PEER-REVIEWED JOURNAL PAPERS
Murphy, S., Wang, M., Cheng, C.- S., Passalacqua, P., Leite, F. (in review). Land-use Analysis Using Infrastructure Representations and High-Resolution Flood Inundation Mapping Techniques. (in revision)
Luo, L., Cheng, C.- S., Mobley, M., Novoselac, A., Lieberknecht, K., Leite, F. (2024). Scenario Generation for Built Environment Decision Support Under Uncertainty: Case Studies on Energy Modeling and Climate-resilient Infrastructure System Design. (in revision)
Cheng, C.- S., Behzadan, A. H., Noshadravan, A. (2024). A Post-Hurricane Debris Estimation Workflow Enabled by Uncertainty-aware AI and Crowdsourcing. https://doi.org/10.1016/j.ijdrr.2024.104785
Cheng, C.- S., Luo, L., Murphy, S., Lee, Y.-C., Leite, F. (2024). A Framework to Enhance Disaster Debris Estimation with AI and Aerial Photogrammetry. International Journal of Disaster Risk Reduction. https://doi.org/10.1016/j.ijdrr.2024.104468
Cheng, C.- S., Khajwal, A. B., Behzadan, A. H., Noshadravan, A. (2023). A probabilistic crowd-AI framework for reducing uncertainty in post-disaster building damage assessment. Journal of Engineering Mechanics. https://doi.org/10.1061/JENMDT.EMENG-6992. (2022 EMI Student Paper Competition Award, Featured in Editor's Choice)
Khajwal, A. B., Cheng, C.- S., Noshadravan, A. (2023). Post-disaster damage classification based on deep multi-view image fusion. Computer‐Aided Civil and Infrastructure Engineering. 38(4), 528-544. https://doi.org/10.1111/mice.12890
Cheng, C.- S., Behzadan, A. H., Noshadravan, A. (2022). Uncertainty-aware convolutional neural network for explainable AI-assisted disaster damage assessment. Structural Control and Health Monitoring. 29(10), e3019. https://doi.org/10.1002/stc.3019
Nath, N. D., Cheng, C.- S., & Behzadan, A. H. (2022). Drone Mapping of Damage Information in GPS-Denied Disaster Sites. Advanced Engineering Informatics. 51, 101450. https://doi.org/10.1016/j.aei.2021.101450
Cheng, C.- S., Behzadan, A. H., Noshadravan, A. (2021). Deep Learning for Post-Hurricane Aerial Damage Assessment of Buildings. Computer‐Aided Civil and Infrastructure Engineering. 36(6), 695-710. https://doi.org/10.1111/mice.12658 (2022 Top Downloaded Article)
Chan, P.-T., Cheng, C.-S., & Leu, L.-J. (2016). Optimal Design of Viscous Dampers for Two and Three-Dimensional Building Structures. Structural Engineering, 31(4), 57-65. https://dx.doi.org/10.6849/SE.201612_31(4).0004
PEER-REVIEWED CONFERENCE PROCEEDINGS
Cheng, C.- S., Pi, Y., Lomax, T., Duffield, N. & Behzadan, A. H. (June 2023). Pedestrian Phone-related Distracted Behavior Classification in Front-facing Vehicle Cameras for Road User Safety. ASCE 2023 International Conference on Computing in Civil Engineering (I3CE 2023). https://ascelibrary.org/doi/abs/10.1061/9780784485248.050
Cheng, C.- S., & Behzadan, A. H, Noshadravan, A. (June 2023). Rapid and Automated Vision-based Post-disaster Debris Estimation. ASCE 2023 International Conference on Computing in Civil Engineering (I3CE 2023). https://ascelibrary.org/doi/abs/10.1061/9780784485248.008
Nath, N. D., Cheng, C.- S., & Behzadan, A. H. (July 2022). Reinforcement Learning for Active Monitoring of Moving Equipment in 360-Degree Videos. EG-ICE 2022 International Workshop on Computing in Engineering. https://doi.org/10.7146/aul.455.c204
Cheng, C.- S., Behzadan, A. H., & Noshadravan, A. (June 2022). A Bayesian Framework for Human-AI Partnership in Disaster Damage Classification. 8th World Conference on Structural Control and Monitoring (8WCSCM) Presentation
Khajwal, A. B., Cheng, C.- S., Noshadravan, A. (June 2022) An uncertainty-aware multi-view approach to automated post-disaster damage assessment. 8th World Conference on Structural Control and Monitoring (8WCSCM)
