Dr Timothy Rogers
MEng, PhD
School of Mechanical, Aerospace and Civil Engineering
Senior Lecturer in Mechanical Engineering
tim.rogers@sheffield.ac.uk
+44 114 222 7820
+44 114 222 7820
Sir Frederick Mappin Building
Full contact details
Dr Timothy Rogers
School of Mechanical, Aerospace and Civil Engineering
Sir Frederick Mappin Building
Mappin Street
Sheffield
S1 3JD
School of Mechanical, Aerospace and Civil Engineering
Sir Frederick Mappin Building
Mappin Street
Sheffield
S1 3JD
- Profile
-
Dr Timothy Rogers is a lecturer in the Dynamics Research Group (DRG), part of the Department of Mechanical Engineering at The University of Sheffield.
He has completed both his MEng in Mechanical Engineering and his PhD at Sheffield, the title of which was "Towards Bayesian System Identifcation: With Application to SHM of Offshore Structures".
His work focusses on application of Machine Learning and Bayesian statistical methods to problems in structural dynamics in particular those within nonlinear system identification and Structural Health Monitoring (SHM).
- Research interests
-
Current research interests include:
- Machine learning for structural dynamics and Structural Health Monitoring
- Bayesian statistical modelling of structural systems
- Probabilistic nonlinear system identification
- Joint input/state/parameter identification
- Publications
-
Journal articles
- Machine-learning perspectives on Volterra system identification. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 383(2305).
- Hierarchical Gaussian processes for characterizing gait variability in multiple sclerosis. Data-Centric Engineering, 6. View this article in WRRO
- BINDy: Bayesian identification of nonlinear dynamics with reversible-jump Markov-chain Monte Carlo. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 481(2319). View this article in WRRO
- A new perspective on Bayesian operational modal analysis. Mechanical Systems and Signal Processing, 236. View this article in WRRO
- On calculating structural similarity metrics in population-based structural health monitoring. Data-Centric Engineering, 6. View this article in WRRO
- Active learning for regression in engineering populations: a risk-informed approach. Data-Centric Engineering, 6. View this article in WRRO
- Multiple-input, multiple-output modal testing of a Hawk T1A aircraft: a new full-scale dataset for structural health monitoring. Structural Health Monitoring. View this article in WRRO
- Towards nonlinear model predictive control of flexible structures using Gaussian Processes. Journal of Physics: Conference Series, 2909(1). View this article in WRRO
- Calibrating the discrete boundary conditions of a dynamic simulation: a combinatorial approximate Bayesian computation sequential Monte Carlo (ABC-SMC) approach. Sensors, 24(15). View this article in WRRO
- A Gaussian-process assisted model-form error estimation in multiple-degrees-of-freedom systems. Mechanical Systems and Signal Processing, 216, 111474-111474.
- Baseline Results for Selected Nonlinear System Identification Benchmarks. IFAC-PapersOnLine, 58(15), 474-479.
- Control of flexible structures using model predictive control and gaussian processes. Journal of Physics: Conference Series, 2647(3). View this article in WRRO
- Convolution models for output only linear structural system identification and the problem of identifiability. Journal of Physics: Conference Series, 2647(19). View this article in WRRO
- A spectrum of physics-informed Gaussian processes for regression in engineering. Data-Centric Engineering, 5(11). View this article in WRRO
- A robust probabilistic approach to stochastic subspace identification. Journal of Sound and Vibration, 581. View this article in WRRO
- A probabilistic approach for acoustic emission based monitoring techniques: with application to structural health monitoring. Mechanical Systems and Signal Processing, 208. View this article in WRRO
- Full-scale modal testing of a Hawk T1A aircraft for benchmarking vibration-based methods. Journal of Sound and Vibration, 576. View this article in WRRO
- On gait consistency quantification through ARX residual modeling and kernel two-sample testing. IEEE Transactions on Biomedical Engineering, 71(3), 720-731. View this article in WRRO
- Physically meaningful uncertainty quantification in probabilistic wind turbine power curve models as a damage-sensitive feature. Structural Health Monitoring, 22(6), 3623-3636. View this article in WRRO
- Distributions of fatigue damage from data-driven strain prediction using Gaussian process regression. Structural Health Monitoring.
