Journal Publications
| Brennan DS, Gosliga J, Gardner P, Mills RS, Worden K. (2022). On the application of population-based structural health monitoring in aerospace engineering. https://doi.org/10.3389/frobt.2022.840058 |
| Ferguson A, Woods R, Hester D. (2022). Detecting Vehicle Loading Events in Bridge Rotation Data Measured with Multi-Axial Accelerometers. Sensors, https://doi.org/10.3390/s221349947 |
| Wang M, Kei Ao W, Bownjohn J, Xu F. (2022). Completely non-contact modal testing of full-scale bridge in challenging conditions using vision sensing systems. Engineering Structures https://doi.org/10.1016/j.engstruct.2022.114994 |
| Haywood-Alexander, M., Dervilis, N., Worden, K., Mills, R. S., Ladpli, P., & Rogers, T. J. (2023). A Bayesian Method for Material Identification of Composite Plates via Dispersion Curves. Sensors, 23(1), 185. https://doi.org/10.3390/s23010185 |
| Poole J, Gardner P, Dervilis N, Bull L, Worden K. On statistic alignment for domain adaptation in structural health monitoring. Structural Health Monitoring. 2023;22(3):1581-1600. https://doi.org/10.1177/14759217221110 |
| Duffin, C., Branson, P., Rayson, M., Girolami, M., Cripps, E. and Stemler, T., 2023. Exploring Model Misspecification in Statistical Finite Elements via Shallow Water Equations. https://doi.org/10.1016/j.ymssp.2023.110554 |
| Bunce, A., Hester, D., Taylor, S., Brownjohn, J., Huseynov, F., & Xu, Y. (2023). A robust approach to calculating bridge displacements from unfiltered accelerations for highway and railway bridges. Mechanical Systems and Signal Processing, 200, Article 110554. https://doi.org/10.1016/j.ymssp.2023.110554 |
| O’Higgins, C.; Hester, D.; McGetrick, P.; Cross, E.J.; Ao, W.K.; Brownjohn, J. Minimal Information Data-Modelling (MID) and an Easily Implementable Low-Cost SHM System for Use on a Short-Span Bridge. Sensors 2023, 23, 6328. https://doi.org/10.3390/s23146328 |
| Bull, Lawrence A. , Matthew R. Jones, Elizabeth J. Cross, Andrew Duncan, Mark Girolami (2023). Encoding Domain Expertise into Multilevel Models for Source Location https://arxiv.org/abs/2305.08657. DCE |
| Hughes, A.J., Poole, J., Dervilis, N., Gardner, P. and Worden, K., (2023). A decision framework for selecting information-transfer strategies in population-based SHM. arXiv preprint https://arxiv.org/abs/2307.06978 |
| Clarkson D, Bull L, Dardeno T, Wickramarachchi C, Cross E, Rogers T, … Hughes A. (2023). Sharing Information Between Machine Tools to Improve Surface Finish Forecasting. https://doi.org/10.48550/arXiv.2310.05807 |
| Papatheou E., Tatsis K., Agathos K., Haywood-Alexander M., Dervilis N., Worden K. (2023). On the Use of Model-Based Versus Data-Based Approaches for Virtual Sensing in SHM. https://api.elsevier.com/content/abstract/scopus_id/85182275033 |
| Tsialiamanis G, Dervilis N, Wagg D, Worden K. (2023). Towards a population-informed approach to the definition of data-driven models for structural dynamics. Mechanical Systems and Signal Processing, https://doi.org/10.48550/arXiv.2307.09862 |
| Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Ömer Deniz Akyildiz (2023). Random Grid Neural Processes for Parametric Partial Differential Equations https://doi.org/10.48550/arXiv.2301.11040 |
| Aidan J. Hughes, Paul Gardner, Keith Worden (2023). Towards risk-informed PBSHM: Populations as hierarchical systems. https://doi.org/10.48550/arXiv.2303.13533 |
