Mahmoud Ayyad

Mahmoud Ayyad is a Researcher at Stevens Institute of Technology, affiliated with the Charles V. Schaefer, Jr. School of Engineering and Science's Department of Civil, Environmental and Ocean Engineering. His work focuses on applying machine learning to environmental and coastal engineering challenges, including storm surge modeling, energy harvesting systems, and fluid dynamics. He holds a PhD in Civil, Environmental, and Ocean Engineering from Stevens (2023), an MS in Engineering Mathematics from Cairo University (2017), and a BS in Aerospace Engineering (2013).

Research Interests: Dr. Ayyad’s research integrates artificial intelligence with environmental systems analysis. His work emphasizes:

• Machine learning-driven hurricane storm surge prediction under climate change scenarios
• Optimization of energy harvesting systems using neural networks
• Computational fluid dynamics for transonic aerodynamics and wave energy converters
• Uncertainty quantification in coastal morphodynamic models

Publications: His recent work spans AI-based storm surge hazard assessment, piezoelectric energy harvesting optimization, and river ice detection using machine vision. Over 20 peer-reviewed articles demonstrate his interdisciplinary approach combining environmental engineering with advanced computational methods.

Advising/Grants: While no specific grants or student advisement are documented, his research collaborations indicate active participation in Stevens' flood prediction and renewable energy initiatives. His work aligns with the Davidson Laboratory’s focus on coastal engineering and ocean systems.