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 holds a B.Sc. and M.Sc. in mechanical engineering 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.
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Zeynab Rokhi is a Ph.D. candidate in mechanical engineering at McMaster University, working under the supervision of Dr. Ali Emadi at the McMaster Automotive Resource Centre (MARC). She began her doctoral studies in September 2022, focusing on improving intelligent transportation systems through the development of automatic calibration methods for on-road radar and camera sensors. Her current research involves building a data-driven framework to enhance vehicle detection and tracking in real-world traffic environments. As part of her doctoral work, she led an industry-driven project aimed at improving the alignment and fusion of radar and camera data at intersections to support smarter, more responsive transportation systems.
Zeynab earned both her B.Sc. and M.Sc. in mechanical engineering from Sharif University of Technology in Tehran, Iran, in 2018 and 2021, respectively. During her time there, she contributed to projects at the Center of Excellence in Design, Robotics, and Automation, including the development of a full-body 3D scanning mechanism and the implementation of facial emotion recognition capabilities on humanoid robots. Her master’s research focused on AI-based human-robot interaction, integrating deep learning with real-time vision systems.
With a multidisciplinary background in robotics, artificial intelligence, and computer vision, Zeynab is passionate about applying advanced technologies to address key challenges in intelligent transportation and autonomous vehicle systems.
