Prof. Ye Qi’s Team at the School of Mathematical Sciences Continues to Make Breakthroughs and Produce Frequent Achievements in Intelligent Education and Interdisciplinary Research

Time: 2026-09-15 22:00:00

In July 2026, the course "Optimization Methods," co-developed by Tan Lulin, Chen Yannan, and Yang Tan from Professor Ye Qi’s team, won the third prize in the Associate Professor category for Basic Courses at the 6th National University Teacher Teaching Innovation Competition. The team integrated cutting-edge topics such as machine learning optimization into the classic curriculum and published "Optimization Methods and Machine Learning," restructuring the knowledge system along the "Problem—Theory—Algorithm—Application" axis to lay the disciplinary foundation for intelligent education research and development.

With the advancement of the National Education Digitalization Strategic Action, the team has introduced modeling, optimization algorithms, and artificial intelligence technologies into education, building an intelligent education system that covers the entire chain of "teaching, learning, and assessment."Centered on the granted invention patent "Presentation Analysis Model, Classroom Discourse Analysis Model, and Their Applications," the team developed an intelligent analysis system to achieve multi-dimensional analysis of classroom teaching; and developed a specialized mathematical question-answering system that integrates knowledge bases, knowledge graphs, and large language models, significantly improving accuracy and providing students with clear problem-solving approaches. A particularly key breakthrough lies in learning diagnosis: the team creatively introduced the interactive theorem-proving tool Lean language to verify students’ problem-solving reasoning step by step, not only judging the correctness of conclusions but also precisely identifying issues such as theorem conditions, implicit premises, and logical jumps, generating personalized "learning prescriptions" for each student and achieving truly individualized precise diagnosis. The results have been presented and exchanged at international academic conferences.

Building upon intelligent education, the team has guided students to extend optimization algorithms and mathematical modeling to broader application scenarios and interdisciplinary fields: In medicine, the team, in collaboration with Director Fang Chihua from Zhujiang Hospital of Southern Medical University, secured approval for the National Natural Science Foundation "Key Special Project on Mathematics and Healthcare Cross-Disciplinary Research," focusing on mathematical methods and evolutionary modeling for pancreatic cancer surgical planning and postoperative evaluation. In psychology, the team collaborated with Associate Professor Han Biao from the School of Psychology to study consciousness neural mechanisms based on brain-computer interfaces, jointly securing approval for the National Key R&D Program, developing a brain-computer interface system for consciousness detection based on SEEG, which accurately detects consciousness states through intracranial electrical signals.

Through the intelligent education platform, the team provides students with solid algorithm training and precise diagnosis while transforming research projects into student practice projects, enabling students to deeply participate in cutting-edge topics such as medical modeling and brain-computer interfaces, honing their algorithmic capabilities in real-world scenarios, and achieving a leap in ability from theory to application. Intelligent education not only empowers teaching but also serves as a bridge connecting industries such as medicine and psychology,establishing a closed-loop collaborative education system that deeply integrates research, teaching, and industry.