Youssef Bouh

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About

Youssef Bouh is a researcher at the forefront of embedded machine learning, with a focused interest in TinyML and its application for assistive technologies. His most cited work, "TinyML on Arduino Nano 33 BLE for Disabled Person" (2024), demonstrates a pioneering approach to deploying lightweight neural networks on resource-constrained microcontrollers. By leveraging the Arduino Nano 33 BLE’s low-power capabilities, Bouh’s research enables real-time, on-device inference for tasks like gesture recognition or environmental sensing—critical for empowering individuals with disabilities through affordable, portable solutions. Though early in its citation trajectory (2 citations), this work signals a growing impact in the intersection of edge AI and inclusive design. Bouh’s contributions address the pressing need for energy-efficient, privacy-preserving models that operate without cloud connectivity, making AI accessible in low-resource settings. His research not only advances TinyML methodologies but also underscores the potential of microcontrollers to drive social good, positioning him as an emerging voice in the democratization of intelligent systems for underserved communities.