep learning to predict blood transfusion needs in critically ill ICU patients. As a Research Associate in the University of Calgary's Department of Surgery, he has also worked on identifying trauma patients at risk of deterioration before they reach the hospital. Across these projects, Meg focuses on developing AI that clinicians can understand, trust, and actually put to work.

Outside of work, Meg is a teacher at heart and tutors high school students in math and science, which keeps him sharp at explaining complex ideas simply. He has a soft spot for minimalist and retro design, loves travelling and exploring new cultures, and is currently growing herbs and leafy greens in a hydroponic garden at home.