Corrosion remains one of the most costly and persistent challenges in the oil and gas industry—silently eroding infrastructure, compromising safety, and draining billions of dollars annually from operations worldwide. Despite decades of engineering advancements, traditional corrosion management practices still rely heavily on reactive strategies, periodic inspections, and delayed corrective actions—approaches that are no longer sufficient in today’s high-risk, high-demand energy landscape.

AI Techniques for Materials Corrosion Management in the Oil and Gas Industry delivers a transformative shift in how corrosion is understood, predicted, and controlled. This book introduces a new paradigm—where artificial intelligence and machine learning enable predictive, data-driven decision-making that anticipates failures before they occur.

Bridging the gap between conventional engineering practices and cutting-edge digital innovation, this book provides a comprehensive and practical roadmap for integrating AI into corrosion and asset integrity management. Readers will discover how advanced analytics, real-time data, and intelligent algorithms can significantly enhance reliability, reduce downtime, optimize maintenance strategies, and improve overall operational efficiency.

More than just a technical guide, this book is a strategic resource for engineers, researchers, and industry leaders seeking to modernize corrosion management systems and future-proof their operations. By replacing reactive approaches with proactive intelligence, it empowers organizations to mitigate risk, improve safety, and unlock new levels of performance in energy infrastructure.

Dr. Muhammad Hussain is a globally recognized thought leader in corrosion management, asset integrity, and the application of artificial intelligence in the energy sector. As the principal author of AI Techniques for Materials Corrosion Management in the Oil and Gas Industry, he stands at the forefront of integrating advanced analytics with industrial operations to drive safer, smarter, and more sustainable infrastructure.

With a career spanning research, innovation, and industry leadership, Dr. Hussain has pioneered the use of data-driven methodologies, machine learning, and predictive analytics to transform corrosion management and pipeline integrity practices. His work bridges the gap between traditional engineering and next-generation digital technologies, enabling energy companies to anticipate failures, optimize maintenance strategies, and significantly reduce operational risk.

Dr. Hussain has authored multiple books and influential research publications covering artificial intelligence, big data analytics, asset integrity management, risk-based inspection, and pipeline systems. His contributions extend to critical areas such as hydrogen pipeline integrity and the future of energy infrastructure, positioning him as a key voice in the transition toward more resilient and sustainable energy systems.

Widely respected for his vision and technical depth, Dr. Hussain continues to shape the evolution of intelligent asset management—leveraging AI to redefine how the oil and gas industry approaches corrosion, reliability, and long-term performance.

Dr. Tieling Zhang is currently serving as the director of the Engineering Asset Management and Systems Engineering Research Group at the Faculty of Engineering and Information Sciences, University of Wollongong, Australia. His group has developed its capabilities to provide research and training in the areas of railway asset management, system reliability and maintenance, supply chain management and optimization, condition-based maintenance and operation of wind turbines, rail track modeling, railway vibration and noise, risk assessment of railway systems, and battery health management.

Dr. Aziza Chakir is a Senior Lecturer, Keynote Speaker and currently serves as a researcher professor in the university Hassan II. Her research interests include in the area of Computer Engineering, Information Systems, Digital culture, Software Engineering, Knowledge Transfer Technology, IT Governance, Cloud Computing, Suitable Development (Green IT..), Machine Learning, Big Data, Data mining. She is currently working on many projects such as "Green computing" and "Ecological frameworks". Her disciplines include Architectural Engineering Information Technology, Politics Information Systems (Business Informatics) and Artificial Intelligence Distributed Computing. Her skills and expertise fall into the fields of Risk Management, Business Intelligence, IT Governance, Corporate Governance, Information Technology, Cloud Computing, and E-Government.

She has authored & edited many books with renowned national & international publishers including IGI Global USA, Lambert Academic Publishing, Springer, etc. In addition, she has published research papers in national and international journals indexed by Scopus. She has also reviewed many international journals indexed by Scopus.