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About

Jianmin Ji is a prolific robotics and artificial intelligence researcher whose work spans human-robot interaction, autonomous navigation, and cognitive systems. His research career reflects a sustained commitment to making robots more capable, intelligent, and socially aware in real-world environments. Ji's early contributions focused on equipping service robots with high-level cognitive capabilities, integrating Natural Language Processing with commonsense reasoning through Answer Set Programming (ASP) to enable meaningful human-robot communication — work that garnered 90 and 17 citations respectively and laid important theoretical groundwork for the field. He later advanced open knowledge utilization for robots, enabling autonomous extraction and application of web-scale knowledge resources (45 citations). A significant portion of Ji's more recent research addresses autonomous robot navigation, particularly in dynamic, human-populated environments. His map-based deep reinforcement learning approaches for single and multi-robot collision avoidance have attracted strong attention, accumulating citations ranging from 20 to 42, demonstrating both academic interest and practical relevance. His contributions to LiDAR-based SLAM and visual place recognition further demonstrate breadth across perception and localization challenges. Ji's body of work, totaling hundreds of citations across a decade of research, reflects enduring influence in intelligent robotics — bridging language understanding, reasoning, and autonomous physical operation in complex environments.