Hadi Saboohi

Islamic Azad University, Karaj, University of Malaya

Papers

Total Citations

H-Index

About

Hadi Saboohi’s research lies at the intersection of soft robotics, adaptive control, and computational intelligence, with a focus on designing and analyzing compliant, underactuated robotic systems. His most cited work introduces support vector regression as a predictive tool for input displacement in adaptive compliant robotic grippers, demonstrating how machine learning can enhance the precision of flexible grasping mechanisms. In parallel, his study on underactuated robotic fingers employs adaptive neuro-fuzzy methodology to identify the joints most susceptible to strain, offering crucial insights for improving durability and performance in bio-inspired manipulators. Although one of his key papers has been retracted, it still garnered 21 citations, reflecting the initial interest in his predictive modeling approach. His contributions have advanced the understanding of how data-driven techniques can optimize the design and control of compliant robotic hands, a field critical for applications in manufacturing, prosthetics, and human-robot interaction. With a total of 36 citations across his most recognized works, Saboohi’s research provides a foundation for engineers seeking to integrate intelligent algorithms with mechanical compliance, pushing the boundaries of adaptive robotic manipulation.