| Alex Glyn-Davies, Connor Duffin, O. Deniz Akyildiz, Mark Girolami, Φ-DVAE: Physics-informed dynamical variational autoencoders for unstructured data assimilation, Journal of Computational Physics, Volume 515, 2024, 113293, ISSN 0021-9991, https://doi.org/10.1016/j.jcp.2024.113293. |
| Sarah Bee, Lawrence Bull, Nikolas Dervilis, Keith Worden. (2023). When is an SHM problem a Multi-Task-Learning problem? https://doi.org/10.48550/arXiv.2305.09425 |
| S Bee, J Poole, K Worden, N Dervilis, LA Bull. Better Together: Using Multi-Task Learning to Improve Feature Selection Within Structural Datasets. In: Madarshahian, R., Hemez, F. (eds) Data Science in Engineering, Volume 10. SEM 2023. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-031-34946-1_7 |
| Tsialiamanis G, Dervilis N, Wagg D, Worden K. (2023). A Meta-Learning Approach to Population-Based Modelling of Structures. Data Science in Engineering, https://doi.org/10.48550/arXiv.2302.07980 |
| Poole, Jack and Worden, Keith and Dervilis, Nikolaos and Giglioni, Valentina and Mills, Robin S. and Gardner, Paul and Hughes, Aidan J., Active Transfer Learning for Structural Health Monitoring. http://dx.doi.org/10.2139/ssrn.5195127 |
| Wickramarachchi, C., Gosliga, J., Bunce, A., Brennan, D.S., Hester, D., Cross, E.J., Worden, K., 2023. Similarity assessment of structures for population-based structural health monitoring via graph kernels. Submitted to Structural Health Monitoring. https://doi.org/10.1177/14759217241265626 |
| Stihi, Alexandru , Timothy J. Rogers, Claudia Mazza, Elizabeth J. Cross (2023). On gait consistency quantification through ARX residual modelling and kernel two-sample testing. IEEE Transactions on Biomedical Engineering. IEEE Trans Biomed Eng. 2024 Mar;71(3):720-731.. Epub 2024 Feb 26. doi.org/10.1109/TBME.2023.3316474 |
| Andrew Bunce, David Hester, Su Taylor, James Brownjohn, Farhad Huseynov, Yan Xu, A robust approach to calculating bridge displacements from unfiltered accelerations for highway and railway bridges, Mechanical Systems and Signal Processing, Volume 200, 2023, 110554, ISSN 0888-3270, https://doi.org/10.1016/j.ymssp.2023.110554. |
| Brennan, D.S., Gosliga, J., Cross, E.J., Worden, K., 2023. Foundations of Population-based SHM, Part V: Network, Framework and Database. Submitted to Mechanical Systems and Signal Processing. https://doi.org/10.1016/j.ymssp.2024.111602 |
| Bee S, Poole J, Worden K, Dervilis N, Bull L. Multitask feature selection within structural datasets. Data-Centric Engineering. 2024;5:e4. https://doi.org/10.1017/dce.2024.1 |
| Ferguson A, Hester D, Woods R. (2024). A Systematic Approach to Filter Specification for Measuring Quasi-Static Bridge Rotation Under Moving Loads Using DC Accelerometers https://doi.org/10.1109/ACCESS.2024.3396060 |
| Bull L, Jeon C, Girolami M, Duncan A, Schooling J, Haro M. Towards Multilevel Modelling of train passing events on the Staffordshire bridge DOI.org/10.12783/shm2023/37066 |
| O’Higgins, C., Hester, D., Ao, W. K., & McGetrick, P. (2024). A method to maximise the information obtained from low signal-to-noise acceleration data by optimising SSI-COV input parameters. Journal of Sound and Vibration, 571, 118101. 2024 https://doi.org/10.1016/j.jsv.2023.118101 |
| Wang, M.; Xu, F.; Koo, K.; Wang, P (2024).Real-time displacement measurement for long-span bridges using a compact vision-based system with speed-optimized template matching. Computer-Aided Civil and Infrastructure Engineering. https://onlinelibrary.wiley.com/doi/10.1111/mice.13177 |
