Xuan Zhou is currently an Assistant Professor at the School of Aeronautic Science and Engineering, Beihang University. He obtained the Ph.D. degrees at Beihang University and Politecnico di Milano (Cum Laude). His research interests include structural integrity, airframe digital twins, structural health monitoring, and surrogate modeling. His research is supported by grants from the NSFC, MIIT, CPSF and BUAA, among others. He has published 22 articles in mainstream peer-reviewed journals of aeronautical and mechanical engineering, including the AIAA J (8 articles), MSSP, CMAME, CJA and AST. He has been recognized with several awards, including the Excellent Doctoral Dissertation Award from the Chinese Society of Aeronautics and Astronautics (awarded to 15 recipients annually), the Graduated with Honor of Beijing, and the ICCES 2023 Best Student Paper Award.

1. Selected Journal Article

[1] Zhou, X., He, S. *, Dong, L., & Atluri, S. N. (2022). Real-Time Prediction of Probabilistic Crack Growth with a Helicopter Component Digital Twin. AIAA Journal, 60(4), 2555–2567. 

[2] Zhou, X., Oboe, D., Poloni, D., Sbarufatti, C.*, & Dong, L.*, Giglio, M. (2023). Cluster-based Joint Distribution Adaptation Method for Debonding Quantification in Composite Structures. AIAA Journal, 61(2), 831–842.

[3] Zhou, X., Sbarufatti, C.*, Giglio, M., Dong, L.* & Atluri, S. N.. (2023). Copula-based Collaborative Multi-Structure Damage Diagnosis and Prognosis for Fleet Maintenance Digital Twins. AIAA Journal, 61(10),  4735-4740.

[4] Zhou, X., Dong, L.*, Dziendzikowski, M., Dragan, K., Giglio, M., and Sbarufatti, C.* (2025). Real-Time In-Service Load Tracking Toward Airframe Digital Twins. AIAA Journal, 63(12),5416-5429.

[5] Zhou, X., Sbarufatti, C.*, Giglio, M., & Dong, L.* (2023), A Fuzzy-set-based Joint Distribution Adaptation Method for Regression and its Application to Online Damage Quantification of a Structural Digital Twin. Mechanical Systems and Signal Processing, 191, 110164. 

[6] Xu, J., Zhou, X.*, Giglio, M., Sbarufatti, C., & Dong, L.* (2025), Variational Neural Network Embedded with Digital Twins for Probabilistic Structural Damage Quantification. AIAA Journal, 63(6), 2474-2486. 

[7] Zhao, F., Zhou, X.*, He, S., Wang, C., Dong, L.*, & Atluri, S. N. (2024), B-Spline Surface-Based Reduced-Order Modeling of Nonplanar Crack Growth in Structural Digital Twins. AIAA Journal, 62(1), 360-373. 

[8] Zhao, F., Zhou, X.*, Wang, C., Dong, L.*, & Atluri, S. N. (2023), Setting Adaptive Inspection Intervals in Helicopter Components, Based on a Digital-Twin. AIAA Journal, 61(6), 2675-2688. 

[9] Wang, C., Zhou, X.*, Liu, R., & Dong, L.* (2025), Parametric Symbolic Regression for Discovering Unified Crack Growth Models from Diverse Experiments. AIAA Journal, 63(12),5298-5312.

[10] Xu, J., Dai, D., Zhou, X.*, Giglio, M., Sbarufatti, C., & Dong, L.* (2026). Structural damage diagnosis and prognosis with fleet digital twin considering similarity of individual structural features. Aerospace Science and Technology, 168, 110983.

ResearchGate：https://www.researchgate.net/profile/Xuan-Zhou-16

Google Scholar：‪Xuan Zhou‬ - ‪Google Scholar