101 citations · 107 across the 4 of their papers we have counts for
4 papers
A Large Language Model for Disaster Structural Reconnaissance Summarization
Yuqing Gao, Guanren Zhou, Khalid M. Mosalam
Artificial Intelligence (AI)-aided vision-based Structural Health Monitoring (SHM) has emerged as an effective approach for monitoring and assessing structural condition by analyzi…
Prediction of the Most Fire-Sensitive Point in Building Structures with Differentiable Agents for Thermal Simulators
Yuan Xinjie, Khalid M. Mosalam
Fire safety is crucial for ensuring the stability of building structures, yet evaluating whether a structure meets fire safety requirement is challenging. Fires can originate at an…
Balanced Semi-Supervised Generative Adversarial Network for Damage Assessment from Low-Data Imbalanced-Class Regime
Yuqing Gao, Pengyuan Zhai, Khalid M. Mosalam
In recent years, applying deep learning (DL) to assess structural damages has gained growing popularity in vision-based structural health monitoring (SHM). However, both data defic…
Text Analytics for Resilience-Enabled Extreme Events Reconnaissance
Alicia Y. Tsai, Selim Gunay, Minjune Hwang +4
Post-hazard reconnaissance for natural disasters (e.g., earthquakes) is important for understanding the performance of the built environment, speeding up the recovery, enhancing re…