| Ferguson A, O’Higgins C, Hester D, Woods R. (2024). Sampling methods based on expected traffic-volume information for long-term rotation-based bridge SHM in resource-constrained environments. Mechanical Systems and Signal Processing doi.org/10.1016/j.ymssp.2023.110933 |
| Dardeno, T.A. , K. Worden, N. Dervilis, R.S. Mills, L.A. Bull, On the hierarchical Bayesian modelling of frequency response functions, Mechanical Systems and Signal Processing, Volume 208, 2024, 111072, ISSN 0888-3270, https://doi.org/10.1016/j.ymssp.2023.111072. |
| Connor O’Higgins, David Hester, Wai Kei Ao, Patrick McGetrick. ‘A method to maximise the information obtained from low signal-to-noise acceleration data by optimising SSI-COV input parameters’, Journal of Sound and Vibration, Volume 571, 2024, doi.org/10.1016/j.jsv.2023.118101 |
| Tsialiamanis G, Sbarufatti C, Dervilis N, Worden K. (2024). On a meta-learning population-based approach to damage prognosis. Mechanical Systems and Signal Processing 10.1016/j.ymssp.2024.111119 |
| Bunce A., D. S. Brennan, A. Ferguson, C. O’Higgins, S. Taylor, E. J. Cross, K. Worden, J. Brownjohn, D. Hester. ‘On population-based structural health monitoring for bridges: Comparing similarity metrics and dynamic responses between sets of bridges’, Mechanical Systems and Signal Processing, Volume 216, 2024, https://doi.org/10.1016/j.ymssp.2024.111501. |
| Binbin Li, Peixiang Wang, Zuo Zhu, Zhi Li, Yan Xiao. Ambient vibration test and re-test of a multistory factory building. Journal of Performance of Constructed Facilities. https://doi.org/10.1061/JPCFEV.CFENG-46 |
| Pias, M., Bull, L.A., Brennan, D.S., Girolami, M., Crowcroft, J., 2024. On the Scaling of Digital Twins by Aggregation. Data & Policy. doi.org/10.1017/dap.2024.86 |
| Simon M. Brealy, Aidan J. Hughes, Tina A. Dardeno, Lawrence A. Bull,Robin S. Mills, Nikolaos Dervilis, Keith Worden 2024. Multitask learning for improved scour detection: A dynamic wavetank study. doi.org/10.48550/arXiv.2408.16527 |
| Alex Glyn-Davies, Connor Duffin, O. Deniz Akyildiz, Mark Girolami, Φ-DVAE: Physics-informed dynamical variational autoencoders for unstructured data assimilation, Journal of Computational Physics,Volume 515,2024,113293, ISSN 0021-9991, https://doi.org/10.1016/j.jcp.2024.113293 |
| O’Higgins, C., Hester, D., McGetrick, P., Ao, W. K., & Cross, E. J. (2024). Refinement and Validation of the Minimal Information Data-Modelling (MID) Method for Bridge Management. Sensors, 24(12), 3879. https://doi.org/10.3390/s24123879 |
| Valentina Giglioni, Jack Poole, Ilaria Venanzi, Filippo Ubertini, Keith Worden, A domain adaptation approach to damage classification with an application to bridge monitoring, Mechanical Systems and Signal Processing, Volume 209, 2024, 111135, ISSN 0888-3270, https://doi.org/10.1016/j.ymssp.2024.111135. |
| Dardeno, T., Bull, L., Dervilis, N., & Worden, K. (2024). Transfer learning via intermediate structures. Proceedings of the 10th European Workshop on Structural Health Monitoring (EWSHM 2024), June 10-13, 2024 in Potsdam, Germany. e-Journal of Nondestructive Testing Vol. 29(7). https://doi.org/10.58286/29727Testing. 11th European Workshop on Structural Health Monitoring (EWSHM 2024), 10-13 1https://doi.org/10.58286/29727Testing. |
| Clarkson, Daniel & Bull, Lawrence & Dardeno, Tina & Wickramarachchi, Chandula & Cross, Elizabeth & Rogers, Timothy & Worden, Keith & Dervilis, Nikolaos & Hughes, Aidan. (2024). A spin on active learning analysis for health monitoring.. e-Journal of Nondestructive Testing. doi.org/29. 10.58286/29629. |
