Great News🏆: AI Cube Lab Team Wins National Second Prize at the China Collegiate Computer Design Contest

From 16 to 19 August 2026, the national finals of the 19th China Collegiate Computer Design Contest (4C2026) were held at Jiangnan University in Wuxi, Jiangsu. Associate Professor Feng Jianshe led the team. Xie Ying and Li Yiyi represented the Sun Yat-sen University Advanced Manufacturing Intelligence Laboratory (AI Cube Lab) and won a national Second Prize in the Artificial Intelligence Application (Newland Cup) track. The project had already been recommended for the national finals in the Guangdong round; this further result at the national finals demonstrates the laboratory’s record in undergraduate training at the intersection of artificial intelligence and intelligent manufacturing.

About the contest

The China Collegiate Computer Design Contest is a major national contest for institutions of higher education. This is the 19th edition, and it has wide influence in the training of computer-science talent. The national finals were hosted by Jiangnan University, on the Artificial Intelligence Application (Newland Cup) track. The track emphasizes completeness of application, technical depth, and performance in on-site defense, and places high demands on both theoretical work and engineering implementation.

The national finals bring together projects recommended from provinces, autonomous regions, and municipalities. Moving from a provincial recommendation to a national award is an important test of project completeness and of a team’s overall capability.

From provincial recommendation to a national award

The national result follows directly from the Guangdong round. In May 2026, the team of Li Yiyi, Xie Ying, Wang Ziming, Chen Zexu, Liu Xinshao, Wei Jiangying, and Deng Yu won a Guangdong Second Prize with the project “High-Dimensional Time-Series Multi-Agent Collaborative Perception and Defect Diagnosis for FDM Printing” and was recommended for the national finals. The project focuses on modeling multi-source time-series data in additive manufacturing (FDM printing) and diagnosing print defects through multi-agent collaborative perception. It shows a solid algorithmic foundation and engineering capability, and is consistent with the laboratory’s research on process monitoring in intelligent manufacturing.

At the national finals, Xie Ying and Li Yiyi represented the team, with Associate Professor Feng Jianshe serving as advisor and accompanying the team to Wuxi. The laboratory sent an undergraduate research project onto the national stage in order to test its work on process monitoring for additive manufacturing.

In the same Guangdong round, another laboratory team, also under the guidance of Associate Professor Feng Jianshe, won a Second Prize in the AI Practice category for the project “Domestic PLC Large Model Edge Inference and Full-Stack Intelligent Control for Advanced Manufacturing.” The project was one of only two award-winning entries from Sun Yat-sen University in that category, reflecting the laboratory’s depth of work on intelligent industrial control. The laboratory won two Second Prizes in the Guangdong round; the additive-manufacturing project recommended for the national finals subsequently received a national Second Prize.

Training

Both lines of work address real demand for the intelligent upgrading of domestically produced equipment: one in process monitoring for additive manufacturing, the other in large-model transformation of PLCs, a core component of industrial control. This is consistent with the laboratory’s research orientation of rooting work in real industrial problems. The national Second Prize is a further result of the laboratory’s ongoing effort to involve undergraduates in research at an early stage and to develop their innovation capacity in real engineering settings.

The laboratory will continue to use high-level academic contests as a vehicle, deepen the model of learning through competition and research through competition, and encourage more undergraduates to receive systematic training at the intersection of artificial intelligence and intelligent manufacturing, working to cultivate innovative talent with an international outlook and strong engineering practice.