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About

Amar Halilovic is an emerging researcher specializing in explainable artificial intelligence (XAI) applied to human-robot interaction (HRI), with a particular focus on making autonomous robot navigation transparent and understandable to everyday users. His work addresses a critical challenge in modern robotics: as robots become increasingly present in public and domestic spaces, people need intuitive explanations of robotic decision-making to build appropriate trust and comprehension. Halilovic's most influential contribution, "Visuo-Textual Explanations of a Robot's Navigational Choices" (2023, 10 citations), pioneered the integration of visual and textual modalities to clarify why robots choose specific paths. His follow-up work applying LIME — a well-established machine learning interpretability technique — to local path planning (7 citations) demonstrated strong methodological creativity. Beyond technical explanations, he has explored how a robot's personality shapes user reception of real-time explanations, and introduced the novel concept of "Explanation Identity," positioning robots as social agents with consistent communicative personas. Together, his publications accumulate over 25 citations and point toward a holistic framework for explainable robot navigation — a research vision that bridges computer science, cognitive science, and HRI, making him a promising voice in the rapidly growing field of trustworthy autonomous systems.