- Resource-efficient machining through physics-informed machine learning. Procedia CIRP, 117, 347-352.
- Constraining Gaussian processes for physics-informed acoustic emission mapping. Mechanical Systems and Signal Processing, 188. View this article in WRRO
- A Bayesian method for material identification of composite plates via dispersion curves. Sensors, 23(1). View this article in WRRO
- On the dynamic properties of statistically-independent nonlinear normal modes. Mechanical Systems and Signal Processing, 181. View this article in WRRO
- Online damage detection of cutting tools using Dirichlet process mixture models. Mechanical Systems and Signal Processing, 180.
- A latent restoring force approach to nonlinear system identification. Mechanical Systems and Signal Processing, 180. View this article in WRRO
- A sampling-based approach for information-theoretic inspection management. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 478(2262). View this article in WRRO
- Informative bayesian tools for damage localisation by decomposition of Lamb wave signals. Journal of Sound and Vibration, 535.
- A Bayesian methodology for localising acoustic emission sources in complex structures. Mechanical Systems and Signal Processing, 163. View this article in WRRO
- Bayesian modelling of multivalued power curves from an operational wind farm. Mechanical Systems and Signal Processing, 169. View this article in WRRO
- Grey-box models for wave loading prediction. Mechanical Systems and Signal Processing, 159. View this article in WRRO
- A Latent Restoring Force Approach to Nonlinear System Identification.
- Structured machine learning tools for modelling characteristics of guided waves. Mechanical Systems and Signal Processing, 156. View this article in WRRO
- Learning model discrepancy: A Gaussian process and sampling-based approach. Mechanical Systems and Signal Processing, 152. View this article in WRRO
- Probabilistic inference for structural health monitoring: new modes of learning from data. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7(1). View this article in WRRO
- Foundations of population-based SHM, Part I : homogeneous populations and forms. Mechanical Systems and Signal Processing, 148. View this article in WRRO
- Equation discovery for nonlinear dynamical systems : a Bayesian viewpoint. Mechanical Systems and Signal Processing, 154. View this article in WRRO
- Autonomous ultrasonic inspection using bayesian optimisation and robust outlier analysis. Mechanical Systems and Signal Processing, 145. View this article in WRRO
- A brief introduction to recent developments in population-based structural health monitoring. Frontiers in Built Environment, 6. View this article in WRRO
- Bayesian joint input-state estimation for nonlinear systems. Vibration, 3(3), 281-303.
- On the application of Gaussian process latent force models for joint input-state-parameter estimation : With a view to Bayesian operational identification. Mechanical Systems and Signal Processing, 140. View this article in WRRO
- Probabilistic modelling of wind turbine power curves with application of heteroscedastic gaussian process regression. Renewable Energy, 148, 1124-1136. View this article in WRRO
- Probabilistic active learning : an online framework for structural health monitoring. Mechanical Systems and Signal Processing, 134. View this article in WRRO
- Sparse Gaussian Process Emulators for surrogate design modelling. Applied Mechanics and Materials, 885, 18-31. View this article in WRRO
- On evolutionary system identification with applications to nonlinear benchmarks. Mechanical Systems and Signal Processing, 112, 194-232. View this article in WRRO
- On the confidence bounds of Gaussian process NARX models and their higher-order frequency response functions. Mechanical Systems and Signal Processing, 104, 188-223. View this article in WRRO
- A spin on active learning analysis for health monitoring.. e-Journal of Nondestructive Testing, 29(7).
