Papers
38
Total Citations
8,842
H-Index
22
About
Amjad J. Humaidi is a prolific researcher whose work spans deep learning, autonomous robotics, intelligent control systems, and swarm optimization — areas in which he has made substantial and wide-ranging contributions. He is perhaps best known for his co-authorship of a landmark 2021 survey on deep learning concepts, CNN architectures, and applications, which has amassed an extraordinary 7,484 citations, establishing it as one of the most influential review articles in the machine learning community. Beyond this seminal work, Humaidi has made significant strides in autonomous mobile robot navigation, developing novel path planning algorithms using hybrid optimization techniques such as PSO, ant colony optimization, and bat algorithm variants, with key papers collectively earning hundreds of citations. His expertise extends to advanced control system design, where he has pioneered fractional PID controllers, synergetic control frameworks, super-twisting sliding mode controllers, and active disturbance rejection strategies applied to robot manipulators and pneumatic muscle actuators. His work on interval type-2 fuzzy logic control for parallel robots further demonstrates his breadth across intelligent systems. Through a consistently applied philosophy of hybridizing bio-inspired optimization with sophisticated control theory, Humaidi has emerged as a highly impactful figure bridging artificial intelligence and robotics engineering.
Research Focus
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