Zeynab Ezzati Babi

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About

Zeynab Ezzati Babi is a robotics researcher whose work lies at the intersection of computer vision, autonomous manipulation, and intelligent manufacturing. Her most cited contribution, "Autonomous Robotic Assembly and Sequence Planning Based on YOLOv8," introduces a fully integrated robotic building system capable of observing its workspace, planning assembly sequences, and executing real-time grasps and motions using the YOLOv8 object detection framework. This work, which includes the creation of a custom wooden brick dataset, demonstrates a practical pipeline for enabling robots to reason about and physically construct structures without human intervention. Though early in her career, her research has already garnered attention for its potential to advance automated construction and flexible manufacturing. Ezzati Babi’s work is particularly notable for bridging deep learning-based perception with classical motion planning, offering a scalable approach to autonomous assembly. As the demand for intelligent, adaptive robotic systems grows, her contributions are poised to influence both academic research and industrial applications in robotics and automation.