Publications

[10] Xu, L., Sejin Kim & Spence, S.M.J. (2025). Hybrid deep learning-enabled high-dimensional spatiotemporal flood emulation for coastal communities under hurricanes. (In Preparation)

[9] Xu, L., & Spence, S.M.J. (2025). A Stratified Multi-fidelity Framework with Adaptive Backpropagation Transfer Learning for Risk Assessment under Natural Hazards. (To be submitted to Reliability Engineering & System Safety)

[8] Xu, L., & Spence, S.M.J. (2025).  Adaptive Machine Learning-Driven Multi-Fidelity Stratified Sampling for Failure Analysis of Nonlinear Stochastic Systems. Structural Safety,  102673. (link)

[7] Xu, L., & Spence, S. M.J. (2025). Multiple stripe analysis for rapid failure probability analysis in support of performance-based wind engineering. Engineering Structures, 342, 120864. (link)

[6] Xu, L., & Spence, S.M.J. (2024). Collapse reliability of wind-excited reinforced concrete structures by stratified sampling and nonlinear dynamic analysis. Reliability Engineering & System Safety, 110244. (link)

[5] Xu, L., & Zhou, Z. (2022). Weighted Average Conditional Mean Spectrum (WACMS): A bridge between common CMS and Uniform Hazard Spectrum (UHS). Soil Dynamics and Earthquake Engineering, 156, 107238. (link)

[4] Xu, L., & Zhou, Z. (2022). Impact of target spectra variance of selected ground motions on seismic response of structures. Earthquakes & Structures, 23(2), 115-128. (link)

[3] Xu, L., & Zhou, Z. (2021). Application of Conditional Mean Spectrum on the super high-rise building in soft soil, Engineering Mechanics, 38(S). 228-236 (link) 

[2] Xu, L., Zhao, J., & Zhou, Z. (2020). Effects of characteristic parameters of isolation system on seismic response of isolated nuclear power plants. The Structural Design of Tall and Special Buildings, 29(3), e1697. (link)

[1] Zhou, Z., Xu, L., Sun, C., & Xue, S. (2018). Brazier effect of thin angle-section beams under bending. Sustainability, 10(9), 3047 (link)

[8] Xu, L., Kim, S. & Spence, S.M.J. (2026). A hybrid deep learning framework for regional-scale forecasting of hurricane-driven flood evolution. 8th International Symposium on Computational Wind Engineering. (Accepted) 

[7] Xu, L., & Spence, S.M.J. (2025). A multi-fidelity framework with adaptive transfer learning for risk assessment of structural systems subject to natural hazards. International Conference on Structural Safety and Reliability (ICOSSAR'25). (link)(Best Paper Award)

[6] Xu, L., & Spence, S.M.J. (2025). Adaptive multi-fidelity machine learning stratified sampling for efficient failure analysis of nonlinear dynamic systems, Engineering Mechanics Institute 2025 Conference (Paper Competition Winner) 

[5] Xu, L., & Spence, S.M.J. (2024). An adaptive surrogate-based multi-fidelity stratified sampling scheme for probabilistic analysis of nonlinear systems subject to stochastic excitation. Pacific Earthquake Engineering Research Center: 68. (link)

[4] Xu, L., & Spence, S.M.J. (2023).  Reliability assessment of reinforced concrete (RC) structures within the setting of performance-based wind engineering. 16th International Conference on Wind Engineering (ICWE16). (link)

[3] Xu, L., & Spence, S.M.J. (2023).  Collapse reliability of high-rise reinforced concrete systems subject to fully non-straight/-stationary hurricane representations.  14th International Conference on Application of Statistics and Probability in Civil Engineering (ICASP14) (link)(Best Paper Award)

[2] Xu, L., & Zhou, Z. (2021). Application of Conditional Mean Spectrum on the super high-rise building in soft soil, 29th National Structural Engineering Conference. (link) (Best Paper Award)

[1] Xu, L., & Zhou, Z. (2020). Response analysis of the super high-rise structure under dispersion-appropriate motions input. Proceedings of the fib Symposium: Concrete Structures for Resilient Society (link)

Note: Preseneter underlined

2026

[20] Xu, L., Kim, S. & Spence, S.M.J. (06/2026). A hybrid deep learning framework for regional-scale forecasting of hurricane-driven flood evolution. 8th International Symposium on Computational Wind Engineering, London, Canada.

[19] Xu, L., Kim S., & Spence, S.M.J. (06/2026). High-Dimensional Emulation of Hurricane-Driven Coastal Flood Evolution using Hybrid Neural Networks. Engineering Mechanics Institute Conference 2026, Boulder, CO. 

[18] Xu, L., & Spence, S.M.J. (06/2026). Transfer Learning-enabled Multi-fidelity Stratified Sampling for Rapid Failure Analysis of Nonlinear Stochastic Systems under Extreme Events, 9th International Conference on Computational Stochastic Mechanics, Corfu, Greece. 

2025

[17] Xu, L., Kim S., & Spence, S.M.J. (12/2025). Community-level Spatiotemporal Flooding Emulation using Convolutional and Recurrent Neural Networks. AGU25 Annual Meeting, New Orleans, LA. (selected as Oral Presentation) 

[16] Xu, L., & Spence, S.M.J. (06/2025). A multi-fidelity framework with adaptive transfer learning for risk assessment of structural systems subject to natural hazards. International Conference on Structural Safety and Reliability (ICOSSAR'25), Los Angeles, CA. (Best Paper Award)

[15] Xu, L., & Spence, S.M.J. (05/2025). Adaptive multi-fidelity machine learning stratified sampling for efficient failure analysis of nonlinear dynamic systems, Engineering Mechanics Institute 2025 Conference (EMI 2025), Anaheim, CA. (Paper Competition Winner)

[14] Xu, L., & Spence, S.M.J. (02/2025). Metamodeling of High-Dimensional Nonlinear Stochastic Systems through Autoencoders and LSTM Networks.  Simcenter NHERI Computational Symposium, Los Angeles, CA.