- A Bayesian non-parametric clustering approach for semi-supervised Structural Health Monitoring. Mechanical Systems and Signal Processing, 119, 100-119. View this article in WRRO
Book chapters
- Heteroscedastic Gaussian Processes for Localising Acoustic Emission, Data Science in Engineering, Volume 9 (pp. 185-197). River Publishers
- Investigating Engineering Data by Probabilistic Measures, Special Topics in Structural Dynamics & Experimental Techniques, Volume 5 (pp. 77-81). River Publishers
- State-of-the-Art and Future Directions for Predictive Modelling of Offshore Structure Dynamics Using Machine Learning, Dynamics of Civil Structures, Volume 2 (pp. 223-233). River Publishers
- Towards Physics-Based Metrics for Transfer Learning in Dynamics, Data Science in Engineering, Volume 10 (pp. 73-82). River Publishers
- Bayesian Solutions to State-Space Structural Identification, Model Validation and Uncertainty Quantification, Volume 3 (pp. 247-253). River Publishers
- An Evolutionary Approach to Learning Neural Networks for Structural Health Monitoring, Model Validation and Uncertainty Quantification, Volume 3 (pp. 237-246). River Publishers
- Predicting Tool Wear Using Linear Response Surface Methodology and Gaussian Process Regression, Topics in Modal Analysis & Testing, Volume 8 (pp. 283-286). River Publishers
- On Modelling Statistically Independent Nonlinear Normal Modes with Gaussian Process NARX Models, Nonlinear Structures & Systems, Volume 1 (pp. 135-147). River Publishers
- On improving the efficiency of Bayesian stochastic subspace identification In Rainieri C, Gentile C & Aenlle López M (Ed.), Proceedings of the 10th International Operational Modal Analysis Conference (IOMAC 2024): Volume 1 (pp. 609-617). Springer Nature Switzerland View this article in WRRO
- Multi-dataset OMA of a Sightseeing Tower with the New SpCF Method, Lecture Notes in Civil Engineering (pp. 652-662). Springer Nature Switzerland
- Data-Centric Monitoring of Wind Farms, Data Driven Methods for Civil Structural Health Monitoring and Resilience (pp. 120-180). CRC Press
- Physical Covariance Functions for Dynamic Systems with Time-Dependent Parameters, Lecture Notes in Civil Engineering (pp. 381-391). Springer International Publishing
- Bayesian Changepoint Modelling for Reference-Free Damage Detection with Acoustic Emission Data, Lecture Notes in Civil Engineering (pp. 462-471). Springer International Publishing
- Gaussian Processes, Computational Methods in Engineering & the Sciences (pp. 121-147). Springer International Publishing
- Artificial Neural Networks, Computational Methods in Engineering & the Sciences (pp. 85-119). Springer International Publishing
- Digital Transformation by the Implementation of the True Digital Twin Concept and Big Data Technology for Structural Integrity Management, Ageing and Life Extension of Offshore Facilities (pp. 143-157). ASME
- Physics-informed machine learning for structural health monitoring In Cury A, Ribeiro D, Ubertini F & Todd MD (Ed.), Structural Health Monitoring Based on Data Science Techniques (pp. 347-367). Springer Cham View this article in WRRO
- Partially Supervised Learning for Data-Driven Structural Health Monitoring, Structural Integrity (pp. 389-411). Springer International Publishing
- Structural Health Monitoring and Damage Identification, Handbook of Experimental Structural Dynamics (pp. 1-72). Springer New York
- Structural Health Monitoring and Damage Identification, Handbook of Experimental Structural Dynamics (pp. 989-1061). Springer New York
- Gaussian Process Based Grey-Box Modelling for SHM of Structures Under Fluctuating Environmental Conditions, Lecture Notes in Civil Engineering (pp. 55-66). Springer International Publishing
- New Modes of Inference for Probabilistic SHM, Lecture Notes in Civil Engineering (pp. 415-426). Springer International Publishing
- Structural Health Monitoring and Damage Identification, Handbook of Experimental Structural Dynamics (pp. 1-72). Springer New York
Conference proceedings
- A Gibbs sampler for removing environmental effects in structural health monitoring features. Proceedings of the 11th International Operational Modal Analysis Conference Iomac 2025 (pp 288-295)
- Exploring Physically Meaningful Prior Distributions for OMA. Proceedings of the 11th International Operational Modal Analysis Conference Iomac 2025 (pp 304-311)
- Calculating Structure Similarity via a Graph Neural Network in Population-Based Structural Health Monitoring: Part II (pp 151-158)
- Towards Exact Statistically Independent Nonlinear Normal Modes via the FPK Equation (pp 81-92)
- Identification of NonlinearWave Forces Using Gaussian Process NARX Models (pp 203-219)
- On a Grey Box Modelling Framework for Nonlinear System Identification (pp 167-178)
- On the Behaviour of Structures with Many Nonlinear Elements (pp 509-520)
- Bayesian grey-box identification of nonlinear convection effects in heat transfer dynamics. 2024 IEEE Conference on Control Technology and Applications (CCTA) (pp 382-387), 21 August 2024 - 23 August 2024.
