Imene Tarakli

Papers

Total Citations

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About

Imene Tarakli is a rising researcher at the forefront of human-robot interaction, with a focused expertise in social robotics, personalisation, and interactive machine learning. Her work addresses a critical challenge in modern robotics: enabling robots to adapt dynamically to unpredictable human behaviours and diverse social contexts. Tarakli’s major contributions include pioneering frameworks for social robot personalisation, where she explores how robots can tailor their actions to individual users, and a comparative study on teachable robots that examines how teaching strategies and task complexity shape user perception—a study grounded in data from 138 participants. Her most recent work introduces ECLAIR, an innovative framework that leverages Large Language Models to integrate natural language feedback into robotic learning, bridging the gap between human instruction and machine adaptation. With a growing citation record—including 4 citations for her 2023 paper on social robots—Tarakli’s research is gaining traction for its practical implications in education, healthcare, and assistive technology. Her achievements highlight a promising trajectory in making robots more intuitive, responsive, and user-friendly, positioning her as a key voice in the next generation of human-centred robotics.