Mohammed Alsehaimi

About

Mohammed Alsehaimi’s research lies at the intersection of assistive robotics and intelligent control systems, with a primary focus on enhancing mobility and independence for individuals with disabilities. His most cited work, “Steering a Robotic Wheelchair Based on Voice Recognition System Using Convolutional Neural Networks” (2022, 45 citations), introduces a low-cost, CNN-driven voice control system that enables users to navigate a wheelchair autonomously through spoken commands. This contribution directly addresses a critical barrier to independence for many wheelchair users, offering a practical, affordable solution that reduces reliance on caregivers. By integrating deep learning with real-time robotic control, Alsehaimi’s work demonstrates how accessible AI can transform assistive technology. His research is notable for its emphasis on real-world deployability, bridging the gap between advanced neural network architectures and everyday assistive devices. With growing citation impact, Alsehaimi is establishing himself as a key voice in the development of smart, human-centered robotic systems that prioritize user autonomy and quality of life.

Research Focus

Key Achievements

Top Papers

1. 1
   Steering a Robotic Wheelchair Based on Voice Recognition System Using Convolutional Neural Networks

   45 citations · 2022

Key Collaborators

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