Yongbao Li
Papers
2
Total Citations
12
H-Index
2
About
Yongbao Li is a medical physicist and researcher specializing in the optimization of robotic radiotherapy, with a particular focus on circular cone-based systems such as the CyberKnife. His work addresses a critical challenge in modern radiation oncology: balancing the geometric flexibility of robotic linacs with the computational and temporal demands of treatment planning. Li’s major contributions include the development of a singular value decomposition linear programming (SVDLP) optimization technique, which efficiently handles the large, complex beam spaces inherent to robotic systems, and the application of PyTorch—a deep learning toolkit—to accelerate plan optimization for circular cone delivery. These innovations aim to reduce both optimization and treatment times while maintaining plan quality, making hypo-fractionated radiotherapy more practical. Although his citation counts are modest (8 and 4 for his two most-cited papers), his work represents a pioneering intersection of machine learning and radiation therapy optimization. Li’s research is particularly notable for its translational potential, directly addressing a bottleneck in clinical workflow for advanced robotic radiotherapy systems.
Research Focus
Key Achievements
Top Papers
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- 2