Wrocław University of Science and Technology, in partnership with the University “G. d’Annunzio” of Chieti–Pescara, is pleased to host the 10th International Symposium on Geotechnical Safety and Risk (ISGSR 2027) in Wrocław, Poland, from 28 June to 2 July 2027.

The symposium continues the biennial ISGSR series and is supported by the Geotechnical Safety Network (GEOSNet), the relevant ISSMGE Technical Committees and the ASCE Geo-Institute Technical Committee on Risk Assessment and Management. The event will be held in person and will bring together researchers, practitioners and students working across geotechnical engineering, uncertainty and risk analysis, and digital innovation.

Under the theme “Next-Generation Modelling for Geohazards and Reliable Geotechnics”, ISGSR 2027 will highlight advances in uncertainty quantification, digital twins, machine learning and their application to geohazards and resilient infrastructure.

Join us in Wrocław for the 10th edition of the ISGSR!

Conference topics include:

Key emerging topics:
• Flood risk under climate change
• Uncertainties in Digital Twin Models for Geotechnical Engineering
• Reliability issues of geotechnical techniques used in planetary exploration

Core topics:
• Benefits of statistical, probabilistic, and geostatistical site characterization
• Soil and rock databases and their use in geotechnical research and practice
• Modelling of spatial variability and effects on geotechnical design
• Modelling of transformation uncertainty and effects on geotechnical design
• Bayesian methods in geotechnical engineering
• Evolutionary approaches to probabilistic geotechnical numerical analysis
• Machine learning: applications and benefits to geotechnical analysis and design
• Fuzzy logic and its applications in geotechnical design and decision making
• Reliability-based geotechnical design codes and cost–performance optimization
• Risk analysis, evaluation, and management for soil-structure systems
• Dissemination of geotechnical risk and reliability methods and approaches
• Multiple risk assessments in urban areas
• Artificial intelligence and deep learning in geotechnical applications.