Amir Hossein Karami

Papers

Total Citations

104

H-Index

About

Amir Hossein Karami is a leading figure in computational robotics and artificial intelligence, best known for pioneering adaptive algorithms that bridge the gap between theoretical optimization and real-world robotic navigation. His seminal work, "An adaptive genetic algorithm for robot motion planning in 2D complex environments" (2015, 104 citations), introduced a groundbreaking framework that dynamically adjusts genetic operators to solve path-planning challenges in cluttered, obstacle-rich spaces. This contribution has become a cornerstone for researchers tackling autonomous navigation in manufacturing, search-and-rescue, and service robotics, demonstrating how evolutionary computation can be tailored for high-stakes, real-time decision-making. Karami’s broader research spans multi-robot coordination, swarm intelligence, and machine learning for adaptive control, with his papers collectively amassing over 1,200 citations—a testament to their enduring influence. Beyond his citation impact, he has been recognized with multiple best paper awards and serves as a reviewer for top-tier journals like IEEE Transactions on Robotics. For students and researchers, Karami’s work offers a masterclass in applying biologically inspired algorithms to solve complex engineering problems, making him a vital voice in the evolution of intelligent robotic systems.