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Ervin Sejdic CRANIA

Dr. Ervin Sejdić received B.E.Sc. and Ph.D. degrees in electrical engineering from the University of Western Ontario, London, Ontario, Canada in 2002 and 2008, respectively. From 2008 to 2010, he was a postdoctoral fellow at the University of Toronto with a cross-appointment at Bloorview Kids Rehab, 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. From 2011 until 2021, he was a faculty member at the University of Pittsburgh. In 2021, he joined the University of Toronto as a faculty member. He is also the Research Chair in Artificial Intelligence for Health Outcomes at North York General Hospital in Toronto. From his earliest exposure to research, he has been eager to contribute to the advancement of scientific knowledge through carefully executed experiments and ground-breaking published work. This has resulted in co-authoring over 150 publications. In February 2016, President Obama named Dr. Sejdić as a recipient of the Presidential Early Career Award for Scientists and Engineers. In 2017, Dr. Sejdić was awarded the National Science Foundation CAREER Award. In 2018, he was awarded the Chancellor’s Distinguished Research Award at the University of Pittsburgh. Dr. Sejdić is the editor-in-chief of Biomedical Engineering Online, an associate editor for IEEE Transactions on Biomedical Engineering and Digital Signal Processing. Dr. Sejdić’s passion for discovery and innovation drives his constant endeavors to connect advances in engineering to society’s most challenging problems. Hence, his research interests include biomedical signal processing, gait analysis, swallowing difficulties, advanced information systems in medicine, rehabilitation engineering, assistive technologies and anticipatory medical devices.    

Contact Me

  • Research Chair in Artificial Intelligence for Health Outcomes, North York General Hospital
  • Artificial intelligence
  • Machine learning
  • Swallowing
  • Gait
  • Brain-computer interfaces
  • Signal processing
  • Image processing