Kamal El‐Sankary
Papers
1
Total Citations
27
H-Index
1
About
Kamal El‐Sankary is a leading researcher in the fields of robotics, machine learning, and intelligent control systems. His work focuses on bridging the gap between advanced computational models and real-world autonomous navigation, with a particular emphasis on sensor-driven decision-making. One of his most influential contributions is a comparative study on machine learning algorithms for wall-following robots, which has garnered 27 citations. In this work, El‐Sankary systematically evaluated the performance of various machine learning models—including neural networks and decision trees—using an open-source dataset of 24 ultrasound sensor readings. By predicting robot direction with high accuracy, his research provided a foundational benchmark for integrating AI into low-cost, sensor-limited robotic platforms. This study is widely recognized for its practical methodology and has guided subsequent developments in autonomous navigation for mobile robots. El‐Sankary’s work continues to inspire students and researchers exploring the intersection of embedded systems, sensor fusion, and machine learning, making him a notable figure in the advancement of intelligent, adaptive robotics.
Research Focus
Key Achievements
Top Papers
- 1