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School of Mathematics‑Physics and Statistics Conducts Research and Exchange Visit to Zhiyuan Innovation
发布日期:2026-08-20 9:29:34   发布人:

On August 13, 2026, Fang Hong, Dean of our School; Qiu Lu, Deputy Secretary of the Party General Branch; Gao Meina, Vice Dean; Zhan Xiaolin, Director of the Statistics Department; Zhang Xuanhao, Deputy Director of the Statistics Department; Xie Xiaoqiang, Deputy Director of the Mathematics Department; and Ye Jiachen, faculty member, led a delegation to visit Zhiyuan Innovation Technology Co., Ltd., where they were warmly received by the enterprise representatives. The two sides had in‑depth exchanges on topics including university‑enterprise collaborative talent cultivation, co‑construction of practical training resources, and innovation of talent‑training models.

Guided by enterprise staff, the delegation visited the Embodied Robot Exhibition Hall, which showcased various robot forms such as wheeled, semi‑humanoid, humanoid and quadruped robots. On‑site technicians demonstrated the practical applications of robots in scenarios including industrial manufacturing, commercial services, scientific research and education, intuitively presenting the industrial implementation achievements of embodied intelligence technologies as they move from laboratories to front‑line industries.



During the exchange meeting, the enterprise introduced its robot operating system deeply integrated with large‑model capabilities. It supports access and collaborative scheduling of heterogeneous robots, and adapts to cutting‑edge technology exploration as well as industrial‑scenario implementation. In view of industrial talent demands, the enterprise pointed out that embodied intelligence, as an emerging vertical track, is witnessing strong demand for talents in three major directions: perception and control, data and models, and scenario‑oriented engineering.



Dean Fang Hong introduced the key work of the school in industry‑education integration. She stated that the school is focusing on big‑data analysis, machine learning, artificial intelligence and other fields to continuously deepen the reform of the curriculum system, and actively exploring effective paths to integrate emerging interdisciplinary disciplines into the existing talent‑training system. For embodied intelligence, this emerging track, the school may give priority to adopting forms such as micro‑majors, inter‑college elective courses and special classes to adapt to the interdisciplinary features of embodied intelligence.


Multiple consensuses were reached at the meeting on issues including talent‑training programs and cooperation mechanisms. In terms of practical training, the enterprise can provide teaching support combining real‑machine operation and simulation environments, together with full‑process support for relevant competitions, to help students accumulate hands‑on practical experience. Meanwhile, in response to the multi‑disciplinary nature of embodied intelligence, the school will cooperate with relevant schools such as the School of Mathematics‑Physics and Statistics, the School of Computer Science and the School of Intelligent Manufacturing to jointly discuss the implementation paths for micro‑majors or special classes. Teaching staff and curriculum resources from all participating schools will be integrated to form joint forces for the implementation of talent‑training programs.

This exchange marks a substantive step forward in our school’s university‑enterprise cooperation in the emerging interdisciplinary field of embodied intelligence. It also provides a new fulcrum for the school to deepen industry‑education integration by leveraging its geographical advantage of being adjacent to industrial parks. Going forward, the school will accelerate the introduction of courses and the deployment of practical‑training resources, enabling students to get exposed to cutting‑edge industrial developments and master practical skills at an early stage, so as to gain competitive advantages in employment within this emerging track.

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