Huda Ubaya

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About

Huda Ubaya specializes in mobile robotics, embedded systems, and computer vision, with a particular focus on developing intelligent navigation and control systems for autonomous robots. Their major contributions lie in integrating neural network architectures with real-time robotic applications, notably through the implementation of RAM-based neural networks for maze mapping algorithms in wall-follower robots. This work, cited 8 times, established foundational methods for safe robot navigation by enabling environmental recognition through wall position detection. Ubaya further advanced human-robot interaction by pioneering dynamic facial pattern recognition for robot movement control, a technique that overcomes the resource constraints of embedded platforms. Their 2021 paper on this topic has garnered 7 citations. Expanding on this, Ubaya developed a novel facial landmarks detection method using auto-extracted nose-corner features to create geometric invariants for face-following mobile robots, published in 2022 with 5 citations. These contributions collectively demonstrate Ubaya’s impact in making robots more responsive to human presence while operating within the computational limitations of embedded systems, advancing both autonomous navigation and socially interactive robotics.