Jae Moon Lee

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About

Jae Moon Lee is a researcher whose work sits at the intersection of artificial intelligence, autonomous systems, and collective behavior modeling. His primary research areas include swarm intelligence, rule-based crowd simulation, and autonomous driving technologies. Lee’s most influential contribution is his 2010 paper on an efficient algorithm for k-nearest neighbors in flocking behavior (21 citations), which advanced the computational modeling of group dynamics in artificial life and multi-agent systems. His 2009 work on rule-based crowd behavior for intelligent games (12 citations) explored how information flows between characters in video games and animated movies, drawing inspiration from animal behavior and prey-predator models. More recently, Lee has ventured into practical autonomous driving systems, demonstrated by his 2022 paper on implementing autonomous driving on an RC car using a Raspberry Pi and AI server (3 citations). This work addresses the fundamental challenge of developing self-driving technology without expensive real vehicles, making autonomous driving research more accessible. Lee’s career reflects a trajectory from theoretical behavior algorithms to applied autonomous systems, bridging the gap between simulated crowd intelligence and real-world robotic autonomy.