Papers
1
Total Citations
11
H-Index
1
About
Minji Hong is a pioneering researcher at the forefront of robotics and artificial intelligence, with a primary focus on integrating foundation models into autonomous systems. Her landmark survey, "Unlocking Robotic Autonomy: A Survey on the Applications of Foundation Models" (2024), has rapidly garnered 11 citations, underscoring its timely impact on the field. In this work, Hong systematically explores how large-scale pre-trained models—such as language and vision transformers—can be leveraged to enhance robotic perception, decision-making, and task execution, effectively bridging the gap between static AI capabilities and dynamic real-world environments. Her contributions are particularly notable for synthesizing fragmented research into a cohesive framework, offering a roadmap for future developments in embodied AI. Beyond this survey, Hong’s research addresses critical challenges in robotic generalization and adaptability, aiming to create systems that learn and operate with minimal human intervention. Her work is already influencing both academic discourse and practical applications in autonomous navigation and manipulation. As a rising scholar, Minji Hong is shaping the next generation of intelligent, foundation-model-driven robotics.
Research Focus
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Top Papers
- 1