Zeynab Rokhi is a Ph.D. candidate in Mechanical Engineering at McMaster University, where she develops automatic calibration systems for camera and radar sensors in intelligent transportation applications. She previously earned her B.Sc. and M.Sc. from Sharif University of Technology, where she conducted research in robotics and artificial intelligence. Her work bridges AI, computer vision, and embedded systems to address challenges in autonomous vehicle environments.
Full Profile
Zeynab Rokhi is a Ph.D. candidate in Mechanical Engineering at McMaster University, supervised by Dr. Ali Emadi at the McMaster Automotive Resource Centre (MARC). She began her doctoral studies in September 2022 with focuses on improving intelligent transportation systems through the development of automatic calibration methods for on-road radar and camera sensors. She is currently working on a data-driven framework that enhances vehicle detection and tracking performance in real-world traffic environments. As part of her doctoral studies, she led an industry-driven project aimed at improving the alignment and fusion of radar and camera data at intersections to support intelligent transportation systems.
She received both her B.Sc. and M.Sc. degrees in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, in 2018 and 2021, respectively. During her studies, she contributed to projects at the Center of Excellence in Design, Robotics, and Automation, where she developed a full-body 3D scanning mechanism and later implemented facial emotion recognition capabilities on humanoid robots. Her master’s research centered on AI-based human-robot interaction, combining deep learning and real-time vision systems.
Zeynab’s work draws on her multidisciplinary background in robotics, AI, and computer vision, and is driven by a passion for applying advanced technologies to solve critical problems in intelligent transportation and autonomous vehicle systems.
