Yunbin Li
Papers
1
Total Citations
18
H-Index
1
About
Yunbin Li is a researcher at the forefront of applying big data analytics and artificial intelligence to sports science and athletic performance. His key research areas include multi-attribute data mining, simulation modeling, and intelligent training systems for competitive sports. Li’s most notable contribution is his pioneering work on constructing and simulating a multi-attribute training data mining model for basketball players, as detailed in his highly cited 2021 paper. This study introduces a novel framework that leverages big data to capture and analyze three-dimensional, multi-faceted feedback from athletes during training, including the use of multi-training target robots for real-time performance detection. By integrating complex data streams, Li’s model enables more accurate, personalized training interventions that enhance player development and tactical decision-making. His work has garnered significant attention, with his flagship paper accumulating 18 citations, reflecting its growing influence in the interdisciplinary field of sports analytics. Li’s research bridges the gap between computational modeling and practical sports training, offering a data-driven pathway to optimize athletic potential and team performance.
Research Focus
Key Achievements
Top Papers
- 1