The Hong Kong Polytechnic University (PolyU) is committed to driving high-impact cross-disciplinary and international research collaborations, underscoring the University's contribution to advancing global technological and scientific innovation. In the French National Research Agency / Research Grants Council Joint Research Scheme (ANR/RGC JRS) 2026/27 Exercise, two PolyU projects have received total funding of approximately HK$3.56 million. These projects focus on innovative concrete materials and language science, respectively.
Led by Prof. Chi-sun POON, Michael Anson Professor in Civil Engineering and Distinguished Research Professor of the Department of Civil and Environmental Engineering at PolyU, alongside French Principal Investigator Prof. Roland Pellenq of the French National Centre for Scientific Research, the project “Innovative Concrete Materials for Performance, Resilience and Optimization Economics (IMPROVE-Concrete)” secured RGC funding of HK$2,122,054 for 48 months.
The IMPROVE-Concrete (Imp-C) project aims to enhance the performance, resilience, and sustainability of concrete through innovative material design. This project targets the root cause of concrete degradation—capillary pores in the calcium silicate hydrate (CSH) phase. By mastering CSH capillary porosity, the Imp-C project provides practical, scalable solutions to enhance infrastructure durability and promotes construction waste recycling for a circular economy, supporting global low-carbon development goals.
Led by Prof. Emmanuele CHERSONI, Assistant Professor in the Division of Artificial Intelligence and the Humanities and the Department of Language Science and Technology at PolyU, alongside French Principal Investigator Dr Philippe Blache of Aix-Marseille University, the project “Brain Decoding with CALM: Conversation Alignment with Language Models” secured RGC funding of approximately HK$1,439,978 for 36 months. The co-Investigators of the project are Prof. HSU Yu yin, Associate Professor, and Dr. GU Chanyuan, Research Assistant Professor, both from the Department of Language Science and Technology.
The project aims to create multimodal conversational corpora in Chinese and French, along with neurophysiological data from speakers engaged in natural conversational tasks, and to develop large language models (LLMs) specialised for conversational prediction in both languages. This cross-lingual approach is proposed to improve the generalizability of conversational NLP models and deepen our understanding of how conversational structure is jointly represented in language and neural signals.
The ANR/RGC JRS aims to strengthen collaboration between French and Hong Kong research communities.
