Xufeng Ling

Papers

Total Citations

H-Index

About

Xufeng Ling is a leading researcher at the intersection of intelligent automation and machine learning, with a primary focus on revolutionizing document processing through Robotic Process Automation (RPA). In his highly influential 2020 work, "Intelligent document processing based on RPA and machine learning" (33 citations), Ling introduced a groundbreaking framework that seamlessly integrates human input into automated learning pipelines. His major contribution lies in demonstrating how this hybrid approach can boost processing efficiency by over 200% while maintaining error rates below 0.5%, a critical advancement for industries handling high-volume business documents. By applying machine learning to optimize RPA workflows, Ling has addressed a key bottleneck in enterprise automation: balancing speed with accuracy. His research has profound implications for sectors like finance, legal, and logistics, where reliable document processing is essential. Ling’s work stands out for its practical, scalable solutions, bridging the gap between theoretical AI and real-world business needs. With his innovative methodology and measurable results, he continues to shape the future of intelligent automation, making him a pivotal figure for students and researchers exploring the next generation of document processing technologies.