- Review on research of uncertain dynamics for bimetallic structures. International Conference on Optoelectronic Information and Functional Materials (OIFM 2024) (pp 16-16), 19 April 2024 - 21 April 2024.
- Cost-informed dimensionality reduction for structural digital twin technologies. Proceedings of ISMA 2024 International Conference on Noise and Vibration Engineering and Usd 2024 International Conference on Uncertainty in Structural Dynamics (pp 4529-4542)
- An efficient reversible-jump MCMC scheme for model term selection in dynamic systems. Proceedings of ISMA 2024 International Conference on Noise and Vibration Engineering and Usd 2024 International Conference on Uncertainty in Structural Dynamics (pp 4422-4431)
- Using higher-order frequency response functions from NARX models to support activation function choices. Proceedings of ISMA 2024 International Conference on Noise and Vibration Engineering and Usd 2024 International Conference on Uncertainty in Structural Dynamics (pp 2294-2307)
- Mode indicator guided sequential modal analysis. Proceedings of ISMA 2024 International Conference on Noise and Vibration Engineering and Usd 2024 International Conference on Uncertainty in Structural Dynamics (pp 1012-1022)
- GP-NARX for active control of nonlinear flexible structures. Proceedings of ISMA 2024 International Conference on Noise and Vibration Engineering and Usd 2024 International Conference on Uncertainty in Structural Dynamics (pp 2239-2249)
- SHARING INFORMATION BETWEEN MACHINE TOOLS TO IMPROVE SURFACE FINISH FORECASTING. Proceedings of the 14th International Workshop on Structural Health Monitoring
- PHYSICS-INFORMED GAUSSIAN PROCESSES FOR WAVE LOADING PREDICTION. Proceedings of the 14th International Workshop on Structural Health Monitoring
- DETECTION, LOCALISATION, AND QUANTIFICATION OF BOLT LOOSENESS IN AN ALUMINIUM PLATE USING LAMB WAVE ANALYSIS. Proceedings of the 14th International Workshop on Structural Health Monitoring
- A novel variational Bayesian approach to stochastic subspace identification. Eccomas Proceedia, Vol. 19796 (pp 82-93). Athens, Greece, 12 June 2023 - 12 June 2023. View this article in WRRO
- APPROXIMATE BAYESIAN MODAL ANALYSIS WITH PARTICLE-SWARM PROPOSALS. UNCECOMP Proceedings
- CORRELATED GAUSSIAN PROCESS LATENT FORCE MODELS FOR RECOVERING MULTIPLE FORCES. UNCECOMP Proceedings
- CORRELATED GAUSSIAN PROCESS LATENT FORCE MODELS FOR RECOVERING MULTIPLE FORCES. Proceedings of the 5th International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019) (pp 1-10), 12 June 2023 - 14 June 2023.
- APPROXIMATE BAYESIAN MODAL ANALYSIS WITH PARTICLE-SWARM PROPOSALS. Proceedings of the 5th International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019) (pp 621-632), 12 June 2023 - 14 June 2023.
