Saeed Eftekhar Azam 
- (2024): Introduction and application of a drive-by damage detection methodology for bridges using variational mode decomposition. In: Frattura ed Integrità Strutturale, v. 18, n. 70 (15 August 2024).
- (2023): Probabilistic bridge fatigue evaluation at virtual sensing locations using kernel density estimation. In: International Journal of Fatigue, v. 176 (November 2023).
- (2024): System Identification via Unscented Kalman Filtering and Model Class Selection. In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, v. 10, n. 1 (March 2024).
- (2024): Minimum variance unbiased Bayesian smoothing for input and state estimation of systems without direct Feedthrough: Mitigating Ill-Posedness of online load identification. In: Engineering Structures, v. 298 (January 2024).
- (2023): Singular value decomposition and unsupervised machine learning for virtual strain sensing: Application to an operational railway bridge. In: Structures, v. 58 (December 2023).
- (2023): Evaluating pod-based unsupervised damage identification using controlled damage propagation of out-of-service bridges. In: Engineering Structures, v. 286 (July 2023).
- (2023): A linear Bayesian filter for input and state estimation of structural systems. In: Computer-Aided Civil and Infrastructure Engineering, v. 38, n. 13 (May 2023).
- (2023): Novel Physics-Informed Artificial Neural Network Architectures for System and Input Identification of Structural Dynamics PDEs. In: Buildings, v. 13, n. 3 (26 February 2023).
- (2020): Steel railway bridge fatigue damage detection using numerical models and machine learning: Mitigating influence of modeling uncertainty. In: International Journal of Fatigue, v. 134 (May 2020).
- (2021): Unsupervised Machine Learning for Robust Bridge Damage Detection: Full-Scale Experimental Validation. In: Engineering Structures, v. 249 (December 2021).
- (2022): A Bayesian smoothing for input‐state estimation of structural systems. In: Computer-Aided Civil and Infrastructure Engineering, v. 37, n. 3 (2 February 2022).
- (2021): Fatigue crack detection in welded structural components of steel bridges using artificial neural network. In: Journal of Civil Structural Health Monitoring, v. 11, n. 4 (June 2021).
- (2021): On Bayesian active vibration control of structures subjected to moving inertial loads. In: Engineering Structures, v. 239 (July 2021).
- (2020): A framework for hybrid simulation with online model updating suitable for hard real‐time computing. In: Structural Control and Health Monitoring, v. 28, n. 1 (October 2020).
- (2019): Damage detection in structural systems utilizing artificial neural networks and proper orthogonal decomposition. In: Structural Control and Health Monitoring, v. 26, n. 2 (January 2019).
- (2013): Parallelized sigma-point Kalman filtering for structural dynamics. In: Computers & Structures, v. 114 (January 2013).
- (2013): Investigation of computational and accuracy issues in POD-based reduced order modeling of dynamic structural systems. In: Engineering Structures, v. 54 (September 2013).
- (2018): Online damage detection in structural systems via dynamic inverse analysis: A recursive Bayesian approach. In: Engineering Structures, v. 159 (March 2018).
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