Prof. Zhen-Yu YIN, Professor of the Department of Civil and Environment Engineering at PolyU.
Prof. Zhen-Yu YIN and his team.
The resilience of geo-infrastructure is a critical global task amid climate change challenges. A project by the Hong Kong Polytechnic University (PolyU) is propelling machine learning and artificial intelligence (AI) to advance geotechnical engineering, positioning them as next-generation tools to tackle complex challenges. This research has been supported by the European Union — Hong Kong Research Cooperation Co-funding Mechanism by the Research Grants Council (RGC) 2024/25.
The awarded joint project titled “Geotechnical Resilience through Intelligent Design” is led by Prof. Zhen-Yu YIN, Professor of the Department of Civil and Environment Engineering at PolyU, in collaboration with Dr Enrico Soranzo, Deputy Head of the Institute of Geotechnical Engineering at BOKU University in Austria. Prof.YIN’s research has been awarded HK$497,600 for a duration of 48 months.
Geotechnical engineering faces inherent challenges due to the diverse compositions of geomaterials, complex geological processes, and the nonlinear interactions among them. These challenges are further intensified by the impacts of climate change, with a rise in the frequency of extreme weather events.
This project aims to train the next generation of machine learning-savvy geotechnical engineers and assemble an interdisciplinary, intersectoral team that connects industry and academia. Together, the team will develop transformative approaches to infrastructure design, including tunnels, tailing dams, artificial slopes, and embankments, as well as geohazard monitoring and prediction through innovative data-driven methods.
Key initiatives include exploring advanced sensor technologies for on-site data acquisition, leveraging generative AI techniques to optimise design processes, and implementing physics-informed neural networks to enhance the fidelity of geotechnical simulations by integrating physical principles into machine learning models.
Additionally, the project focuses on designing customised solutions for specific challenges, tailoring machine learning approaches to address geotechnical issues encountered in the construction and management of geoinfrastructures, such as tunnels and tailing dams. It also aims to improve the monitoring and mitigation of geohazards, like landslides and earthquakes, thereby enhancing safety and efficiency in critical areas.
Prof. YIN said, “By undertaking this multidimensional approach, the research aims not only to apply machine learning in geotechnical engineering but also to fundamentally transform the field, ushering in a new era of efficiency, sustainability, and resilience.”
The European Union (EU) – Hong Kong Research Cooperation Co-funding Mechanism by the RGC aims to strengthen the collaboration between European and Hong Kong research communities in areas of mutual interest in order to achieve world-class scientific results.
