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About

Salvatore Iengo is a researcher specializing in human-robot interaction (HRI), gesture recognition, and adaptive robotic behavior — fields at the intersection of computer science, engineering, and cognitive science. His most influential contribution, "Continuous Gesture Recognition for Flexible Human-Robot Interaction" (2014), has accumulated 28 citations and presents a pioneering system capable of online training with minimal samples while gracefully handling natural variation in user behavior, making it a significant step toward intuitive human-robot communication. Complementing this work, his 2012 paper on attentional and emotional regulation in HRI — cited 17 times — explores how robots can dynamically adapt their behavior by leveraging emotional and attentional cues, with arousal and predictability playing central roles in shaping robotic responsiveness. Iengo has also investigated biologically-inspired control strategies for autonomous multi-robot navigation systems, reflecting a broader interest in adaptive, nature-driven approaches to robotics. His research collectively advances the vision of robots that are not only technically capable but genuinely responsive to human cognitive and emotional states — a crucial frontier as robots increasingly enter everyday social environments.