Dr. Xin Liu | Deep Learning | Best Researcher Award
Associate Professor at Wenzhou Business College, China📖
Dr. Xin Liu is an Associate Professor and Physical Education Teacher at Wenzhou Business College. With a strong academic background in physical training and deep learning, his research focuses on integrating technology with sports science to optimize athletic performance and injury prevention. His work leverages infrared thermal imaging and deep learning models to analyze heat energy expenditure in athletes. He has authored two books and actively contributes to advancing sports training methodologies through innovative research.
Profile
Education Background🎓
- Ph.D. in Physical Education, Jose Rizal University, 2020–2023
- Master’s in Physical Education, Shanghai Normal University, 2017–2019
- Bachelor’s in Physical Education, Shandong Agricultural University, 2013–2017
Professional Experience🌱
- Physical Education Teacher, Wenzhou Business College (2024–Present)
Engaged in teaching and research on physical training methodologies, integrating AI-driven analytics in sports science. - Researcher in Sports Science & Deep Learning Applications
Focused on using AI models, particularly CNN, to predict and enhance athletic performance.
- Physical Training & Sports Performance Optimization
- Application of Deep Learning in Sports Science
- Infrared Thermal Imaging for Athlete Monitoring
Author Metrics
Dr. Xin Liu has made significant contributions to the field of physical training and sports science through his research on integrating deep learning models with infrared thermal imaging technology. He has authored two books (ISBN: 978-7-5498-5469-1, 978-7-7800-2061-9) that focus on advancements in sports performance and training methodologies. His research includes two completed/ongoing projects, with findings published in reputed platforms such as Elsevier (Link). While his citation index is yet to be established, his pioneering work in applying AI-driven techniques to athlete monitoring is gaining recognition in the academic community.
Simulation of Infrared Thermal Images Based on Deep Learning in Athlete Training: Simulation of Thermal Energy Consumption
- Authors: Xin Liu, Li Zhang, Wei Chen
- Journal: Heliyon
- Volume: 11
- Issue: 1
- Publication Date: January 2025
- Article Number: e00823
- DOI: Link to Article
- Publisher: Elsevier
- Abstract Summary: This study explores the application of deep learning techniques to simulate infrared thermal images for analyzing and predicting athletes’ thermal energy consumption. The research highlights how AI-driven thermal imaging enhances training efficiency, minimizes injury risks, and provides insights into optimizing sports performance.
Conclusion
Dr. Xin Liu is a strong candidate for the Best Researcher Award due to his innovative contributions in integrating deep learning and infrared thermal imaging in sports science. His research holds substantial potential for real-world applications, optimizing athlete performance, and advancing AI-driven monitoring techniques. With continued efforts in increasing citations, industry collaborations, and publishing in high-impact journals, he can further solidify his position as a leading researcher in the field.