Junfei Xie

Papers

Total Citations

H-Index

About

Dr. Junfei Xie is a pioneering researcher whose work lies at the intersection of robotics, distributed systems, and artificial intelligence. Her primary research areas include coverage path planning (CPP) for multi-region environments and the development of robust distributed learning frameworks for multi-agent systems. Dr. Xie’s most-cited paper (2020, 4 citations) introduces a novel approach to multi-regional CPP that accounts for energy constraints in robots, addressing a critical gap in applications like lawn mowing, room cleaning, and search-and-rescue missions. This work provides a practical solution for ensuring complete area coverage while managing limited battery life. Her second highly-cited paper (2021, 3 citations) tackles the challenge of straggler effects in synchronous distributed multi-agent reinforcement learning (MARL), proposing a coding-based method to mitigate system disturbances such as node slowdowns or failures. This contribution enhances the reliability and efficiency of large-scale distributed learning systems. Dr. Xie’s research demonstrates a clear commitment to solving real-world problems in autonomous systems, and her work is increasingly recognized for its potential to improve the performance and scalability of robotic and multi-agent networks.