The 6th Machine Learning in Geotechnics Dialogue
Over the past five years, the Machine Learning in Geotechnics Dialogue (MLIGD) series has established itself as a prominent platform for exploring the intersection of machine learning (ML) and geotechnical engineering. Each edition has addressed a unique and forward-thinking aspect of this transformative field.
- 1st Dialogue (28 July 2019): Explored the foundational "Application of Machine Learning in Geotechnics."
- 2nd Dialogue (14 December 2019): Delved into "Opportunities and Challenges in Developing and Applying ML to Geotechnical Engineering Research and Practice."
- 3rd Dialogue (3 December 2021): Proposed the concept of "ML Supremacy Projects."
- 4th Dialogue (5 December 2023): Examined "Supremacy Projects That Potentially Bring Disruptive Value to Transform Geotechnical Research and Practice."
- 5th Dialogue (12 October 2024): Brought together industry practitioners and researchers to address “Challenges in Geotechnical/Geological Data Sharing and Potential Solutions.”
Building upon the success of these events, the 6th Machine Learning in Geotechnics Dialogue (6MLIGD) will bring together a diverse mix of academics, students, industry professionals, and policymakers to explore a forward-looking and transformative theme. This year’s focus is on investigating how Machine Learning (ML) can fundamentally reshape geotechnical engineering practice and education, with an emphasis on new methodologies, innovative tools, and future paradigms.
Topic Description
ML Revolution in Geotechnics: Transforming Practice and Education for Future Engineers
The 6MLIGD will spotlight the dual impact of ML as both:
- A disruptive force transforming traditional geotechnical engineering workflows, including site investigations, design optimization, and infrastructure monitoring; and
- A catalyst for reimagining education, equipping the next generation of geotechnical professionals with ML-integrated knowledge, skills, and tools.
The 6MLIGD aims to provide a collaborative platform to envision how ML will disrupt and redefine geotechnical engineering, ensuring the discipline evolves to meet the demands of a rapidly changing world.
Co-conveners:
Enrico Soranzo (BOKU University, Austria)
Mingliang Zhou (Tongji University, China)