Dr. Farnaz Derakhshan received her PhD in Computer Science from the University of Liverpool in the UK and her MSc and BSc degree in Computer Engineering from IUST, Iran Universities. She is a lecturer, researcher and the author of books, academic journal papers and conference papers. Farnaz has worked in many different academic roles including teaching and research activities at international universities and colleges, in Canada, Iran and the UK.
She joined the Faculty of Applied Science and Technology at Sheridan College as an instructor in 2020 and is a researcher with Sheridan's Centre for Mobile Innovation (CMI).
Farnaz is a part-time faculty member at Humber College, and is a lecturer at College of Engineering, Northeastern University at the Toronto Campus. She worked as a tenured faculty at the University of Tabriz, Iran from 2009 to 2020, which provided her with a wealth of experience in teaching and research. In addition, she was a teaching assistant at the University of Liverpool, UK.
She has taught post-graduate and undergraduate courses and was the supervisor of three successful PhD candidates and 16 successful MSc students. She had a research collaboration with the University of Guelph for two years.
Contributions to research
Dr. Farnaz Derakhshan is the Principal Investigator for a CMI, Sheridan and Tech4Life Enterprise project titled: "From Digital to Smart Stethoscope – Adding Decision Support and Artificial Intelligence to eSteth."
Tech4Life is an Ontario-based company and one of the enablers of Telemedicine around the world. The company has designed a digital stethoscopes eSteth and eSteth Pro. Digital stethoscope can convert an acoustic sound to electronic signals, which can be further amplified for optimal listening. These electronic signals can be further processed and digitalized to transmit to a personal computer, laptop or mobile device. Researchers at Sheridan are working on adding more capabilities to eSteth (e.g. adding Artificial Intelligence/Machine Learning (AI/ML) to support heart disease Diagnosis).
Nathaniel Mastracci, Farnaz Derakhshan, Edward Sykes, Dodo Khan, "Classification of Heart Sounds Using Machine Learning," IEEE Conference on Digital Health Technologies (ICDH), Washington, US, July 2023 (Accepted).