On April 19, the 10th Huawei ICT Competition China Final concluded successfully in Wuhan. After fierce competition, the U-care “Yuka” team (supervised by Researcher Xinman Chen), composed of graduate students Jiao Zilong, Luo Qianxing, and Zheng Haoyu (Class of 2025) from the School of Electronic Science and Engineering (School of Microelectronics), Faculty of Engineering, won the National Second Prize with their project: “U-care ‘Yuka’: An Emotional Interaction Robot for Home‑Based Elderly Care Based on a Mobile Chassis and Lightweight End‑to‑End Vision‑Language‑Action Model.”

   U-care “Yuka” is an emotional interaction and embodied intelligent robot system designed for home‑based elderly care, integrating safety monitoring, emotional companionship, and household assistance. The system adopts an end‑cloud collaborative architecture: on the cloud, it deploys large language models, visual detection models, and voice cloning models based on Ascend 910B computing power to handle emotional interaction and anomaly detection; on the edge, a Raspberry Pi is used for audio‑video acquisition and skeletal keypoint extraction, enabling low‑latency voice intercom and secondary verification for fall false‑alarm reduction; the mobile execution unit relies on SLAM‑based autonomous navigation and a lightweight end‑to‑end vision‑language‑action dual‑arm collaboration model to precisely control robotic arms for grasping and other household assistance tasks. The project is built upon an embodied intelligence and multi‑agent collaborative architecture, precisely empowering smart elderly care. This is not only a vivid practice of using technology to serve people’s livelihood but also holds great potential for expansion into more home‑service scenarios.

   In addition, the undergraduate MindAligner team (supervised by Professor Jiahui Pan), composed of Chen Rongtao, Huang Zhuoyi, and Chen Jiayou from the School of Artificial Intelligence (Software Engineering major), won the National Second Prize in the same competition with their project: “MindAligner: An Affordable Brain‑Computer Interface Assisted Diagnosis Platform for Disorders of Consciousness, Integrating MindSpore and Large Language Models.” To address pain points such as strong subjectivity of traditional assessment, high misdiagnosis rate, and insufficient diagnostic capability at primary care levels, the platform builds a closed‑loop system integrating low‑cost EEG acquisition, intelligent analysis, assisted diagnosis, and report generation. Technically, it adopts an “end‑edge‑cloud” collaborative architecture: on the end side, a self‑developed portable terminal enables bedside EEG signal acquisition; on the cloud, based on Huawei Ascend 910B computing power and accelerated by MindSpore, ModelArts, and CANN, the self‑developed EEGAlignNet model is deployed, integrating algorithms such as EEG‑CutMix, reinforced self‑building graphs, and progressive multi‑domain adaptation to improve recognition accuracy and generalization under few‑shot and cross‑individual scenarios; on the application side, the Pangu large language model is accessed to convert recognition results into interpretable and revisable assisted diagnostic suggestions. The core algorithms have been published in an IEEE Trans paper and supported by a software copyright, demonstrating value for clinical translation and grassroots promotion.

   In recent years, the Faculty of Engineering, the School of Electronic Science and Engineering (School of Microelectronics), and the School of Artificial Intelligence have taken multiple measures to fully establish a talent cultivation chain from classroom teaching to cutting‑edge research and industrial practice. Winning the national award in the Huawei ICT Competition not only serves as an authoritative recognition of the solid technical capabilities of engineering students but also represents the best example of the outstanding educational achievements of the School of Microelectronics in the fields of integrated circuit science and intelligent systems. Looking ahead, the Faculty of Engineering will continue to encourage young students to keep in mind “national priorities” and shoulder “national responsibilities,” bravely exploring real‑life scenarios such as smart elderly care and precision medicine, and striving to become high‑quality engineering and technology talents who will lead the digital era.