Mohsen Bakouri

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About

Mohsen Bakouri is a researcher at the forefront of assistive robotics, specializing in human-robot interaction and intelligent control systems for mobility aids. His primary research areas include voice-controlled robotic wheelchairs, deep learning architectures, and embedded systems for rehabilitation engineering. Bakouri’s most significant contribution is the development of a smart wheelchair steering system using Convolutional Neural Networks (CNNs) for voice recognition, which empowers individuals with mobility impairments to navigate independently—reducing reliance on caregivers and enhancing quality of life. This work, published in 2022, has garnered 45 citations, reflecting its impact on assistive technology. He further advanced this line of research by integrating Network-in-Network (NIN) and Long Short-Term Memory (LSTM) models to improve voice control accuracy and real-time responsiveness, with an Android-based interface for practical deployment. Bakouri’s innovations bridge the gap between cutting-edge AI and accessible, low-cost solutions for disabled users. His work is notable for its focus on real-world applicability, demonstrating how deep learning can transform simple voice commands into precise wheelchair maneuvers. For students and researchers, Bakouri exemplifies how engineering can directly address societal challenges, offering a compelling model for human-centered robotics research.