Summary
Michael Guerzhoy is an Assistant Professor (Teaching Stream) in Engineering Science at the University of Toronto who blends deep academic teaching in machine learning, computer vision, and data science with hands-on healthcare and industrial applied research. He has a decade of experience spanning lecturing roles at Princeton and U of T, senior data science work at St. Michael’s Hospital, and successful industrial R&D at Seiko Epson where his image-processing work was productized and earned patents and an R&D award. An early adopter of practical deep learning in education, he introduced TensorFlow to a neural networks course months after its release and pioneered an intro ML assignment on policy-gradient reinforcement learning using OpenAI Gym. His research contributions include award-winning human mobility modeling and ongoing consulting for both industry and academia, often providing pro bono support for academic projects. Comfortable moving between theory, teaching, and production code, he maintains a selective consultancy while serving on international committees such as the IOAI scientific committee.
10 years of coding experience
16 years of employment as a software developer
Master of Science (M.Sc.), Statistics, Master of Science (M.Sc.), Statistics at University of Toronto
Honours Bachelor of Science (Hon. B.Sc.), Computer Science, Mathematics, Statistics, Honours Bachelor of Science (Hon. B.Sc.), Computer Science, Mathematics, Statistics at University of Toronto - University College