Suhong Kim

Konkuk University

Papers

2

Total Citations

11

H-Index

1

About

Suhong Kim is at the forefront of autonomous systems and software-defined vehicles, pioneering the integration of edge computing and real-time robotic platforms. Their most cited work, "Enhancing Autonomous Driving Robot Systems with Edge Computing and LDM Platforms" (2024, 10 citations), addresses the critical challenge of processing vast sensor data for autonomous robots in security, environmental monitoring, and disaster response. By leveraging edge computing and LDM (Layered Data Management) platforms, Kim enables efficient data sharing and real-time decision-making among robot swarms—a breakthrough for field-deployed autonomous systems. In their more recent work, "A Dynamic Bridge Architecture for Efficient Interoperability Between AUTOSAR Adaptive and ROS2" (2025, 1 citation), Kim tackles the automotive industry’s shift toward Software-Defined Vehicles (SDVs). They propose a dynamic bridge architecture that overcomes the limitations of static approaches, seamlessly integrating AUTOSAR Adaptive (vehicle control standard) with ROS2 (autonomous driving research platform). This innovation promises to accelerate SDV development by enabling flexible, real-time communication between safety-critical and research-oriented systems. Kim’s contributions are shaping the future of autonomous mobility, from disaster-response robots to next-generation vehicles.

Research Focus

Key Achievements

1
H-Index
2
Papers
11
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Enhancing Autonomous Driving Robot Systems with Edge Computing and LDM Platforms
10 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Konkuk University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago