Ashley Coleman
AI Structural Engineer at aistructuralreview.com
Ashley Coleman is a PhD candidate in structural engineering at the University of California, Berkeley, where her research focuses on performance-based seismic design and the integration of machine learning into structural health monitoring. She has contributed to studies on nonlinear finite element modeling and code-calibration for resilient infrastructure. Deep experience. Intellectual curiosity.
Editorial standards
Our editorial standards are built on an unwavering commitment to accuracy, independence, and integrity: every piece of content is rigorously fact-checked against primary sources, subjected to multiple layers of editorial review, and held to the highest standards of clarity, fairness, and transparency, ensuring that readers receive trustworthy, well-reasoned information free from bias, conflicts of interest, or sensationalism.
Questions? Contact the editorial desk.
Recent articles by Ashley Coleman
- 2026 CLT Code: UBC/UCI Tests Reveal Prescriptive Ductility Gap at 2:1 Ratio August 19, 2026
- Berkeley SHM Trials: Edge Nonlinear Indices Cut Lifecycle Costs August 17, 2026
- 2026 IBC Perimeter Frames: Penalty Math & Selection Matrix August 16, 2026
- 2026 ASCE 7-22 Coastal Pile Depth: Hybrid Saves 18% August 14, 2026
- Mesh-First Protocol vs Material Laws in Collapse Drift (2026) August 13, 2026
- August 11, 2026
- August 10, 2026
- 2026 Ternary Blend: Only Reliable for Chloride Exposure August 9, 2026