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Ervin Sejdić

PhD


Description

Professor Ervin Sejdić, Research Chair in Artificial Intelligence for Health Outcomes at Research & Innovation, North York General Hospital, is an Associate Professor in the Edward S. Rogers Sr. Department of Electrical & Computer Engineering at the University of Toronto. He received B.E.Sc. and Ph.D. degrees in electrical engineering from the University of Western Ontario in 2002 and 2008, respectively. He was a postdoctoral fellow at the University of Toronto with a cross-appointment at Holland Bloorview Kids Rehabilitation Hospital, Canada’s largest children’s rehabilitation teaching hospital. From 2010 until 2011, he was a research fellow at Harvard Medical School with a cross-appointment at Beth Israel Deaconess Medical Center. In 2011, Professor Sejdić joined the Department of Electrical and Computer Engineering at the University of Pittsburgh as a tenure-track Assistant Professor, subsequently promoted to a tenured Associate Professor. He also held secondary appointments in the Department of Bioengineering (Swanson School of Engineering), the Department of Biomedical Informatics (School of Medicine), and the Intelligent Systems Program (School of Computing and Information) at the University of Pittsburgh. From his earliest research, he has been eager to contribute to the advancement of scientific knowledge through carefully executed experiments and ground-breaking published work. For his strong contributions, Sejdić was named the editor-in-chief of Biomedical Engineering Online; an area editor of the IEEE Signal Processing Magazine, the highest rated journal in the field of signal processing; and an associate editor of Digital Signal Processing and IEEE Transactions on Biomedical Engineering. Sejdić’s research interests include biomedical signal processing, gait analysis, swallowing difficulties, advanced information systems in medicine, rehabilitation engineering, assistive technologies and anticipatory medical devices. Sejdić is committed to excellence in education and strives to guide and motivate students to fully understand the fundamental principles of applied sciences, and pays considerable attention to providing students with a learning environment that stimulates collaborative discussions.

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Associated Programs

Digital Health Solutions for Learning Health Systems

Using health data to better understand those living with diabetes and transform diabetes self-management.