Glareh Mir

Universität Hamburg, Hamburg University of Technology

Papers

Total Citations

H-Index

About

Glareh Mir is a researcher at the intersection of human-robot interaction and cognitive robotics, whose work explores how humans build trust with autonomous systems and how robots can learn from their environments. Her most cited research introduces an immersive investment game as a novel paradigm for measuring human-robot trust, addressing the challenge that trust is influenced by multiple social and environmental factors. With over 30 combined citations across her key papers, Mir’s work provides a more nuanced, scenario-based approach to understanding trust dynamics—an essential foundation as robots become more capable collaborators. Beyond trust, she has contributed to neurorobotics by developing a humanoid robot that learns audiovisual classification through active exploration, enabling it to identify materials by dropping objects and analyzing the resulting sounds and images. This work bridges embodied cognition and machine learning, showcasing how robots can learn from physical interaction. Mir’s research is notable for its methodological creativity, combining game theory, immersive environments, and robotic experimentation to advance both the science of human-robot trust and the development of more perceptive, autonomous robots.