- Integrating Physical Knowledge into Gaussian Process Regression Models for Probabilistic Fatigue Assessment (pp 472-481)
- Physically-informed kernels for wave loading prediction. 11th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Vol. 2022 (pp 452-457). Montreal, Canada, 8 August 2022 - 8 August 2022. View this article in WRRO
- Robust probabilistic canonical correlations for stochastic subspace identification. Proceedings of the 9th International Operational Modal Analysis Conference (IOMAC) (pp 124-132). Vancouver, Canada, 3 July 2022 - 3 July 2022. View this article in WRRO
- A Bayesian approach to Lamb-wave dispersion curve material identification in composite plates. European Workshop on Structural Health Monitoring: EWSHM 2022, Vol. 3 (pp 139-149). Palermo, Italy, 4 July 2022 - 4 July 2022. View this article in WRRO
- Incorporation of partial physical knowledge within Gaussian processes. Proceedings of ISMA 2022 International Conference on Noise and Vibration Engineering and Usd 2022 International Conference on Uncertainty in Structural Dynamics (pp 4865-4877)
- Feedback control of flexible systems using Bayesian filtering. Proceedings of ISMA 2022 International Conference on Noise and Vibration Engineering and Usd 2022 International Conference on Uncertainty in Structural Dynamics (pp 4999-5010)
- OUTPUT-ONLY BAYESIAN SEMI-PARAMETRIC IDENTIFICATION OF A NONLINEAR DYNAMIC SYSTEM. 9th Iomac International Operational Modal Analysis Conference Proceedings (pp 156-164)
- Probabilistic numerical integration and sequential Monte Carlo for online identification of nonlinear dynamic systems. Proceedings of ISMA 2022 International Conference on Noise and Vibration Engineering and Usd 2022 International Conference on Uncertainty in Structural Dynamics (pp 4973-4984)
- Enhanced uncertainty quantification for acoustic emission localisation. Proceedings of ISMA 2022 International Conference on Noise and Vibration Engineering and Usd 2022 International Conference on Uncertainty in Structural Dynamics (pp 4890-4903)
- On higher-order frequency response functions from kernel-NARX methods. Proceedings of ISMA 2022 International Conference on Noise and Vibration Engineering and Usd 2022 International Conference on Uncertainty in Structural Dynamics (pp 2301-2315)
- Bayesian identification of material properties for a fibre-composite plate, via dispersion curves. Proceedings of ISMA 2022 International Conference on Noise and Vibration Engineering and Usd 2022 International Conference on Uncertainty in Structural Dynamics (pp 1866-1874)
- A nonparametric Bayesian approach for the detection of acoustic emission events in time series signals. Proceedings of ISMA 2022 International Conference on Noise and Vibration Engineering and Usd 2022 International Conference on Uncertainty in Structural Dynamics (pp 4777-4787)
- On quantifying the similarity of structures via a Graph Neural Network for population-based structural health monitoring. Proceedings of ISMA 2022 International Conference on Noise and Vibration Engineering and Usd 2022 International Conference on Uncertainty in Structural Dynamics (pp 3713-3721)
- Bayesian canonical correlations for stochastic subspace identification. Proceedings of ISMA 2022 International Conference on Noise and Vibration Engineering and Usd 2022 International Conference on Uncertainty in Structural Dynamics (pp 4904-4913)
- Constraining Gaussian processes for the inclusion of boundary conditions in physics-informed structural health monitoring. International Conference on Structural Health Monitoring of Intelligent Infrastructure Transferring Research into Practice Shmii, Vol. 2022-August (pp 445-451)
- On the application of variational auto encoders (VAE) for damage detection in rolling element bearings. Structural Health Monitoring 2021 : Proceedings of the Thirteenth International Workshop, August 31-September 2, 2021, Stanford University (pp 388-397). Lancaster, PA, USA, 15 March 2022 - 15 March 2022. View this article in WRRO
- Physics-derived covariance functions for machine learning in structural dynamics ⁎. IFAC-PapersOnLine, Vol. 54(7) (pp 168-173). Padova, Italy, 13 July 2021 - 16 July 2021.
