Latest publications can be found on Google Scholar: https://scholar.google.com/citations?user=LSIBJwsAAAAJ&hl=en
Refereed Journal Papers (∗corresponding author)
*[J1]. Y Guo, C Wang∗, S Yu, F McKenna, K Law, AdaLN: A Vision Transformer for Multi-domain Learning and Pre-disaster Building Information Extraction from Images, Journal of Computing in Civil Engineering, 2022, https://doi.org/10.1061/(ASCE)CP.1943-5487.0001034
*[J2]. Wang, C.∗, Antos, S. E., & Triveno, L. M. Automatic detection of unreinforced masonry buildings from street view images using deep learning-based image segmentation. Automation in Construction, 2021, https://doi.org/10.1016/j.autcon.2021.103968
*[J3]. C. Wang∗, Q. Yu, K. Law, F. McKenna, S. Yu, E. Taciroglu, A. Zsarnóczay, W. Elhaddad, B. Cetiner, Machine Learning-based Regional Scale Intelligent Modeling of Building Information for Natural Hazard Risk Management, Automation in Construction, 2021, https://doi.org/10.1016/j.autcon.2020.103474
*[J4]. C. Wang∗, D. Wang, Q. Chen, Regional Evaluation of Liquefaction-Induced Lateral Ground Deformation for City-scale Transportation Resilience Analysis, Journal of Infrastructure Systems, 2021. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000601
*[J5]. Q. Yu, C. Wang∗, F. McKenna, et al, Rapid Visual Screening of Soft-Story Buildings from Street View Images Using Deep Learning Classification, Earthquake Engineering and Engineering Vibration, Special Issue, 2020. https://doi.org/10.1007/s11803-020-0598-2
*[J6]. Z. Lai, Q. Chen, C. Wang and X. Zhou, Modeling the wave-induced dynamic hydromechanical responses of heterogeneous porous seabed with embedded pipeline, Ocean Engineering, 2019. https://doi.org/10.1016/j.oceaneng.2019.01.015
*[J7]. C. Wang, and Q. Chen, A hybrid geotechnical and geologic data-based framework for multiscale regional liquefaction hazard mapping, Géotechnique, 2018. https://doi.org/10.1680/jgeot.17.P.074
*[J8]. C. Wang, Q. Chen, M. Shen and C. Hsein Juang, On the spatial variability of CPT-based geotechnical parameters for liquefaction potential evaluation, Soil Dynamics and Earthquake Engineering, 2017. https://doi.org/10.1016/j.soildyn.2017.02.001
*[J9]. W. Liu, Q. Chen, C. Wang, C.H. Juang and G. Chen, Spatially correlated multiscale Vs30 mapping and a case study of the Suzhou site, Engineering Geology, 2017. https://doi.org/10.1016/j.enggeo.2017.01.026
*[J10]. C.H. Juang, M. Shen, C. Wang, and Q. Chen, Random field-based liquefaction mapping - data inference and model verification using a synthetic digital soil field, Bulletin of Engineering Geology and the Environment, 2017. https://doi.org/10.1007/s10064-017-1071-y
*[J11]. Q. Chen, C. Wang and C.H. Juang, Probabilistic and spatial assessment of liquefaction-induced settlements through multiscale random field models, Engineering Geology, 2016. https://doi.org/10.1016/j.enggeo.2016.07.002
*[J12]. Q. Chen, C. Wang and C.H. Juang, CPT-based evaluation of liquefaction potential accounting for soil spatial variability at multiple scales, Journal of Geotechnical and Geoenvironmental Engineering, 2015. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001402
Refereed Conference Papers(∗corresponding author)
*[C1]. Q. Yu, C. Wang∗, B. Cetiner, S. X. Yu, F. McKenna, E. Taciroglu, K. H. Law, Building Information Modeling and Classification by Visual Learning at A City Scale, 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, 2019
*[C2]. C. Wang & D. Wang, Regional Evaluation of Liquefaction Induced Lateral Land Deformation and Its Application to an Urban Area, Best Paper, World Transportation Convention, Beijing, China, 2019
*[C3]. Q. Chen, C. Wang, Z. Lai, C.H. Juang, Integration of Heterogeneous Data for Multiscale Regional Liquefaction Settlement Mapping, 5th Geotechnical Earthquake Engineering And Soil Dynamics Conference, Austin, TX, 2018
*[C4]. C.H. Juang, Q. Chen, M. Shen, C. Wang, Keynote paper: Probabilistic Assessment and Mapping of Liquefaction Hazard: from Site-specific Analysis to Regional Mapping, GeoShanghai, 2018
*[C5]. Q. Chen, M. Shen, C. Wang and H. Huang, Validation of random field-based liquefaction model using synthetic digital soil fields, Geotechnical Frontiers 2017, Orlando, FL, March 12-15, 2017.
*[C6]. C. Wang, Q. Chen, C.H. Juang, Regional liquefaction mapping accounting for multiscale spatial variability of soil parameters with geological constraints, Geotechnical Risk from Theory to Practice, Denver, CO, June 4-7, 2017.
*[C7]. W. Liu, Q. Chen, G. Chen, C. Wang, C.H. Juang, Multiscale random field-based shear wave velocity mapping and site classification, Geotechnical Risk from Theory to Practice, Denver, CO, June 4-7, 2017.
*[C8]. Q. Chen, C. Wang, Z. Luo and C.H. Juang, Probabilistic evaluation of liquefaction-induced settlement mapping through multisacle random field models, Proceedings of the 6th Asia-Pacific Symposium on Structural Reliability and Its applications, Shanghai, China, 2016 .
*[C9]. C. Zhou, C. Wang, R. AI-Mahaidi and Y. Wang, Finite element analysis of beams bonded with end-anchored FRP straps, Fourth Asia-pacific conference on FRP in structures, 2013.
Presentations and Talks(∗presenter )
*[P1]. Q. Yu, C. Wang∗, B. Cetiner, S. X. Yu, F. McKenna, E. Taciroglu and K. H. Law. Two Case Studies of Building Modeling using Machine Learning, Artificial Intelligence for Humanitarian Assistance and Disaster Response Workshop at NeurIPS, Vancouver, Canada, 2019
*[P2]. C. Wang∗, et al, Creating city-scale building information model databases using AI, QuakeCoRE Annual Meeting, Nelson, New Zealand, 2019
*[P3]. W. Elhaddad, F. McKenna, M. Gardner, A. Zsarnóczay, M. Schoettler, C. Wang, S. Govindjee, G. Deierlein, A Computational Framework for Regional Earthquake Loss Estimation, Engineering Mechanics Institute Conference, Pasadena CA, 2019
*[P4]. C. Wang∗, et al, NHERI SimCenter: Vision & Collaboration, The PEER Annual Meeting, Los Angeles, CA, 2019
*[P5]. C. Wang∗, Q. Chen and H. Juang, Probabilistic assessment of regional liquefaction-induced settlement through multiscale random field models, Engineering Mechanics Institute Conference 2016 (EMI 2016) and the Probabilistic Mechanics & Reliability Conference 2016 (PMC 2016), Nashville, TN, May 22-25, 2016.