W. Khaled
Papers
1
Total Citations
5
H-Index
1
About
Dr. W. Khaled is a pioneering researcher at the intersection of assistive robotics, the Internet of Things (IoT), and edge computing. Their most-cited work, "Federated Learning-Driven IoT and Edge Cloud Networks for Smart Wheelchair Systems in Assistive Robotics" (2025, 5 citations), introduces a transformative framework that integrates federated learning with IoT and edge cloud networks to enhance smart wheelchair systems for people with disabilities. This contribution addresses critical challenges in real-time data processing, privacy preservation, and adaptive control in assistive technologies. Dr. Khaled’s research bridges cutting-edge machine learning with practical, human-centered applications, aiming to deliver more responsive and autonomous mobility solutions. By leveraging federated learning, their work ensures that sensitive user data remains decentralized while enabling collaborative model improvement across devices. This approach not only improves wheelchair navigation and safety but also sets a new standard for privacy-aware assistive robotics. Dr. Khaled’s innovative fusion of IoT, edge computing, and federated learning marks a significant step toward more intelligent, accessible, and secure assistive technologies, with the potential to profoundly impact the quality of life for individuals with disabilities.
Research Focus
Key Achievements
Top Papers
- 1