Youssef Bakouny

Papers

Total Citations

H-Index

About

Youssef Bakouny is a researcher at the intersection of robotics, artificial intelligence, and autonomous systems, with a primary focus on advancing path planning and human-robot interaction. His most cited work introduces an end-to-end sketch-guided path planning framework for autonomous mobile robots, leveraging imitation learning to translate human-drawn sketches directly into executable robot trajectories. This innovation circumvents the need for complex reward engineering or expensive additional hardware, making intuitive robot control more accessible and flexible. While his research is still in its early stages, Bakouny’s contributions address a critical gap in making autonomous navigation responsive to human preferences without sacrificing efficiency. His work has already garnered attention for its practical implications in real-world robotics applications, from warehouse logistics to assistive technologies. By enabling robots to learn from simple human demonstrations rather than predefined reward functions, Bakouny is helping to democratize robot programming and pave the way for more natural, user-friendly autonomous systems. His approach represents a promising step toward bridging the gap between human intent and machine execution in dynamic environments.