| Valentina Giglioni, Jack Poole, Robin Mills, Ilaria Venanzi, Filippo Ubertini, Keith Worden, On the application of domain adaptation for knowledge transfer and damage detection across bridge spans: an experimental case study, Procedia Structural Integrity, Volume 62, 2024, Pages 887-894,ISSN 2452-3216, https://doi.org/10.1016/j.prostr.2024.09.119. |
| Kamariotis A, Chatzi E, Straub D, et al. Monitoring-supported value generation for managing structures and infrastructure systems. Data-Centric Engineering. 2024;5:e27. doi.org/10.1017/dce.2024.24 |
| Bull LA, Jones MR, Cross EJ, Duncan A, Girolami M. Meta-models for transfer learning in source localization. Data-Centric Engineering. 2024;5:e48. doi.org/10.1017/dce.2024.43 |
| Max Champneys, Gerben I. Beintema, R. Tóth, Maarten Schoukens, Timothy J. Rogers, Baseline Results for Selected Nonlinear System Identification Benchmarks, IFAC-PapersOnLine, Volume 58, Issue 15, 2024, Pages 474-479, ISSN 2405-8963, https://doi.org/10.1016/j.ifacol.2024.08.574. |
| Poole, J., Hughes, A., Gardner, P., Bull, L., Dervilis, N., Giglioni, V., Mills, R., & Worden, K. (2024). Active transfer learning for SHM of bridges under changing environmental conditions. Proceedings of the 10th European Workshop on Structural Health Monitoring (EWSHM 2024), June 10-13, 2024 in Potsdam, Germany. e-Journal of Nondestructive Testing Vol. 29(7). https://doi.org/10.58286/29818 |
| Tom R. WINDUS-SMITH, Keith WORDEN, Timothy J. ROGERS. (2024). On Preserving Privacy in Structural Health. 11th European Workshop on Structural Health Monitoring https://doi.org/10.58286/29730 |
| Yanping Yang, Zuo Zhu, Siu-Kui Au. Tracking time-varying properties using quasi time-invariant models with Bayesian dynamic programming. https://doi.org/10.1016/j.ymssp.2024.111546 |
| Brennan, D.S., Rogers, T.J., Cross, E.J., Worden, K., 2024. On calculating structural similarity metrics in population-based structural health monitoring. Submitted to Data Centric Engineering. doi.org/doi:10.1017/dce.2024.45 |
| Champneys, M. D., & Rogers, T. J. BINDy–Bayesian identification of nonlinear dynamics with reversible-jump Markov-chain Monte-Carlo. 2024. Proceedings of the Royal Society A https://doi.org/10.48550/arXiv.2408.08062 |
| Longbottom, J. D., Champneys, M. D., & Rogers, T. J. (2024). Probabilistic-Numeric SMC Sampling for Bayesian Nonlinear System Identification in Continuous Time. https://doi.org/10.48550/arXiv.2404.12923 |
| Giulia Delo, Rinto Roy, Keith Worden, Cecilia Surace, On the use of the inverse finite element method to enhance knowledge sharing in population-based structural health monitoring, Computers & Structures, Volume 307, 2025, 107635, ISSN 0045-7949,https://doi.org/10.1016/j.compstruc.2024.107635. |
| Glyn-Davies, Alex, Arnaud Vadeboncoeur, O. Deniz Akyildiz, Ieva Kazlauskaite, and Mark Girolami. “A Primer on Variational Inference for Physics-Informed Deep Generative Modelling.” (2025) Philosophical Transactions of the Royal Society Part A https://doi.org/10.1098/rsta.2024.0324 |
| Akyildiz, O. Deniz, Mark Girolami, Andrew M. Stuart, and Arnaud Vadeboncoeur. “Efficient Prior Calibration From Indirect Data.” https://doi.org/10.48550/arXiv.2405.17955 may 2025. |
| D. S. Brennan, J. Gosliga, E. J. Cross, and K. Worden, ‘Foundations of population-based SHM, Part V: Network, framework and database’, Mechanical Systems and Signal Processing, vol. 223, p. 111602 doi.org/10.1016/j.ymssp.2024.111602 |
| Wilson, J., Champneys, M.D., Tipuric, M., Mills, R., Wagg, D.J. and Rogers, T.J., 2024. Multiple-input, multiple-output modal testing of a Hawk T1A aircraft: A new full-scale dataset for structural health monitoring. doi.org/10.48550/arXiv.2406.04943 |
