Insaf Ajili

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About

Insaf Ajili is a researcher whose work sits at the intersection of robotics, human–robot interaction, and gesture-based control systems. Her most-cited paper, "Gesture recognition for humanoid robot teleoperation" (2017), has garnered 23 citations and addresses a core challenge in making robot teleoperation more intuitive and accessible. In this work, Ajili explores how natural human gestures can be reliably interpreted by humanoid robots, reducing the cognitive load on operators and enabling more fluid, real-time control. This contribution is particularly significant for applications in hazardous environments, assistive robotics, and remote exploration, where traditional joystick or keyboard interfaces fall short. Ajili’s research helps bridge the gap between human intent and robotic action, advancing the field of non-verbal human–robot communication. Her work has been presented to an international audience, reflecting its relevance to a global community of roboticists and human–computer interaction specialists. By focusing on gesture recognition, Ajili contributes to the broader goal of creating robots that can understand and respond to humans as naturally as another person would.