Steel Bridge

Steel bridge research currently focuses on improving design, inspection, and maintenance processes through advanced computational methods. Key areas include leveraging deep learning for tasks like crack detection in high-resolution images, optimizing bridge span selection using reinforcement learning, and developing probabilistic models to predict deterioration and the effectiveness of interventions. These advancements aim to enhance bridge safety, reduce costs, and improve the efficiency of bridge management, impacting both the civil engineering and broader AI communities.