Omar Alfandi
Papers
4
Total Citations
83
H-Index
4
About
Dr. Omar Alfandi is a leading researcher at the intersection of artificial intelligence, robotics, and next-generation communication networks. His work primarily focuses on reinforcement learning for autonomous systems, remote robotic surgery enabled by 5G, and lightweight deep learning for human-computer interaction. Dr. Alfandi’s most cited paper (30 citations) introduces a Twin Delayed Deep Deterministic Policy Gradient-based framework for UAV target tracking, incorporating achievement rewarding and multistage training to handle complex nonlinear dynamics. He has also made significant contributions to telemedicine, developing a framework to predict haptic feedback during needle insertion in 5G remote robotic surgery (22 citations), and proposing a fog-based architecture for remote phobia treatment using the Tactile Internet (13 citations). Additionally, his work on facial expression recognition using lightweight deep learning (18 citations) advances efficient human-robot interaction and intelligent surveillance. Dr. Alfandi’s research consistently bridges theoretical advances with practical, real-world applications, demonstrating high impact across multiple domains.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Facial expression recognition using lightweight deep learning modeling18 citations · 2023
- 4A Fog-Based Architecture for Remote Phobia Treatment13 citations · 2019