DRF Lunchtime Clinic - Prof Asaad Faramarzi

Prof Asaad Faramarzi, Professor of Civil and Geotechnical Engineering in the School of Engineering and head of the Department of Civil Engineering at the University of Birmingham, joins us at the DRF Lunchtime Clinic to talk on Data-Informed Ground Engineering: Machine Learning for Resilient and Sustainable Infrastructure.

Abstract

This presentation explores how machine learning is transforming ground engineering towards more resilient and sustainable infrastructure. Professor Faramarzi will illustrate this through several examples, highlighting recent advances in applying ML to interpret data from state-of-the-art sensing technologies, such as quantum sensors, to convert complex subsurface information into actionable insights. These advances enable faster, safer, and more cost-effective engineering decisions, saving millions of pounds in asset management and enhancing public safety. He will also discuss his work integrating ML with the fundamentals of geomaterial behaviour and computational mechanics to model complex geotechnical problems with greater accuracy and efficiency. Together, these approaches demonstrate a data-informed framework for intelligent and sustainable civil infrastructure design and maintenance particularly our buried infrastructure. 

Bio

Professor Faramarzi is a Professor of Civil and Geotechnical Engineering in the School of Engineering and head of the Department of Civil Engineering at the University of Birmingham. His main research interests are development and application of intelligent computational solutions, and machine learning in geotechnical infrastructure modelling. He also has interest in geophysical sensing, ground engineering, experimental modelling, and energy geotechnics. He has led several research projects in the above areas funded by UKRI, Industry and RAEng. His recent work focuses on advancing smart and sustainable infrastructure through data-driven modelling, AI integration, and innovative approaches to improve the performance, sustainability, and resilience of civil infrastructure systems.