Assistant Professor, Teaching Stream, Mechanical Engineering
Applied Machine Learning
Diagnosis and Management of Mental Health; Medical Imaging; Brain-Computer Interfaces; Mechatronics
Sinisa Colic is an Assistant Professor, Teaching Stream with the Department of Mechanical and Industrial Engineering. He completed his PhD at the University of Toronto in the area of personalized treatment options for epilepsy using advanced signal processing techniques and machine learning. After that Sinisa was a postdoctoral fellow at McMaster University where he worked with medical imaging data for the diagnosis and treatment of mood disorders. To date Dr. Colic has contributed to a number of refereed publications, conference proceedings and presentations in the field of biomedical engineering. He was awarded best paper at the 35th Annual Conference of the IEEE EMBC in Osaka, Japan for his work on cross-frequency coupling for characterizing seizure-like events. In 2018 he was awarded the Digitech Innovation Prize in Paris, France for the commercial work on developing an EEG-based system for the management of major depressive disorder. Sinisa has taught several courses at University of Toronto covering a broad range of topics in mechatronics and machine learning.