Mohamed E. Ghoneim
Papers
2
Total Citations
4
H-Index
2
About
Mohamed E. Ghoneim is a leading researcher in robotics and artificial intelligence, specializing in multi-robot systems, bio-inspired optimization, and deep reinforcement learning. His work focuses on enabling autonomous robots to navigate and coordinate in complex, dynamic environments, with a particular emphasis on real-time evasion and pursuit-evasion strategies. Ghoneim’s major contributions include the development of hybrid bio-inspired neural networks that optimize multi-robot evasion behaviors, as well as the integration of differential game theory with deep reinforcement learning for mobile robot control. His 2024 paper on hybrid bio-inspired optimized neural networks and his 2025 study on pursuit-evasion differential game strategies have each garnered 2 citations, reflecting their early impact in advancing autonomous navigation. Notably, Ghoneim’s research bridges theoretical control frameworks with practical robotic applications, offering scalable solutions for real-world challenges such as surveillance, search-and-rescue, and autonomous defense systems. His work stands out for its innovative fusion of biological inspiration and cutting-edge AI, positioning him as a rising figure in the field of intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2