Jieun Hur

Jieun Hur works on assessing the safety and reliability of infrastructure systems, including transmission towers, bridges, pipelines, and nuclear power plant components, under hazards such as earthquakes, typhoons, wind, flooding, and soil erosion. Much of the work uses probabilistic risk modeling and machine learning (such as gradient boosting and active learning methods) to predict failure risks and guide maintenance or repair decisions. This research aims to help engineers and infrastructure managers make data-informed decisions about inspection, budgeting, and risk mitigation for critical infrastructure.

Publication output has been variable over the past decade, with a gap in 2023-2024 followed by a notable increase in 2025, while the 5-year average remains relatively modest at 1.6 papers per year.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026