A full list of publications is available on Google Scholar

Peer-Reviewed Journal
  1. Hu, D., Li, S., & Wang, M. (2023). Object detection in hospital facilities: A comprehensive dataset and performance evaluation. Engineering Applications of Artificial Intelligence, 123, 106223. (IF: 7.802)
  2. Hu, D., Li, S., Du, J., & Cai, J. (2023). Automating Building Damage Reconnaissance to Optimize Drone Mission Planning for Disaster Response. Journal of Computing in Civil Engineering, 37(3), 04023006. (IF: 5.802)
  3. Hu, D., Chen, L., Du, J., Cai, J., & Li, S. (2022). Seeing through Disaster Rubble in 3D with Ground-Penetrating Radar and Interactive Augmented Reality for Urban Search and Rescue. Journal of Computing in Civil Engineering, 36(5), 04022021. (IF: 5.802)
  4. Hu, D., Chen, J., & Li, S. (2022). Reconstructing unseen spaces in collapsed structures for search and rescue via deep learning based radargram inversion. Automation in Construction, 140, 104380. (IF: 10.517)
  5. Hu, D., & Li, S. (2022). Recognizing object surface materials to adapt robotic disinfection in infrastructure facilities. Computer‐Aided Civil and Infrastructure Engineering, 37(12), 1521-1546. (IF: 10.066)
  6. Hu, D., Nejat, A., & Shankar, V. (2021). Random Parameter Model of Postdisaster Household Relocation. Natural Hazards Review, 22(3), 04021027. (IF: 4.2)
  7. Hu, D., & Nejat, A. (2021). Role of spatial effect in postdisaster housing recovery: Case study of Hurricane Katrina. Journal of Infrastructure Systems, 27(1), 05020009. (IF: 3.462)
  8. Hu, D., Zhong, H., Li, S., Tan, J., & He, Q. (2020). Segmenting areas of potential contamination for adaptive robotic disinfection in built environments. Building and environment, 184, 107226. (IF: 7.093)
  9. Hu, D., Li, S., Chen, J., & Kamat, V. R. (2019). Detecting, locating, and characterizing voids in disaster rubble for search and rescue. Advanced Engineering Informatics, 42, 100974. (IF: 7.862)
  10. Hu, D., Yu, W., Lu, Y., Chen, L., Han, F., & Liu, W. (2019). Experimental study on unfrozen water and soil matric suction of the aeolian sand sampled from Tibet Plateau. Cold Regions Science and Technology, 164, 102784. (IF: 4.427)
  11. Hu, D., Yu, W., Zhao, J., Liu, W., Han, F., & Yi, X. (2019). A hierarchical mixed logit model of individuals' return decisions after Hurricane Katrina. International journal of disaster risk reduction, 34, 443-447. (IF: 4.842)
Peer-Reviewed Conference Proceedings
  1. Hu, D., Li, S., Du, J., & Cai, J. Human-in-the-Loop Robot-Augmented Intelligent System for Emergency Reconnaissance. In Computing in Civil Engineering 2021 (pp. 1409-1416).
  2. Hu, D., Li, S., & Cai, J. (2021). A machine learning-based framework for automatic bridge deck condition assessment using ground penetrating radar. In Computing in Civil Engineering 2021 (pp. 74-82).
  3. Hu, D., Li, S., Cai, J., & Hu, Y. (2020, December). Toward intelligent workplace: Prediction-enabled proactive planning for human-robot coexistence on unstructured construction sites. In 2020 Winter Simulation Conference (WSC) (pp. 2412-2423). IEEE.
  4. Hu, D., Hou, F., & Li, S. (2020, November). Ground-penetrating radar-based root architecture detection and characterization. In 18th International Conference on Ground Penetrating Radar (pp. 243-246). Society of Exploration Geophysicists.
  5. Hu, D., & Li, S. (2020, November). 3D reconstruction of voids in disaster rubble using ground-penetrating radar. In 18th International Conference on Ground Penetrating Radar (pp. 452-455). Society of Exploration Geophysicists.
  6. Hu, D., Hou, F., Blakely, J., & Li, S. (2020, November). Augmented reality based visualization for concrete bridge deck deterioration characterized by ground penetrating radar. In Construction Research Congress 2020: Computer Applications (pp. 1156-1164). Reston, VA: American Society of Civil Engineers.