Bio
Zahra Arjmandi is an assistant professor working in robotics and autonomous systems. Her research addresses uncertainty in perception and decision-making, with an emphasis on probabilistic estimation and the integration of learning-based methods into classical model-based frameworks.
She holds a PhD from York University, a Master of Science in Mechatronics Engineering from Amirkabir University of Technology (Tehran Polytechnic), and a Bachelor of Science in Mechanical Engineering from the University of Tehran. She subsequently held a joint postdoctoral research appointment at York University and the University of Waterloo. Her research has been published in IEEE IROS, IEEE CASE, ICAR, ITSC, and the International Journal of Robotics Research, and she has collaborated with industry partners including Thales Canada, contributing to a project recognized with the 2021 PEO York Chapter Engineering Research Project of the Year Award.
Her work spans the full development stack, from sensor modelling and signal processing through perception, planning, and deployment on physical platforms, an approach grounded in the conviction that robust autonomy is built by understanding how each layer of a system constrains the next. She brings the same perspective to teaching and mentorship, favouring course design and student supervision that put people in direct contact with real tools and real problem structures.
