Eunjin Kim
Papers
7
Total Citations
125
H-Index
5
About
Eunjin Kim is a leading researcher in autonomous robotics, with a focus on knowledge representation, deep learning, and human-robot interaction. Her work bridges the gap between semantic understanding and real-world robotic deployment, particularly in domestic, hospital, and industrial settings. Her most cited paper, "Ontology-Based Knowledge Representation in Robotic Systems" (2021, 54 citations), provides a comprehensive survey that has become a foundational reference for integrating semantic knowledge into autonomous task assistance. Kim has also made significant contributions to edge AI, as demonstrated by her work on "Edge Deployment Framework of GuardBot" (2022, 24 citations), which optimizes deep learning models for real-time face mask recognition on resource-constrained devices. Her research on automatic elevator button localization (2020, 21 citations) addresses a critical challenge in multi-story navigation for service robots, enabling seamless floor-to-floor movement without specialized hardware. Additionally, Kim has advanced 3D recognition for robotic systems (2021, 12 citations) and human-following robots (2023, 6 citations), with her work on dynamic visual servoing (2018) showcasing her expertise in precise robot manipulator control. With over 125 total citations, Kim’s research is shaping the next generation of intelligent, context-aware robots.
Research Focus
Key Achievements
Top Papers
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- 43D Recognition Based on Sensor Modalities for Robotic Systems: A Survey12 citations · 2021
- 5Edge Deployment of Vision-Based Model for Human Following Robot6 citations · 2023
- 6
- 7A dynamic visual servoing of robot manipulator with eye-in-hand camera3 citations · 2018