· Awards and Honors · 2 min read
Great News🏆: AI Cube Lab Teams Win Two Second Prizes at Computer Design Contest
Two undergraduate teams from AI Cube Lab won Second Prize in the Guangdong regional round of the 2026 China Collegiate Computer Design Contest's Artificial Intelligence Application track. The project 'High-Dimensional Time-Series Multi-Agent Collaborative Perception and Defect Diagnosis for FDM Printing' was recommended for the national finals, while 'Domestic PLC Large Model Edge Inference and Full-Stack Intelligent Control for Advanced Manufacturing' was one of only two award-winning entries from Sun Yat-sen University in the AI Practice competition category.
Recently, the results of the Guangdong regional round of the 2026 China Collegiate Computer Design Contest were announced, and two undergraduate teams guided by AI Cube Lab both won Second Prize, demonstrating the laboratory’s strong track record in undergraduate cultivation at the intersection of artificial intelligence and intelligent manufacturing.
The team composed of Li Yiyi, Xie Ying, Wang Ziming, Chen Zexu, Liu Xinshao, Wei Jiangying, and Deng Yu won Second Prize with their project “High-Dimensional Time-Series Multi-Agent Collaborative Perception and Defect Diagnosis for FDM Printing.” The project focuses on modeling multi-source time-series data during additive manufacturing (FDM printing) and achieves precise defect diagnosis through multi-agent collaborative perception, showcasing the team’s solid algorithmic foundation and engineering capability. The project also stood out among numerous entries and was recommended for the national finals.
Meanwhile, the team composed of Lin Zhengang, Li Wenfei, Liu Qiuyang, Chen Xiaowen, Lin Yule, Zhou Yingmei, Huang Lingxuan, and Yu Chenyu, under the guidance of Associate Professor Feng Jianshe, won Second Prize in the AI Practice competition category of the Artificial Intelligence Application track with their project “Domestic PLC Large Model Edge Inference and Full-Stack Intelligent Control for Advanced Manufacturing.” Notably, this was one of only two award-winning entries from Sun Yat-sen University in the AI Practice category, fully demonstrating the project’s technical depth and innovation.
Both projects closely align with industrial demand for the intelligent upgrading of domestically-made equipment — one targeting process monitoring in additive manufacturing, the other targeting large-model transformation of PLCs, a core component of industrial control. This achievement is another vivid example of the laboratory’s ongoing effort to bring undergraduates into research early and cultivate their innovation capabilities in real engineering contexts.
