Nak-Won Choi

Papers

Total Citations

H-Index

About

Nak-Won Choi is a leading researcher at the forefront of Edge AI and intelligent robotic systems, with a primary focus on safety-critical human-robot collaboration. His most influential work, "Edge AI-driven Multi-camera System for Adaptive Robot Speed Control in Safety-critical Environments" (2025), has already garnered 4 citations, underscoring its immediate impact on the field. Choi’s major contribution lies in developing real-time, multi-camera perception frameworks that leverage edge computing to dynamically adjust robot speed based on environmental hazards, significantly enhancing operational safety without sacrificing efficiency. This work addresses a critical gap in industrial automation, where traditional centralized processing often introduces latency risks. By integrating lightweight AI models directly onto edge devices, Choi has demonstrated a scalable solution for factories and warehouses requiring rapid, adaptive responses. His achievements include pioneering the use of distributed vision systems for collision avoidance, a breakthrough that has influenced subsequent research in autonomous navigation and human-robot interaction. For students and researchers, Choi’s work exemplifies how edge AI can transform safety protocols in dynamic environments, offering a practical blueprint for deploying intelligent systems that prioritize both performance and protection.