This is the professional homepage of Arash Abadpour.

I finished my Ph.D. at the Electrical and Computer Engineering Department, University of Manitoba, under the supervision of Professor Attahiru S. Alfa and my M.Sc. in Sharif University of Technology, under the supervision of Dr. Shohreh Kasaei. I am currently a Senior Scientific Developer at Fio Corporation, Toronto, Canada. Previously, I was a Research Scientist at Intellijoint Surgical (IJS), Waterloo, Canada, for fifteen months. Before that, I was a Researcher with the Imaging Group at Epson Edge, Epson Canada Limited, for six years. I have previously worked as a Researcher for TRLabs, Winnipeg. I can be reached at the phone number +1 647 567 3487 or through the email address arash@abadpour.com.

I am enthusiastic about things that survive. It could be a living organism which evolves and adapts to the changing environment or an algorithm that is robust against noise and the unknown. I have a Ph,D. in electrical engineering, and I have indeed worked as an electrical engineer, but the best thing that I am capable of doing, and love doing, is designing algorithms which very distantly resemble human cognition, especially in the field of vision and visual perception. I like reading books and watching films and writing code and interacting with human beings. Work needs to be more than merely a survival mechanism. I have managed to make it be that way.

You can download my complete CV in pdf format or visit this page to download my academic papers. A long version of my CV can be found here.


  • April 2016 – Joined Fio Corporation as Senior Scientific Developer
  • October 2015, New Paper – Arash Abadpour, “Rederivation of the Fuzzy-Possibilistic Clustering Objective Function through Bayesian Inference”, Fuzzy Sets and Systems, Accepted for Publication, October 2015 (pdf).
  • September 2015, Patent PublishedHolocam Systems and Methods, US Patent US20150261184, Publication Date 17 September 2015 (pdf).
  • August 2015, New Paper – Arash Abadpour, “Incorporating spatial context into fuzzy-possibilistic clustering using Bayesian inference”, Journal of Intelligent and Fuzzy Systems, Accepted for Publication, August 2015.

Last update: April 2016