Central South University formally established a standalone School of Artificial Intelligence during a national academic forum in Changsha, appointing university president and Chinese Academy of Engineering Academician Li Jiancheng as its founding dean.
The institution holds "Project 985" status, an elite designation created by the Chinese government to channel massive state resources into a selective tier of research universities aimed at building world-class scientific capacity. Operating as a fully integrated secondary college within the university, the new school is designed to align directly with national artificial intelligence strategies and accelerate domestic technological breakthroughs.
During the unveiling ceremony, the newly formed school and the regional Xiangjiang Laboratory jointly released the "Xiangjiang Embodied Brain Model 1.0," an algorithmic framework for embodied AI that captured global honors at the ECCV 2026 RoboDojo Embodied AI Safety World Model Challenge. Researchers simultaneously introduced the Embodi-Verse-110k dataset, a massive repository featuring more than 110,000 robot body configurations to standardize embodied intelligence research.
To bridge academic research and commercial deployment, Central South University established student training partnerships with 13 leading technology and industrial firms, including China Mobile, iFlytek, and robotics maker Unitree Robotics. The university also executed strategic cooperation and donation agreements with Hunan Broadcasting System and Zhuzhou Diamond Cutting Tool Co. Ltd.
The university's aggressive push into AI talent development coincides with broader international deliberations over how educational systems should integrate emerging technologies. A report released by the World Bank, titled "Costing Artificial Intelligence Interventions in Education in Low- and Middle-Income Countries," recommended a three-phased deployment strategy for developing nations seeking to build digital capabilities while controlling variable usage costs.
According to the World Bank study, equipping educators directly with AI tools is significantly more cost-effective for developing countries than deploying student-facing platforms, as teacher-focused implementations require fewer devices and lower upfront infrastructure investments. Unlike traditional educational technologies, AI integration brings dynamic, ongoing expenses for cloud computing, model inference, and data integration.
The World Bank framework advises developing nations to first empower teachers with administrative and instructional AI tools before selectively scaling digital learning applications for students and ultimately embedding AI across entire administrative and curricular infrastructure.
