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About

Ilche Georgievski is a robotics researcher whose work sits at the intersection of autonomous planning, human-robot interaction, and artificial intelligence. His research focuses primarily on long-term task planning for mobile robots, with a particular emphasis on enabling robots to operate intelligently in dynamic, human-populated environments. Among his most significant contributions is the development of human-flow-aware planning systems that leverage hierarchical reinforcement learning, allowing robots to anticipate and adapt to human movement patterns in crowded spaces — a challenge largely overlooked by prior approaches. This work has attracted 16 citations since its 2023 publication. More recently, Georgievski has pioneered the integration of Large Language Models into robot task and motion planning through his DELTA framework, which decomposes complex, long-horizon tasks efficiently using LLM-derived commonsense knowledge, accumulating 15 citations across its 2024–2025 iterations. His broader portfolio extends into telepresence robotics, including automated systems for human detection and following, as well as privacy-aware robotic assistance within smart IoT environments. Together, these contributions reflect a researcher consistently pushing the boundaries of context-aware, socially intelligent autonomy — making his work increasingly relevant as robots transition from controlled labs into everyday human spaces.