Reshaping Geotechnical Engineering with Machine Learning Theory, Applications, and Innovations

Dr. Divesh Ranjan Kumar is a post-doctoral fellow at Research unit in data science and digital transformation, department of civil engineering, Thammasat School of Engineering, Thammasat University, Pathumthani, Thailand. He holds a distinguished academic background, having completed both his M.Tech and Ph.D. in Geotechnical Engineering from the esteemed NIT Patna. In addition to his research, Dr. Kumar's work often integrates advanced machine learning techniques to address complex geotechnical challenges, such as predicting probability of liquefaction potential, finite element modelling, the unconfined compressive strength of controlled low-strength materials using fly ash and pond ash. In addition to his research, Dr. Kumar is actively involved in the scholarly community, with publications in international journals, national journals, participating in international conferences and contributing to scholarly publications. His dedication to advancing civil engineering through innovative research and collaboration underscores his role as a leading figure in his areas of expertise.

Dr. Samui is an Associate Professor in the Department of Civil Engineering at NIT Patna, India. He received his PhD in Geotechnical Engineering from the Indian Institute of Science Bangalore, India, in 2008. His research interests include geohazard, earthquake engineering, concrete technology, pile foundation and slope stability, and application of AI for solving different problems in civil engineering. Dr. Samui is a repeat Elsevier editor but also a prolific contributor to journal papers, book chapters, and peer-reviewed conference proceedings.

Dr. Pradeep Thangavel is a post-doctoral fellow at Thammasat AI Center, College of Innovation, Thammasat University Bangkok. He received an M.E. in structural engineering from Anna University and a Ph.D. from NIT Patna. He was formerly working as an assistant professor at NIT Andhra Pradesh. His primary research interests centre around Building materials like cold-form steel, concrete in steel tubes, and Sustainable Materials in concrete. Furthermore, he is actively researching the use of machine learning in the structural engineering industry and rock. With publications in national and international journals, his research has substantially contributed to the academic community.

Dr. Warit Wipulanusat is an Associate Professor at the Faculty of Engineering, Thammasat University, Thailand, and a lecturer in the MBA program at Thammasat University. He earned his doctoral degree in Construction Management from the Griffith School of Engineering, Griffith University. As the Head of the Thammasat University Research Unit in Data Science and Digital Transformation, Dr. Warit leads research efforts in applying machine learning and soft computing techniques across various civil engineering disciplines.