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About

A.M. Al-Fahed Nuseirat’s research lies at the intersection of robotics, neural networks, and control theory, with a central focus on dexterous manipulation and grasping. His major contributions address the fundamental challenge of enabling robot hands to securely hold objects, even under difficult conditions. Notably, he pioneered a two-stage method for constructing a firm grip that can tolerate small fingertip slips, formulating the gripper-object interaction as a linear complementarity problem. This work, along with his neural network approaches to frictionless grasping and intelligent gripper design for polygon-shaped objects, has been highly influential, with his most cited papers each garnering 13–14 citations. In a particularly innovative line of research, Nuseirat applied concepts from power system stability—such as participation factors and modal analysis—to model and control the dynamics of a multifingered robot hand-object system. This cross-disciplinary approach, detailed in his 1999 study, identified the state variables most responsible for instability, offering a novel framework for robust robotic grasping. Through these contributions, Nuseirat has advanced both the theoretical foundations and practical algorithms for intelligent robotic manipulation.