We are thrilled to announce that the research team from the Department of Electrical and Computer Engineering has been awarded Gold Medal and Silver Medal in the 51st International Exhibition of Inventions at Geneva, which is the largest global exhibition for inventors, researchers, and industry leaders, devoted exclusively to inventions, the results of their research and their new products. The team members include Dr. Albert T.L. LEE, Dr. Vincent W.L. TAM, Ir Dr. K.H. LAM, Prof. Lawrence K. YEUNG, Mr. Alex Y.W. KIANG, and Dr. Zhenglong LI. The team is honoured to express their deepest gratitude to Prof. Kaibin HUANG, Head of the Department of Electrical and Computer Engineering, the Dean of the Faculty of Engineering, and the Office of Vice-President and Pro-Vice-Chancellor (Research) for their tremendous support. With their backing, we became the only team composed solely by ECE members to win both medals at Inventions Geneva 2026.
Gold Medal
Project Name: Generative-AI Knowledge-Based Education Chatbot – a Trusted Learning Partner for Students
To enrich and enhance students’ learning experiences, the team developed an in-house, knowledge-based GenAI chatbot (K-bot) with support from the Fund for Innovative Technology-in-Education (FITE). The chatbot is built on a Retrieval-Augmented Generation (RAG) framework and complemented by multi-agent technologies. In essence, this design directs the large language model (LLM) to retrieve and synthesise relevant information from domain-specific course materials, with different agents collaborating on tasks such as information retrieval, response generation, and quality assurance. This provides a quick, cost-effective, scalable, and sustainable way to improve LLM outputs, ensuring they remain relevant, accurate, and consistent across diverse learning contexts. K-bot has already demonstrated a strong positive impact on overall learning outcomes, serving as a trusted learning companion for students.
Silver Medal
Project Name: Alviss – Educational AI Platform Built with Expert-guided Knowledge Base for Personalised Learning
Alviss is an educational AI platform built to make personalised learning practical at scale. It creates two evolving knowledge profiles: an instructor profile that captures teaching logic, course expectations, and expert know-how, and a student profile that reflects mastery, learning gaps, and progress. Using these profiles through an expert-guided knowledge base, Alviss delivers course-specific support to students when they need help, while also giving teachers clear feedback on common questions, confusion points, and class-wide progress. This helps students receive more suitable guidance and helps teachers refine their pace, emphasis, and explanations. Alviss turns teaching expertise into scalable support and learning data into better teaching decisions.
