Dr. Jesse Hoey is an associate professor in the David R. Cheriton School of Computer Science at the University of Waterloo. He is also an adjunct scientist at the Toronto Rehabilitation Institute in Toronto, Canada, where he is co-leader of the AI and Robotics Research Team. Dr. Hoey received the B.Sc. degree (1992) in physics from McGill University in Montreal, Canada, the M.Sc. degree (1995) in physics and the Ph.D degree (2004) in computer science from the University of British Columbia in Vancouver, Canada. From 2004-2010, he was an assistant professor in the School of Computing at the University of Dundee, Scotland. In 2014-2015 he was a visiting professor at the Institut National de Recherche en Informatique et en automatique (INRIA) in Sophia-Antipolis, France.
He has published over fifteen peer reviewed scientific papers in highly visible journals, and over fifty conference and workshop publications. Professor Hoey works in artificial intelligence, affective computing, and health informatics. He is primarily interested in developing computational models of human interactions with machines, and in using these models to build artificially intelligent applications in healthcare. This research involves four main aspects. First, he works on decision theoretic planning, particularly on Markov decision processes (MDPs), and their partially observable counterparts, POMDPs. He is interested in learning these models from data, and on solving them, particularly for large state, action, and observation spaces. Second, he works on sensor-based recognition of human behaviour (including gesture, facial expression and gait/body posture) from dynamic sensor streams (including video). He is interested in task-oriented sensor stream analysis (e.g. computer vision), in which the goal is to optimise over the action/policy space for an automated agent. Third, he works on computational models of social and emotional behaviours of humans. This work integrates sociology, social psychology, and affective computing. Lastly, he uses sensors, decision theoretic models, and computational social science, to build assistive systems for persons with physical and cognitive disabilities. In particular, he is interested in systems that help a person with dementia during activities of daily living (ADL) using cameras and other sensors to inform decision processes with multiple and competing objectives. He is particularly interested in detecting and responding to emotional states of persons with these assistive technologies.