- Decomposition of multi-mode signals using dispersion curves and Bayesian linear regression. Proceedings of SPIE: Health Monitoring of Structural and Biological Systems XV, Vol. 11593. Online, 22 March 2021 - 22 March 2021. View this article in WRRO
- Bayesian localisation of acoustic emission sources for wind turbine bearings. Health Monitoring of Structural and Biological Systems XV (pp 78-78), 22 March 2021 - 27 March 2021.
- Physics-derived covariance functions for machine learning in structural dynamics. IFAC PAPERSONLINE, Vol. 54(7) (pp 168-173)
- Nonlinear Gaussian process latent force models for input estimation in hysteretic systems. Uncecomp Proceedings, Vol. 2021-June
- Towards population-based structural health monitoring, part I : homogeneous populations and forms. Model Validation and Uncertainty Quantification, Volume 3 : Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics 2020 (pp 287-302). Houston, TX USA, 10 February 2020 - 10 February 2020. View this article in WRRO
- Modelling of guided waves in a composite plate through a combination of physical knowledge and regression analysis. Rotating Machinery, Optical Methods & Scanning LDV Methods: Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics 2020, Vol. 6 (pp 109-114). Houston, Texas, 10 February 2020 - 10 February 2020. View this article in WRRO
- On decision-making for adaptive models combining physics and data. Proceedings of ISMA 2020 - International Conference on Noise and Vibration Engineering and USD 2020 - International Conference on Uncertainty in Structural Dynamics (pp 3623-3637). Virtual Conference, Leuven, Belgium, 7 September 2020 - 7 September 2020. View this article in WRRO
- Lamb wave mode separation using dispersion curves. Proceedings of ISMA 2020 International Conference on Noise and Vibration Engineering and Usd 2020 International Conference on Uncertainty in Structural Dynamics (pp 2891-2898)
- Data-driven strain prediction models and fatigue damage accumulation. Proceedings of ISMA 2020 International Conference on Noise and Vibration Engineering and Usd 2020 International Conference on Uncertainty in Structural Dynamics (pp 3667-3675)
- Constraining Gaussian processes for grey-box acoustic emission source localisation. Proceedings of ISMA 2020 International Conference on Noise and Vibration Engineering and Usd 2020 International Conference on Uncertainty in Structural Dynamics (pp 2789-2800)
- On the application of Gaussian process latent force models for Bayesian identification of the Duffing system. Proceedings of ISMA 2020 International Conference on Noise and Vibration Engineering and Usd 2020 International Conference on Uncertainty in Structural Dynamics (pp 2141-2153)
- A spatiotemporal dual Kalman filter for the estimation of states and distributed inputs in dynamical systems. Proceedings of ISMA 2020 International Conference on Noise and Vibration Engineering and Usd 2020 International Conference on Uncertainty in Structural Dynamics (pp 3591-3597)
- A grey-box model for wave loading prediction with uncertainty propagation. Proceedings of ISMA 2020 International Conference on Noise and Vibration Engineering and Usd 2020 International Conference on Uncertainty in Structural Dynamics (pp 3611-3622)
- Identification of a Duffing oscillator using particle Gibbs with ancestor sampling. Journal of Physics: Conference Series, Vol. 1264. Valpre, Lyon, France, 15 April 2019 - 15 April 2019. View this article in WRRO
- A probabilistic framework for online structural health monitoring : active learning from machining data streams. Journal of Physics: Conference Series, Vol. 1264. Valpre, Lyon, France, 15 April 2019 - 15 April 2019. View this article in WRRO
- Learning of model discrepancy for structural dynamics applications using Bayesian history matching. Journal of Physics: Conference Series, Vol. 1264(1). Valpre, France, 15 April 2019 - 15 April 2019. View this article in WRRO
- A Gaussian process form for population-based structural health monitoring. Proceedings of the 13th International Conference on Damage Assessment of Structures. Porto, Portugal, 9 July 2019 - 9 July 2019. View this article in WRRO
