Reza Rashidi Far
About Reza Rashidi Far
Reza Rashidi Far is a Strategic Product Manager and Principal LiDAR & AI System Product Engineer at LeddarTech, with a strong background in electrical engineering and applied mathematics. He has held various roles in research and engineering, contributing to advancements in sensor technology and machine learning applications for advanced driver assistance systems.
Work at LeddarTech
Currently, Reza Rashidi Far serves as the Strategic Product Manager and Principal LiDAR & AI System Product Engineer at LeddarTech. He has been with the company since 2018, focusing on mastering LiDAR sensor technology. His role involves overseeing product development and integrating advanced technologies into the company's offerings. LeddarTech specializes in providing solutions for the automotive and mobility sectors, emphasizing the importance of sensor technology in enhancing safety and efficiency.
Previous Experience
Reza Rashidi Far has a diverse professional background. He worked at Magna International as a Research Engineer from 2015 to 2018, contributing to automotive technology in the Toronto area. Prior to that, he held positions at CAE as a Senior Technical Staff - Systems S/W Specialist from 2011 to 2014 and at the Canadian Space Agency as a Visiting Fellow - Researcher from 2007 to 2010. His early career included roles at Queen's University as a Postdoctoral Fellow and Teaching Assistant, as well as an internship at Nortel Networks.
Education and Expertise
Reza Rashidi Far holds multiple degrees in engineering and applied mathematics. He earned his Bachelor of Science in Electrical and Electronics Engineering from Isfahan University of Technology. He then completed a Master of Science in Telecommunications and Signal Processing at K. N. Toosi University of Technology, followed by a Ph.D. in Signal Processing and a Master of Science in Applied Mathematics at Queen's University. His educational background supports his expertise in areas such as deep learning, machine learning, and point cloud processing.
Technical Contributions
Reza Rashidi Far has made significant contributions in various technical domains. He has developed sensor modeling for simulation products, utilizing Software-in-the-Loop (SiL) and Hardware-in-the-Loop (HiL) methodologies. His work includes data pipeline strategy development, focusing on acquisition, calibration, and training for deployed platforms. He specializes in GPU programming with openCL and CUDA, and has experience in computer vision using openCV. His research also encompasses advanced topics such as anomaly detection in airborne images and remote calibration of satellite imagers.
Research and Development Projects
Throughout his career, Reza Rashidi Far has engaged in numerous research and development projects. He has worked on deep learning applications for Advanced Driver Assistance Systems (ADAS) and has expertise in point cloud processing techniques. His research includes studying asymptotic eigenvalue distribution of matrices for applications in beamforming and MIMO systems. Additionally, he has experience with various data sources, including CAN bus, AFDX, and ARINC, which are critical in the fields of automotive and aerospace engineering.