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Farhang Sahba

Farhang Sahba

Professor

Faculty of Applied Science & Technology

farhang.sahba@sheridancollege.ca

Farhang is a professor of Electrical and Computer Engineering at Sheridan College. He received his BSc in Electrical Engineering from Isfahan University of Technology, his MSc in Electrical Engineering from Toosi University of Technology, and his PhD in Image and Signal Processing from the University of Waterloo.

Farhang followed his education with a postdoctoral fellowship at University of Toronto, and Ryerson University’s Signal and Information Processing Lab, where he conducted a number of research projects in the fields of image and signal processing, machine learning, and fuzzy systems.

Prior to joining Sheridan, Farhang was a senior research engineer with Merge Healthcare working on the design and implementation of a computer-aided diagnosis engineering platform for magnetic resonance imaging systems. He also worked as a research scientist with Segasist Technologies, where he carried out research on an innovative intelligent segmentation technology for image analysis systems.

Farhang was part of the committee responsible for the development of Sheridan's Electrical Engineering Bachelor's Degree program. In addition, he has worked as the technical lead for several applied research projects in Sheridan's School of Mechanical and Electrical Engineering Technology. His main research areas are artificial intelligence, machine learning, computer vision, and IoT-based 5G networks.

Farhang is a member of the Professional Engineers Ontario (PEO) and a senior member of the Institute of Electrical and Electronics Engineers (IEEE). In addition, he is a member of the IEEE Computational Intelligence Society, IEEE Robotics and Automation Society, and IEEE Signal Processing Society. He has acted as a reviewer for several conferences and journals and has more than 40 papers published in various journals, conferences, book chapters, and technical reports.

Research Interests

  • Farhang's main research areas are machine learning, computer vision, and IoT-based platforms.
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