Barza Nisar is a PhD candidate in Artificial Intelligence at the University of Toronto with eight years of experience in robotic perception and state estimation for autonomous systems. His research focuses on multi-sensor, multi-task self-supervised foundation models for 3D scene perception—spanning detection, segmentation, occupancy prediction, tracking and prediction for autonomous vehicles. He has practical experience building real-time visual-inertial localization systems at the University of Zurich and applied systems and control work in industry and research internships, including PX4 integration for embedded platforms. With an MS from ETH Zurich and a flawless undergraduate record, he blends strong theoretical foundations with hands-on firmware and perception engineering. Open to PhD internships and visiting researcher roles, he brings a track record of turning optimization-based algorithms into real-time robotic systems.
8 years of coding experience
1 year of employment as a software developer
Bachelor's degree, Mechatronics, Robotics, and Automation Engineering, CGPA 4.0/4.0, Bachelor's degree, Mechatronics, Robotics, and Automation Engineering, CGPA 4.0/4.0 at Sabanci University
Doctor of Philosophy - PhD, Artificial Intelligence, Doctor of Philosophy - PhD, Artificial Intelligence at University of Toronto
Master of Science - MS, Mechatronics, Robotics, and Automation Engineering, Master of Science - MS, Mechatronics, Robotics, and Automation Engineering at ETH Zurich
Hong Kong University of Science and Technology (HKUST)
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