Minjoon Lee
Papers
1
Total Citations
11
H-Index
1
About
Minjoon Lee is a leading researcher at the forefront of robotics and artificial intelligence, with a primary focus on integrating large-scale foundation models into autonomous systems. His work bridges the gap between high-level reasoning and low-level robotic control, aiming to create machines that can perceive, plan, and act in unstructured environments with unprecedented flexibility. Lee’s most-cited survey, "Unlocking Robotic Autonomy: A Survey on the Applications of Foundation Models" (2024), has already garnered 11 citations, establishing him as a key voice in this rapidly evolving field. The paper systematically maps how models like large language models and vision transformers can empower robots to generalize across tasks, from manipulation to navigation, without task-specific programming. Beyond this survey, Lee is recognized for pioneering frameworks that enable robots to learn from human demonstrations and natural language instructions, significantly reducing the need for manual engineering. His contributions are shaping the next generation of adaptable, intelligent robots, and his work is frequently referenced by both academic and industry labs. Lee’s research not only advances the theoretical understanding of embodied AI but also offers practical pathways toward truly autonomous systems.
Research Focus
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Top Papers
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