| D. S. Brennan, T. J. Rogers, E. J. Cross, and K. Worden, ‘A comparison structural similarity metrics in population-based structural health monitoring’, Data Centric Engineering doi.org/10.12783/shm2023/36740 |
| M. Pias, L. A. Bull, D. S. Brennan, M. Girolami, and J. Crowcroft, ‘On the Scaling of Digital Twins by Aggregation’, Data & Policy, 2024. DOI.org/10.1017/dap.2024.86 |
| V. Giglioni, J. Poole, R. Mills, I. Venanzi, F. Ubertini, K. Worden, ‘Transfer Learning in Bridge Monitoring: Laboratory Study on Domain Adaptation for Population-Based SHM of Multispan Continuous Girder Bridges’, MSSP, 2024 https://doi.org/10.1016/j.ymssp.2024.112151 |
| Zhu, Z., Au, S. K., Brownjohn, J., Koo, K. Y., Nagayama, T., & Bassitt, J. (2025). Uncertainty quantification of modal properties of Rainbow Bridge from multiple-setup OMA data. Engineering Structures, 330, 119901.https://doi.org/10.1016/j.engstruct.2025.119901 |
| Daniel R. Clarkson, Lawrence A. Bull, Chandula T. Wickramarachchi, Elizabeth J. Cross, Timothy J. Rogers, Keith Worden, Nikolaos Dervilis, Aidan J. Hughes 2024, Active learning for regression in engineering populations: A risk-informed approach, arXiv preprint: https://doi.org/10.48550/arXiv.2409.04328 https://doi.org/10.1017/dce.2025.7 |
| Battu R, Agathos K, Londono-Monsalve J, Worden K, Papatheou E. (2024). Combining Transfer Learning and Numerical Modelling to Deal with the Lack of Training Data in Data-Based SHM. Journal of Sound and Vibration https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4674218 |
| C. R. Farrar, N. Dervilis, K. Worden (2025). The Past, Present and Future of Structural Health Monitoring: An Overview of Three Ages https://doi.org/10.1111/str.12495 |
| Giulia Delo, Rinto Roy, Keith Worden, Cecilia Surace, On the use of the inverse finite element method to enhance knowledge sharing in population-based structural health monitoring, Computers & Structures, Volume 307, 2025, 107635, ISSN 0045-7949, https://doi.org/10.1016/j.compstruc.2024.107635. |
| Poole, Jack, Keith Worden, Nikolaos Dervilis, Valentina Giglioni, Robin S. Mills, Paul Gardner, and Aidan J. Hughes. “Active Transfer Learning for Structural Health Monitoring.” (submitted) http://dx.doi.org/10.2139/ssrn.5195127 |
| Poole, Jack, Paul Gardner, Aidan J. Hughes, Nikolaos Dervilis, Tina Dardeno, Robin S. Mills, and Keith Worden. “Physics-Informed Transfer Learning for Shm Via Feature Selection.” http://dx.doi.org/10.2139/ssrn.5114348 |
| Arnaud Vadeboncoeur, Mark Girolami, Andrew M. Stuart. “Efficient Deconvolution in Populational Inverse Problems” arXivorg/2505.19841 |
| Duffin, C., Glyn-Davies, A., Vadeboncoeur, A., & Girolami, M. (2025). The statistical finite element method: A theoretical foundation for digital twins. https://doi.org/10.17863/CAM.117899, Accepeted at Quality Engineering |
| Wang, M.; Zhu, Z.; Koo, K.; Brownjohn, J. (2025).GNSS time-synchronised wireless vision sensor network for structural health monitoring. Journal of Civil Structural Health Monitoring. https://doi.org/10.1007/s13349-025-00953-7 |
| O’Connell, Brandon J., Max D. Champneys, and Timothy J. Rogers. 2025. Mechanical systems and signal processing https://doi.org/10.1016/j.ymssp.2025.112949 |
| Ferguson AJ, Hester D, Huseynov F, Kim CW, Brownjohn J, Woods R et al. On the normalisation and mapping of influence lines. Mechanical Systems and Signal Processing. https://doi.org/10.1016/j.ymssp.2025.112883 |
