Yulei Song

Papers

Total Citations

H-Index

About

Yulei Song is a pioneering researcher in healthcare robotics and nursing automation, with a primary focus on integrating robotic systems into clinical environments to alleviate workforce burdens. Their most influential work, "Nursing Robots Can Reduce Nursing Workload in General Adult Wards: A Two‐Phase Study" (2025), stands as a landmark contribution to the field. In this study, Song systematically evaluated the capabilities of existing nursing robots in general adult wards, identifying specific care tasks these robots can perform—such as patient monitoring, medication delivery, and mobility assistance—and quantifying the potential reduction in nursing workload. The findings demonstrated that robotic implementation could significantly offset routine care demands, offering a data-driven roadmap for hospital adoption. With over 3 citations in a short time, this work has already sparked discussions on workforce sustainability and patient safety. Song’s research bridges engineering and clinical practice, providing actionable insights for healthcare administrators and roboticists alike. Their achievements underscore a commitment to solving real-world staffing crises through technology, positioning them as a key voice in the future of intelligent, human-centered healthcare delivery.