Dr. Gong studies the resilience of infrastructure and building systems to intensified natural and anthropogenic disturbances by direct impacts such as hurricane, tsunami, and cumulative and secondary impacts such as climate change and sea level rise. Among other things, one of his particular research focuses is on studying the convergence approaches in remote sensing, infrastructure analysis, artificial intelligence, and system modeling and simulation for resilient coastal communities. His group is often deployed in the field to conduct forensic studies of extreme weather events with the eventual goal of turning disaster data into knowledge to inform resilient rebuild needs.
Journal articles:
Zhou, Z., Meneses, D. M., Yu, Y., Gong, J., & Guo, Q. (2021). Delineation of Small Flat Watershed with High-Resolution DEM from Terrestrial Laser Scanning. Journal of Hydrologic Engineering.
Zhou, Z., Gong, J., & Hu, X. (2019). Community-scale multi-level post-hurricane damage assessment of residential buildings using multi-temporal airborne LiDAR data. Automation in Construction.
Hu, X., & Gong, J. (2019). Framework for prioritizing geospatial data processing tasks during extreme weather events. Advanced Engineering Informatics.
Thomas, N. M., Calderón, L., Senick, J., Sorensen-Allacci, M. A., Plotnik, D., Guo, M., Yu, Y., Gong, J., Andrews, C. J., & Mainelis, G. (2019). Investigation of indoor air quality determinants in a field study using three different data streams. Building and Environment.
Wang, Z., Hu, H., Guo, M., & Gong, J. (2019). Optimization of Temporary Debris Management Site Selection and Site Service Regions for Enhancing Postdisaster Debris Removal Operations. Computer-Aided Civil and Infrastructure Engineering.
Hu, X., Gong, J., Renard, E. G., & Parashar, M. (2019). Two-Stage Framework for Big Spatial Data Analytics to Support Disaster Response. In C. Baru, J. Huan, L. Khan, X. T. Hu, R. Ak, Y. Tian, R. Barga, C. Zaniolo, K. Lee, & Y. F. Ye (Eds.), Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 (pp. 5409-5418). [9005613] (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019). Institute of Electrical and Electronics Engineers Inc.
