Hamza Amrani

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About

Hamza Amrani is a rising researcher at the intersection of human-robot interaction and neural engineering, focusing on making robotic control more intuitive and accessible. His work centers on two complementary approaches: wearable sensor-based teleoperation and brain-computer interfaces (BCIs). In his 2024 paper on "Responsive Teleoperation of a Robotic Arm via Wearable Inertial Sensors," Amrani developed a system that translates natural human arm movements into real-time robotic commands, enabling seamless remote control for applications in industry, medicine, and home automation. His second major contribution, "EEG Acquisition and Motor Imagery Classification for Robotic Control," validates the use of minimally invasive EEG headsets to classify motor imagery—allowing users to command robots through thought alone. Though early in his career, with his most-cited works accumulating 2 and 1 citations respectively, Amrani’s dual-pronged approach demonstrates significant potential: he is advancing both physical and cognitive interfaces for human-in-the-loop robotics. His work promises to democratize robotic assistance, particularly for individuals with limited mobility, and positions him as a promising voice in the next generation of assistive and teleoperated robotic systems.