2024

[13] Xu, L., & Spence, S.M.J. (08/2024). An adaptive surrogate-based multi-fidelity stratified sampling scheme for probabilistic analysis of nonlinear systems subject to stochastic excitation. IFIP WG7.5 Working Group Conference, Berkeley, CA.

[12] Xu, L., & Spence, S.M.J. (06/2024). Efficient reliability assessment of wind-excited nonlinear systems using adaptive multi-fidelity stratified sampling. 7th AAWE Workshop, Ann Arbor, MI. 

[11] Xu, L., & Spence, S.M.J. (05/2024). An adaptive surrogate-based Multi-fidelity Monte Carlo scheme for probabilistic analysis of nonlinear systems subject to stochastic excitation. Engineering Mechanics Institute Conference and Probabilistic Mechanics & Reliability Conference (EMI/PMC), Chicago, IL. 

[10] Xu, L., & Spence, S.M.J. (04/2024). An adaptive surrogate-based Multi-fidelity Monte Carlo scheme for reliability analysis of nonlinear systems against natural hazards​. MICDE Conference on Scientific Foundation Models, Ann Arbor, MI.  (Poster Competition Winner)

[9] Xu, L., & Spence, S.M.J. (02/2024).  A Deep Learning-based Multi-Fidelity Monte Carlo (DL-MFMC) scheme for efficient reliability analysis of nonlinear structural systems subject to natural hazards. Simcenter NHERI Computational Symposium, Los Angeles, CA. (delivered in the Plenary session)

2023

[8] Xu, L., & Spence, S.M.J. (09/2023).  Reliability assessment of reinforced concrete (RC) structures within the setting of performance-based wind engineering. 16th International Conference on Wind Engineering (ICWE), Florence, Italy. 

[7] Xu, L., & Spence, S.M.J. (07/2023).  Collapse reliability of high-rise reinforced concrete systems subject to fully non-straight/-stationary hurricane representations.  14th International Conference on Application of Statistics and Probability in Civil Engineering (ICASP), Dublin, Ireland.  (link) (CERRA Student Recognition Award)

[6] Xu, L., Arunachalam, & S., Spence, S.M.J. (05/2023).  A Multi-fidelity Bayesian-based framework for collapse reliability analysis under hurricane hazards.  Engineering Mechanics Institute Conference (EMI), Atlanta,  GA. 

[5] Xu, L., & Spence, S.M.J. (03/2023) Inelastic modeling and failure analysis of high-rise reinforced concrete structures under extreme winds. Structure Congress, New Orleans, LA. 

2022 and Earlier

[4] Xu, L., & Spence, S.M.J. (06/2022). Collapse reliability analysis of high-rise reinforced concrete structures under extreme winds. Engineering Mechanics Institute Conference (EMI), Baltimore, MD.

[3] Xu, L., & Zhou, Z. (11/2020). Response analysis of the super high-rise structure under dispersion-appropriate motions input. Proceedings of the fib Symposium: Concrete Structures for Resilient Society, Shanghai, China. 

[2] Xu, L., & Zhou, Z. (10/2020). Application of Conditional Mean Spectrum on the super high-rise building in soft soil. 29th National Structural Engineering Conference, Wuhan, China. (Best Paper Award)

[1] Xu, L., & Zhou, Z. (08/2019). Study on characteristic parameters of isolation system on seismic response of isolated nuclear power plants. Joint Workshop on Structural Disaster Mitigation and Safety Assessment, Tokyo, Japan.

[7] Advancing AI-Driven Probabilistic Modeling and Assessment of Civil Infrastructure under Natural Hazards. NHERI GSC General Meeting, (02/2026), online 

[6] Towards Disaster-Resilient Civil Infrastructure: An AI-Enhanced Computational Perspective. Invited Seminar at Department of Civil & Environmental Engineering (05/2025), UC Irvine, CA. 

[5] Advancing Wind Resilience of Civil Infrastructure: An AI-Enhanced Computational Perspective. Invited Seminar at Department of Civil Engineering (05/2025), UT Arlington, TX. 

[4] Transfer Learning-enabled Multi-Fidelity Scheme for Risk Assessment under Natural Hazards. Rising Stars Workshop in Computational and Data Sciences (04/2025), Oden Institute, UT Austin, TX.

[3] Towards Disaster-Resilient Civil Infrastructure: An AI-Enhanced Computational Perspective. Invited Seminar at Department of Civil & Environmental Engineering (04/2025), Cornell University, Ithaca, NY. 

[2] Adaptive Deep Learning-Powered Multi-fidelity Stratified Sampling for Efficient Failure Analysis of Nonlinear Dynamic Systems. MICDE Scientific Computing Seminars (02/2025), Michigan Institute for Computational Discovery & Engineering, Ann Arbor, MI.

[1] Innovative frameworks for reliability assessment of high-rise RC systems against natural hazards. 10th Kwang-Hua Forum (11/2023), Tongji University, Shanghai, China.