Khajwal, A. B., Cheng, C.- S., Noshadravan, A. (Mar. 2022) Multi-view deep learning for reliable post-disaster damage classification. 13th International Workshop on Structure Health Monitoring (IWSHM) https://doi.org/10.48550/arXiv.2208.03419
Cheng, C.- S., Behzadan, A. H., & Noshadravan, A. (Feb. 2022). Exploring the Generalizability of Deep Convolutional Neural Networks for Post-Hurricane Damage Assessment. ASCE/IRD UCLA Lifelines 2021-22 Conference https://doi.org/10.1061/9780784484449.051 Presentation
Cheng, C.- S., Behzadan, A. H., & Noshadravan, A. (Sep. 12-14, 2021). Bayesian Inference for Uncertainty-aware Post-disaster Damage Assessment using Artificial Intelligence. ASCE 2021 International Conference on Computing in Civil Engineering (I3CE 2021). DOI: https://doi.org/10.1061/9780784483893.020
DATA PUBLICATIONS
Kajwal, A. B., Tomotaki L., Cheng, C.- S. & Noshadravan, A. (2022). MV-HarveyNET: A labeled image dataset from Hurricane Harvey for damage assessment of residential houses based on multi-view CNN. DesignSafe-CI. DOI: https://doi.org/10.17603/ds2-wzac-h261
Cheng, C.- S., Behzadan, A. H., & Noshadravan, A. (2021). DoriaNET: A Visual Dataset from Hurricane Dorian for Post-disaster Building Damage Assessment. DesignSafe-CI. DOI: https://doi.org/10.17603/ds2-gqvg-qx37
CONFERENCE PARTICIPATIONS
Cheng, C.- S., Behzadan, A. H., & Noshadravan, A. (May 2022). Hybrid crowd-AI probabilistic framework to reduce uncertainty in post-disaster damage assessment. Engineering Mechanics Institute (EMI) Conference and Probabilistic Mechanics & Reliability Conference
Khajwal, A. B., Cheng, C.- S., Noshadravan, A. (Sep. 2021) A novel automated post-disaster damage assessment based on multi-view imagery. Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering & Technology (MMLDT-CSET). DOI: https://doi.org/10.26226/morressier.612f6737bc981037241008a5
Cheng, C.- S., Behzadan, A. H., & Noshadravan, A. (May. 2021). Reliable Post-disaster Damage Assessment using Deep Learning with Uncertainty Quantification. Engineering Mechanics Institute (EMI) Conference and Probabilistic Mechanics & Reliability Conference (virtual conference) Presentation
Cheng, C.- S., Behzadan, A. H., & Noshadravan, A. (Feb. 2021). Enabling Reliable AI-based Post-disaster Damage Assessment Using Aerial Imagery. IMAC XXXIX Conference, Feb 8-11 (virtual conference) Presentation
Chan, P.-T., Huang, C.-F., Cheng, C.-S. and Leu, L.-J. (2016). Optimal Design of Viscous Dampers for Two-Dimensional Building Structures. Proceedings of the 29th KKHTCNN Symposium on Civil Engineering, December 3-5, Hong Kong.
Chan, P.-T., Cheng, C.-S., Leu, L.-J. (2016). Optimal Design of Viscous Dampers for Two and Three-Dimensional Building Structures. Proceedings of the 13th National Conference on Structural Engineering/3rd National Conference on Earthquake Engineering, Taipei, Taiwan
POSTERS PRESENTATION
Cheng, C.- S., Behzadan, A. H., & Noshadravan, A. (May. 2022). Uncertainty-aware Deep Learning for Explainable Post-disaster Damage Assessment. 5th Annual Texas A&M Research Computing Symposium. Link
Cheng, C.- S., Behzadan, A. H., & Noshadravan, A. (Nov. 2021). Uncertainty-aware Deep Learning for Post-disaster Building Damage Assessment Using Remote Sensing. Graduate Student Poster Session at Texas Texas A&M University Link
THESES AND DISSERTATIONS
Cheng, C.- S., (May 2023). Post-Disaster Damage Assessment with Artificial Intelligence and Uncertainty Quantification. Doctoral Dissertation, Zachry Department of Civil and Environmental Engineering, Texas A&M University.
Cheng, C.- S., (Jul. 2015). Optimal Design of Viscous Dampers for Building Structures. M.S. Thesis, Department of Civil Engineering, National Taiwan University. DOI: https://doi.org/10.6342/NTU.2015.02176