Chunrong Fang

Nanjing University

Papers

2

Total Citations

14

H-Index

2

About

Chunrong Fang is a leading researcher at the intersection of software engineering, robotics, and artificial intelligence, with a focus on automated testing and intelligent system design. His most impactful work introduces a **practical, non-intrusive GUI exploration testing method using visual-based robotic arms** (2024, 9 citations), which overcomes the limitations of platform-specific, intrusive testing frameworks by enabling versatile, physical interaction with diverse embedded systems. This contribution is pivotal for advancing software quality assurance in complex, real-world environments. Additionally, Fang pioneers the use of **self-refined large language models as automated reward function designers for deep reinforcement learning in robotics** (2023, 5 citations), addressing the critical challenge of manual reward engineering. By leveraging LLMs to iteratively generate and refine reward functions, his work significantly reduces human effort and enhances the performance of robotic learning systems. These innovations demonstrate Fang’s unique ability to bridge theoretical AI advances with practical engineering solutions, making him a notable figure in both software testing and autonomous robotics.

Research Focus

Key Achievements

2
H-Index
2
Papers
14
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Practical Non-Intrusive GUI Exploration Testing with Visual-based Robotic Arms
9 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Nanjing University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago