Doeun Choe

Doeun Choe is an Assistant Professor in the Department of Civil Engineering at New Mexico State University, where he has been serving since January 2021. His expertise spans the intersection of civil engineering, artificial intelligence, and structural reliability with applications to critical infrastructure systems.

Education:

• Ph.D. in Civil Engineering/Structures (2007, Texas A&M University)
• M.S. in Architectural Engineering/Structural Engineering (2002, Inha University, South Korea)
• B.S. in Architectural Engineering (2000, Inha University, South Korea)

Research Focus:

Dr. Choe's work integrates Artificial Intelligence methodologies with traditional structural engineering to solve complex infrastructure challenges. His research in Probabilistic Modeling & Structural Reliability addresses corrosion effects on bridges and coastal structures, while his recent work focuses on Deep Learning applications for structural health monitoring of offshore wind turbines. The AISSRR research group he leads develops innovative approaches to enhance infrastructure resilience against extreme environmental conditions including seismic events and climate change impacts.

Publication Trends:

Dr. Choe's scholarly output demonstrates an evolving research trajectory from foundational reliability analysis (2008-2009 publications on corrosion effects) to advanced AI applications (2019-2021 work on deep learning for structural monitoring). His publications consistently address structural safety challenges through computational methods, with increasing emphasis on renewable energy infrastructure systems in recent years. The research spans civil engineering, computer science, and materials science disciplines.

Academic Leadership:

Dr. Choe leads the Artificial Intelligence for Structural Safety, Risk, & Reliability (AISSRR) research group at NMSU and has developed specialized coursework including the 'Artificial Intelligence for Civil Engineers' series (Machine Learning in Fall 2023 and Deep Learning in Spring 2024), which produces student projects applying AI techniques to real-world civil engineering problems.