Synced from ORCID. Full record: orcid.org/0000-0001-5916-8981
Preprints Under Review#
Multi-View Mel-Filterbank Fusion for Robust Drive-By Population-Based Bridge Damage Detection
Submitted to Mechanical Systems and Signal Processing (SSRN preprint, 2026)
This paper shows that fusing several diverse mel-filterbank channels in a single shared graph autoencoder removes the single-channel bias of drive-by population-based damage detection, validated on both simulations and a field campaign on in-service bridges.
A Drive-By PBSHM Framework for Bridge Damage Detection Under Temperature Variability
Submitted to Engineering Structures (SSRN preprint, 2026)
This paper presents a drive-by population-based structural health monitoring framework that detects bridge damage while explicitly addressing temperature-induced variability in structural response.
Journal Articles#
Multibridge Inference Structural Health Monitoring (MISHM): A Drive-By Crowdsensing Approach at the Network Level
Structural Control and Health Monitoring, Vol. 2025, No. 1, Article ID 8624965, 2025
This paper presents a novel framework for monitoring multiple bridges simultaneously using crowdsensing technologies and drive-by measurements.
A computer vision-based method to identify the international roughness index of highway pavements
Journal of Infrastructure Intelligence and Resilience, Vol. 1, Issue 1, Article 100004, 2022
This study presents a novel approach to assess pavement roughness using imaging techniques and artificial neural networks.
Conference Papers#
Unsupervised temperature-aware population-based SHM using drive-by crowdsensing
Moving Toward Smart, Resilient and Sustainable Bridges, Proceedings of the 13th International Conference on Bridge Maintenance, Safety and Management (IABMAS 2026), CRC Press, pp. 1017–1023, 2026
Conference paper on an unsupervised, temperature-aware population-based SHM framework that detects damage with a population-level autoencoder and localises the damaged bridge with leave-one-out sub-autoencoders.
Multi-Bridge Indirect Structural Health Monitoring: Leveraging Big Data and Drive-By Crowdsensing Techniques
Structural Health Monitoring & Machine Learning, Vol. 12, Proceedings of the 43rd IMAC, A Conference and Exposition on Structural Dynamics 2025
Conference proceedings paper on multi-bridge indirect structural health monitoring using big data and drive-by crowdsensing techniques.
Bridge Damage Detection Using Passing-By Vehicles and CNN-LSTM Autoencoder
Proceedings of the Canadian Society for Civil Engineering Annual Conference 2023, Lecture Notes in Civil Engineering, Vol. 507, pp. 327–335, 2024
This paper presents a CNN-LSTM autoencoder approach for bridge damage detection using responses from passing-by vehicles.
Deep learning-based crack detection in a concrete tunnel structure using multispectral dynamic imaging
Proc. SPIE 11382, Smart Structures and NDE for Industry 4.0, Smart Cities, and Energy Systems, 2020
Application of deep learning techniques for automated crack detection in concrete tunnel structures using advanced imaging methods.
Heat loss detection using thermal imaging by a small UAV prototype
Proc. SPIE 11382, Smart Structures and NDE for Industry 4.0, Smart Cities, and Energy Systems, 2020
Investigation of thermal imaging applications using unmanned aerial vehicles for building energy efficiency assessment.