Name：Li Fang
Professional Title / Position：Associate Professor, School of Computer Science and Engineering, South China University of Technology
Research Direction：Intelligent Manufacturing, Intelligent Robots, Industrial Big Data
Team：Intelligent Technology and Robot Team
Tel：Not Specified
Email：cslifang@scut.edu.cn
Biography：Li Fang is an associate professor at the School of Computer Science and Engineering, South China University of Technology. She obtained her Bachelor's degree and Master's degree from Central South University in 2003 and 2006 respectively, and received her Doctor's degree from South China University of Technology in 2010. From 2010 to 2018, she worked as a lecturer at the same university, and has been an associate professor since 2018. She was a visiting scholar at Loughborough University in the United Kingdom from January 2022 to January 2023. Her research focuses on intelligent manufacturing, intelligent robots and industrial big data. She has presided over and participated in a number of national and provincial-level scientific research projects, obtained more than ten authorized invention patents, and published more than 30 high-level academic papers. She welcomes postgraduates who are interested in her research fields and have a positive learning attitude to apply.
Education：
• 2010 // South China University of Technology / Doctor's Degree
• 2006 // Central South University / Master's Degree
• 2003 // Central South University / Bachelor's Degree
Work Experience：
• 2018 - Present // School of Computer Science and Engineering, South China University of Technology / Associate Professor
• 2010 - 2018 // School of Computer Science and Engineering, South China University of Technology / Lecturer
• 2022.01 - 2023.01 // Loughborough University, United Kingdom / Visiting Scholar
Course：
• Advanced Language Programming C++
• Intelligent Robot Technology
Projects：
• National Key Research and Development Program Sub-project: Verification of Cyber-Physical Systems for Intelligent Production Lines, National Level, Role: Principal Investigator
• National Natural Science Foundation Youth Fund Project: Research on Formal Integrated Modeling Method of Service-Oriented Cyber-Physical Systems, National Level, Role: Principal Investigator
• Guangdong Provincial Natural Science Foundation Project: Research on Integrated Modeling Method of Cyber-Physical Production Systems Based on Data and Knowledge Fusion, Provincial Level, Role: Principal Investigator
• Guangdong Provincial Natural Science Foundation Project: Research on Integrated Modeling and Decision-Making Methods of Intelligent Production Lines Based on Cloud-Edge-End Collaboration, Provincial Level, Role: Principal Investigator
• Guangdong Provincial Science and Technology Plan Project: Research on Key Technologies of UAV System Equipment Collaborative Self-Organizing Operation, Provincial Level, Role: Principal Investigator
• National 863 Plan Project, National Level, Role: Principal Investigator (Completed)
Publications：
• Weisen Guo, Fang Li, Ping Zhang, Long Luo. A stage-related online incremental transfer learning-based remaining useful life prediction method of bearings. Applied Soft Computing. 2025,1(169). (SCI)
• Yu Pu, Fang Li*, Shanhin Rahimifard. Multi-agent reinforcement learning for job shop scheduling in dynamic environment. Sustainability. 2024,16(8), 3234. (SCI)
• Fang Li, Weisen Guo, Ping Zhang, Long Luo. A Bearing Remaining Useful Life Prediction Method Based on Spatiotemporal Dual-Cell States. Journal of South China University of Technology. 2023,9(51). (EI)
• Hongkai Qiu, Fang Li*, Zifeng Lu, and Zhiyao Zhuang. Research on Resource Matching Method in Reconfigurable Intelligent Manufacturing System, 2023 IEEE ICCSSE. China. (EI)
• Xiao Bin, Fang Li*. Knowledge-based formal modeling for CPPS in personalized intelligent manufacturing, 2021 IEEE CyberSciTech. 2021.10. (EI)
• Zhuang Zhiyao, Fang Li*, Zhang Ping, Research on Multi-Agent based Optimization in Smart Production Line, IEEE ICCC2020, 2020.11. (EI)
• Haoxuan Yuan, Fang Li*, A Formal Modeling and Verification Framework for Service Oriented Intelligent Production Line Design, 18th IEEE/ACIS International Conference on Computer and Information Science（ICIS 2019）, 2019.07. (EI)
• Caibing Liu, Fang Li*, Guohao Chen, Xin Huang. A TTEthernet Transmission in Software-defined Distributed Robot Intelligent Control System. Wireless Communications and Mobile Computing. 2018, 7(50). (SCI)
• Yongda Deng, Fang Li*, Xin Huang. Research on Multimodal Human-robot Interaction Based on Speech and Gesture. Computers and Electrical Engineering. 2018(72). (SCI)
• Guanglong Du, Shuaiying Long, Fang Li*. Active Collision Avoidance for Human-Robot Interaction with UKF, Expert System and Artificial Potential Field Method. Frontiers in Robotics and AI-Robotic Control Systems. 2018.11. (SCI)
• Song Li, Di Li, Fang Li*, Nan Zhou. CPSiCGF: A code generation framework for CPS integration modeling. Microprocessors and Microsystems, 2015, 39: 1234-1244 (SCI)
• Di Li, Fang Li*, Xin Huang. A Model Based Integration Framework for Computer Numerical Control system Development. Robotics and Computer-Integrated Manufacturing. 2010, 26(4):333-343. (SCI)
Awards：
• 2020: Second Prize of Guangdong Provincial Science and Technology Progress Award, Research and Application of Key Technologies and Systems in the Manufacturing Process of Typical Home Appliance Products, Granted by Guangdong Provincial Government
• 2018: Third Prize of Guangdong Provincial Science and Technology Progress Award, Research and Industrialization of Key Technologies for Flexible Processing Production Lines of Custom Furniture Panels, Granted by Guangdong Provincial Government
• 2018: Second Prize in the Undergraduate Classroom Teaching Competition for Young Teachers (2018-2019 Academic Year), Granted by South China University of Technology
• 2017: First Prize of Military Science and Technology Progress Award, *** Robot Teleoperation Technology and Experiments, Granted by the Military
• 2019: Teaching Newcomer Award in the Teacher Teaching Honor System, Granted by South China University of Technology
• 2018: First Prize of Excellent Instructor for Student Science and Technology Innovation, Granted by South China University of Technology
• 2009: First Prize of Guangdong Provincial Science and Technology Progress Award, Common Control and Detection Technologies and Applications for Advanced Equipment, Granted by Guangdong Provincial Government
