Machine Learning Applications in Structural Engineering
- 1st Edition - August 1, 2026
- Latest edition
- Editors: Rahul Biswas, Pijush Samui, Panagiotis G. Asteris
- Language: English
Machine Learning Applications in Structural Engineering is a practical guide to machine learning in structural engineering. With first-hand examples of machine learning applic… Read more
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Machine Learning Applications in Structural Engineering is a practical guide to machine learning in structural engineering. With first-hand examples of machine learning applications, this book is a vital reference for both entry-level readers and advanced professionals. For experts, the book offers insights into emerging applications that are shaping the future of the discipline, making it a compelling choice for engineers looking to leverage machine learning for smarter, more resilient structural solutions. This accessible style makes complex concepts manageable, and the book offers clear explanations while showcasing the potential of machine learning as a versatile tool for advancing structural engineering practices.
It is aimed at engineers, researchers, and students with an interest in integrating new, machine learning technologies into daily practice. Readers will find a balance of foundational theory with hands-on, data-driven solutions tailored to meet real-world demands.
It is aimed at engineers, researchers, and students with an interest in integrating new, machine learning technologies into daily practice. Readers will find a balance of foundational theory with hands-on, data-driven solutions tailored to meet real-world demands.
- Provides a domain-specific resource that combines machine learning with structural engineering
- Describes advanced machine learning techniques for a wide range of structural engineering applications
- Demonstrates how data-driven approaches are reshaping decision-making, enhancing resilience, and providing valuable predictive insights that are of particular importance in structural health monitoring and disaster resilience
- Includes theoretical approaches that are illustrated with extensive use of practical case studies and real-world examples
Postgraduate research students; early and mid-career research scholars; expert academics; professionals in the construction, civil, and structural engineering industries, specifically roles such as structural engineers, project managers, civil engineering consultants, data analysts; artificial intelligence (AI) specialists working in engineering
1. Concrete Technology and Machine Learning Applications
2. Earthquake Engineering Models with Machine Learning
3. Wind Engineering
4. Steel Structure
5. Structural Health Monitoring and Predictive Maintenance
6. Data Integration and Model Optimization in Structural Engineering
7. Case Studies in Machine Learning for Structural Engineering
2. Earthquake Engineering Models with Machine Learning
3. Wind Engineering
4. Steel Structure
5. Structural Health Monitoring and Predictive Maintenance
6. Data Integration and Model Optimization in Structural Engineering
7. Case Studies in Machine Learning for Structural Engineering
- Edition: 1
- Latest edition
- Published: August 1, 2026
- Language: English
RB
Rahul Biswas
Dr Rahul Biswas is an Assistant Professor in the Applied Mechanics Department at Visvesvaraya National Institute of Technology (VNIT) Nagpur, India. Dr Biswas's primary research interests centre around concrete technology and the utilization of sustainable materials in concrete. Additionally, he is actively involved in exploring the application of machine learning in the field of structural engineering
Affiliations and expertise
Assistant Professor, Applied Mechanics Department, Visvesvaraya National Institute of Technology (VNIT) Nagpur, IndiaPS
Pijush Samui
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.
Affiliations and expertise
Associate Professor, Department of Civil Engineering, National Institute of Technology Patna, Patna, Bihar, IndiaPA
Panagiotis G. Asteris
Professor Asteris received his B.S., M.S., and PhD in Civil Engineering from the National Technical University of Athens, Greece. He is currently a Full Professor and the Head of the Computational Mechanics Laboratory, and the Head of the Civil Engineering Department of the School of Pedagogical and Technological Education, Athens. Prof. Asteris is a trailblazer in the field of computational structural engineering. His research spans diverse areas, including artificial neural networks, soft computing, applied and computational mathematics, and masonry materials and structures. He is also the editor-in-chief of two international scientific journals and a member of the editorial board of more than ten international journals.
Affiliations and expertise
Full Professor, Computational Mechanics Laboratory, School of Pedagogical & Technological Education, Athens, Greece