Deemah Alarabiat
Papers
1
Total Citations
55
H-Index
1
About
Deemah Alarabiat is a researcher whose work lies at the intersection of artificial intelligence, robotics, and bio-inspired computing. Her most cited paper, "Implementation of bio-inspired hybrid algorithm with mutation operator for robotic path planning" (2022, 55 citations), exemplifies her core contribution: developing efficient, nature-inspired algorithms to solve complex robotic navigation challenges. By integrating a mutation operator into a hybrid algorithm, she has advanced the field of autonomous path planning, enabling robots to navigate dynamic environments more effectively. This work has been recognized for its practical implications in robotics and optimization, with citations reflecting its growing influence among peers. Alarabiat's research demonstrates a commitment to bridging theoretical algorithm design with real-world applications, particularly in enhancing the adaptability and efficiency of autonomous systems. Her achievements highlight her as a promising voice in computational intelligence, with potential for further impact in swarm robotics and adaptive control systems.
Research Focus
Key Achievements
Top Papers
- 1