Professor Feng Jianshe Successfully Secures Three Important Research Project Grants

Recently, Professor Feng Jianshe, head of the AI Cube Laboratory, has achieved important progress in his research work, successfully securing three important research project grants in succession. These projects cover different levels from basic research to industrial applications, fully demonstrating Professor Feng Jianshe’s academic strength and industrial influence in the field of industrial artificial intelligence.

Guangdong Province Natural Science Foundation General Project was successfully approved, with the project name “Online Monitoring and Process Optimization of Ultra-Hard Wide-Bandgap Semiconductor Manufacturing Processes Based on Multimodal Time-Series Pre-trained Large Models,” with an execution period from December 2024 to project completion. This project addresses the key technological needs of ultra-hard wide-bandgap semiconductor manufacturing, a national strategic emerging industry, achieving intelligent monitoring and optimization of manufacturing processes through multimodal time-series pre-trained large model technology.

Shenzhen Natural Science Foundation General Project was also funded simultaneously, with the project title “Research on Online Virtual Metrology and Advanced Process Control Methods for High-Precision Manufacturing of Silicon Carbide Materials,” with an execution period starting from November 2024. Silicon carbide, as a representative of third-generation semiconductor materials, has important application value in fields such as new energy vehicles and 5G communications, and the implementation of this project will provide important technical support for related industrial development.

Xiaomi Group Youth Scholar Research Special Project represents an important achievement in industry-academia-research cooperation, with the project name “Key Technology Research on Quality Large Models Based on Manufacturing Process Data,” with an execution period starting from August 2024. This is the first cooperation project between Xiaomi Group and Sun Yat-sen University, marking an important breakthrough in deep integration between universities and enterprises.

The successful approval of the three projects reflects Professor Feng Jianshe’s outstanding performance in research work at different levels. The Guangdong Province and Shenzhen Natural Science Foundation projects demonstrate his deep accumulation in basic research, while Xiaomi Group’s industrial cooperation project showcases his important contributions in industry-academia-research integration.

The research content of these projects all focuses on cutting-edge technologies and key applications of industrial artificial intelligence, covering multiple important directions such as multimodal time-series large models, online monitoring and control, quality prediction and optimization. The implementation of these projects will provide important driving force for related technological development and industrial applications.

For laboratory students, the acquisition of these high-level research projects is of great significance. Students will have the opportunity to participate in national and provincial/municipal important research projects, encounter cutting-edge technological challenges and research problems, and exercise their research capabilities and innovative thinking in practical projects.

The successful approval of the projects also lays a solid foundation for the long-term development of the laboratory. Sufficient research funding guarantee will help the laboratory purchase advanced equipment, attract excellent talent, and conduct high-level academic exchanges, creating favorable conditions for cultivating high-quality talent and producing important research achievements.

The successive acquisition of three important research projects further enhances the academic status and influence of the AI Cube Laboratory in the field of industrial artificial intelligence, laying an important foundation for the laboratory to undertake more major research tasks and achieve more original results in the future.