Research summary
Machine learning uses data and algorithms to imitate the way humans think—and is behind everything from chatbots and predictive text to the machines that can diagnose medical conditions based on images. Machine learning also presents opportunities for engineering, but we are not yet using it to its full potential.
Dr. Katarina Grolinger, Canada Research Chair in Engineering Applications of Machine Learning, is developing solutions for smart systems to overcome barriers to the use of machine learning in engineering practices. She and her research team are designing distributed machine learning approaches that better match the distributed nature of data and connected devices. They have several aims, including ensuring that systems adapt to changing environments, integrating “explainability” and fairness into machine learning, and providing scalable, sustainable solutions. The solutions they develop will drive the responsible use of machine learning in engineering and increase its economic and social benefits.