Yeong-Bin Kim
Papers
1
Total Citations
4
H-Index
1
About
Yeong-Bin Kim is a leading researcher at the forefront of Edge AI and safety-critical robotics, whose work is redefining how autonomous systems perceive and interact with dynamic environments. His most influential contribution, "Edge AI-driven Multi-camera System for Adaptive Robot Speed Control in Safety-critical Environments" (2025), has already garnered 4 citations, signaling its immediate impact on the field. Kim’s research centers on developing real-time, decentralized artificial intelligence that enables multi-camera systems to collaboratively adjust robot speed in hazardous settings—bridging the gap between computational efficiency and human safety. By embedding AI directly on edge devices, he eliminates latency bottlenecks, allowing robots to respond adaptively to unpredictable obstacles without relying on cloud infrastructure. This breakthrough is particularly vital for manufacturing floors, autonomous warehouses, and collaborative human-robot workspaces where split-second decisions prevent accidents. Kim’s work not only advances the theoretical foundations of edge computing but also provides practical frameworks for deploying safer, more responsive automation. His achievements underscore a commitment to translating complex AI algorithms into tangible protections for human workers, marking him as a pivotal figure in the next generation of intelligent, safety-first robotics.
Research Focus
Key Achievements
Top Papers
- 1