- A nonlinear robust outlier detection approach for SHM. Proceedings of 8th International Operational Modal Analysis Conference (IOMAC 2019) (pp 107-114). Copenhagen, Denmark, 13 May 2019 - 13 May 2019. View this article in WRRO
- Machine learning for energy load forecasting. Journal of Physics: Conference Series, Vol. 1106(1). Cambridge, United Kingdom, 2 July 2018 - 2 July 2018. View this article in WRRO
- A semi-supervised bayesian non-parametric approach to damage detection. 9th European Workshop on Structural Health Monitoring Ewshm 2018
- A Bayesian filtering approach to operational modal analysis with recovery of forcing signals. Proceedings of ISMA 2018 International Conference on Noise and Vibration Engineering and Usd 2018 International Conference on Uncertainty in Structural Dynamics (pp 5181-5194)
- On Conserving Privacy in Structural Health Monitoring. e-Journal of Nondestructive Testing, Vol. 29(7)
- Output-only Identification of Loading and Modal Parameters in Dynamic Systems with Non-Gaussian Inputs. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- Online Damage State Clustering of Cutting Tools Using Dirichlet Process Mixture Models. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- Assessing the Likelihood of Damage at the Start of a Structural Health Monitoring Campaign. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- Grey-box Modelling for Structural Health Monitoring: Physical Constraints on Machine Learning Algorithms. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- Health Monitoring of Composite Structures by Combining Ultrasonic Wave Data. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- Clustering-based Crack Growth Characterisation using Synchronised Vibration and Acoustic Emission Measurements. Structural Health Monitoring 2017, 12 September 2017 - 14 September 2017.
- On the Choice of Optimisation Scheme for Gaussian Process Hyperparameters in SHM Problems. Structural Health Monitoring 2017, 12 September 2017 - 14 September 2017.
Preprints
- BINDy -- Bayesian identification of nonlinear dynamics with reversible-jump Markov-chain Monte-Carlo, arXiv.
- Cost-informed dimensionality reduction for structural digital twin technologies, arXiv.
- Active learning for regression in engineering populations: A risk-informed approach, arXiv.
- A new perspective on Bayesian Operational Modal Analysis, arXiv.
- Bayesian grey-box identification of nonlinear convection effects in heat transfer dynamics, arXiv.
- Multiple-input, multiple-output modal testing of a Hawk T1A aircraft: A new full-scale dataset for structural health monitoring, arXiv.
- Baseline Results for Selected Nonlinear System Identification Benchmarks, arXiv.
- Probabilistic Numeric SMC Sampling for Bayesian Nonlinear System Identification in Continuous Time, arXiv.
- Sharing Information Between Machine Tools to Improve Surface Finish Forecasting, arXiv.
- Full-scale modal testing of a Hawk T1A aircraft for benchmarking vibration-based methods, arXiv.
- A spectrum of physics-informed Gaussian processes for regression in engineering, arXiv.
- PAO: A general particle swarm algorithm with exact dynamics and closed-form transition densities, arXiv.
- Physically Meaningful Uncertainty Quantification in Probabilistic Wind Turbine Power Curve Models as a Damage Sensitive Feature, arXiv.
- Physics-informed machine learning for Structural Health Monitoring, arXiv.
- Constraining Gaussian processes for physics-informed acoustic emission mapping, arXiv.
- Informative Bayesian Tools for Damage Localisation by Decomposition of Lamb Wave Signals, arXiv.
- Bayesian Modelling of Multivalued Power Curves from an Operational Wind Farm, arXiv.
- Grey-box models for wave loading prediction, arXiv.
- Probabilistic Inference for Structural Health Monitoring: New Modes of Learning from Data, arXiv.
- Structured Machine Learning Tools for Modelling Characteristics of Guided Waves, arXiv.
- A Bayesian Method for Material Identification of Composite Plates Via Dispersion Curves.
- Machine-learning perspectives on Volterra system identification. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 383(2305).