Recent publications
Article
Chen, K, Eskandari Torbaghan, M, Thom, N, Garcia-Hernández, A, Faramarzi, A & Chapman, D 2024, 'A Machine Learning based approach to predict road rutting considering uncertainty', Case Studies in Construction Materials, vol. 20, e03186. https://doi.org/10.1016/j.cscm.2024.e03186
Pentassuglia, F, Kazantzi, AK, Faramarzi, A & Mitoulis, S-A 2024, 'Bridge assessment based on deflection as a measure of damage using Machine Learning-enhanced pattern identification', Procedia Structural Integrity, vol. 64, pp. 254-261. https://doi.org/10.1016/j.prostr.2024.09.241
Afrasiabi, A, Faramarzi, A, Chapman, D & Keshavarzi, A 2025, 'Optimising Ground Penetrating Radar data interpretation: A hybrid approach with AI-assisted Kalman Filter and Wavelet Transform for detecting and locating buried utilities', Journal of Applied Geophysics, vol. 232, 105567. https://doi.org/10.1016/j.jappgeo.2024.105567
Ye, Z, Lovell, L, Faramarzi, A & Ninic, J 2024, 'Sam-based instance segmentation models for the automation of structural damage detection', Advanced Engineering Informatics, vol. 62, no. Part C, 102826. https://doi.org/10.1016/j.aei.2024.102826
Tafreshi Moghaddas, SN, Sarabadani, A, Rahimi, M, Amiri, A, Dawson, A & Faramarzi, A 2023, 'Geocell-reinforced bed anchored with additional vertical elements under repeated loading', Transportation Geotechnics, vol. 42, 101089. https://doi.org/10.1016/j.trgeo.2023.101089
Mehravar, M, Harireche, O, Faramarzi, A, Rahimzadeh, F, Osman, A & Dirar, S 2023, 'Installation performance of structurally enhanced caissons in sand', Computers and Geotechnics, vol. 159, 105464. https://doi.org/10.1016/j.compgeo.2023.105464
Monzer, A, Faramarzi, A, Yerro, A & Chapman, D 2023, 'MPM Investigation of the Fluidization Initiation and Post-Fluidization Mechanism Around a Pressurized Leaking Pipe', Journal of Geotechnical and Geoenvironmental Engineering - ASCE, vol. 149, no. 11, 04023096. https://doi.org/10.1061/JGGEFK.GTENG-10985
Tafreshi Moghaddas, SN, Khanjani, A, Dawson, A & Faramarzi, A 2023, 'Performance of recycled waste aggregate mixed with crushed glass over a weak subgrade', Construction and Building Materials, vol. 402, 133002. https://doi.org/10.1016/j.conbuildmat.2023.133002
Li, H, Chapman, D, Faramarzi, A & Metje, N 2023, 'The Analysis of the Fracturing Mechanism and Brittleness Characteristics of Anisotropic Shale Based on Finite-Discrete Element Method', International Journal of Rock Mechanics & Mining Sciences. https://doi.org/10.1007/s00603-023-03672-x
Afrasiabi, A, Faramarzi, A, Chapman, D, Keshavarzi, A & Stringfellow, M 2023, 'Toward the optimisation of the Kalman Filter approach in ground penetrating radar application for detection and locating buried utilities', Journal of Applied Geophysics, vol. 219, 105220. https://doi.org/10.1016/j.jappgeo.2023.105220
Dabiri, H, Faramarzi, A, Dall’Asta, A, Tondi, E & Micozzi, F 2022, 'A machine learning-based analysis for predicting fragility curve parameters of buildings', Journal of Building Engineering, vol. 62, 105367. https://doi.org/10.1016/j.jobe.2022.105367
Conference article
Izonin, I, Tkachenko, R, Mitoulis, S, Faramarzi, A, Tsmots, I & Mashtalir, D 2024, 'Machine learning for predicting energy efficiency of buildings: a small data approach', Procedia Computer Science, vol. 231, pp. 72-77. https://doi.org/10.1016/j.procs.2023.12.173
Conference contribution
Ye, Z, Faramarzi, A, Ninic, J & Lin, W 2025, Automated digital twin reconstruction for tunnel inspection and maintenance. in Proceedings of the ITA-AITES World Tunnel Congress 2025 (WTC 2025). CRC Press, World Tunnel Congress 2025, Sweden, 9/05/25.
Ye, Z, Lovell, L, Faramarzi, A & Ninic, J 2024, SAM-based Structural Surface Damage Detection. in B Riveiro & P Arias (eds), Proceedings of the 31st International Workshop on Intelligent Computing in Engineering. University of Vigo, pp. 176-185, 31st International Workshop on Intelligent Computing in Engineering, Vigo, Spain, 1/07/24. <https://3dgeoinfoeg-ice.webs.uvigo.es/proceedings>
Preprint
Ye, Z, Lovell, L, Faramarzi, A & Ninić, J 2024 'Sam-Based Instance Segmentation Models for the Automation of Structural Damage Detection' SSRN. https://doi.org/10.2139/ssrn.4750668
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