M. Z. Naser is a tenure-track Assistant Professor at the Department of Civil and Environmental Engineering and Earth Sciences and a member of the Artificial Intelligence Research Institute for Science and Engineering (AIRISE) at Clemson University. At the moment, his research group is creating causal & eXplainable machine learning methodologies to discover new knowledge hidden within systems belonging to the domains of structural engineering and materials science to help realize functional, sustainable, and resilient infrastructure. He is currently serving as the chair of the ASCE Advances in Information Technology committee and on a number of international editorial boards, as well as codal building committees (in ASCE, ACI, PCI, and FiB). He is a registered professional engineer in the states of Michigan and South Carolina.

• 1. Civil and Environmental Engineering: Past, Present, and Future2. Machine Learning: The Pursuit of Data-driven Analysis3. Why Do We Need Causality? Overcoming the Limitations of Data-driven Analysis4. Introduction to Causal Machine Learning: Theory and Algorithms5. Application of Causal Machine Learning to Discover Knowledge in Civil and Environmental Engineering Problems6. Application of Causal Inference to Discover Knowledge in Civil and Environmental Engineering Problems7. Best Practices for Adopting Causal Machine Learning and Future Research Directions8. A Look into the Future of Civil and Environmental Engineering from the Lens of Causal Machine Learning