Dimitrios Loverdos

Dr Dimitrios Loverdos BEng, MEng, PhD

Lecturer in digital construction

Dimitrios Loverdos is a lecturer in digital construction at the School of Civil Engineering, University of Greenwich. He holds a PhD and MEng from the University of Leeds, where he studied in the Department of Civil and Structural Engineering.

His specialised expertise includes physical large-scale testing and numerical analysis (FEM and DEM). He excels in computer vision, machine learning, and algorithmic operations using Python and MATLAB. In recent projects, he has successfully addressed topics such as automated model generation, defect detection, and damage assessment of structures using digital data.

Dimitrios has extensive experience in a laboratory environment, providing technical assistance and management for tasks such as construction, experimental testing, and demolition. Additionally, he has strong experience in structural design, with extensive knowledge in designing composite perforated beams with both typical and custom web openings

Civil engineering

Responsibilities within the university
  • Teaching  - Design of Concrete Structures.(CIVI0038)

Research / Scholarly interests
  • Numerical analysis of complex structures using the finite-element (FEM) or discrete-element method (DEM).
  • Automation of visual-inspection using computer-vision and machine-learning.
  • Automation of structural-assessment using computer-vision and machine-learning.
  • Automatic generation of classified BIM models for digital twins.

Key funded projects

  • IAA-EPSRC (EP/X52573X/1) – Post-Doctorate Research Assistant (2023-2024): Named researcher in: Automating structural inspection of our ageing infrastructure using machine learning. Value (FEC): £144,823.

Recent publications

Loverdos, D. and Sarhosis, V. (2024) ‘Pixel-level block classification and crack detection from 3D reconstruction models of masonry structures using convolutional neural networks’, Engineering Structures, 310. Available at: https://doi.org/10.1016/j.engstruct.2024.118113.

Loverdos, D. and Sarhosis, V. (2023) ‘Image2DEM: A geometrical digital twin generator for the detailed structural analysis of existing masonry infrastructure stock’, SoftwareX, 22. Available at: https://doi.org/10.1016/j.softx.2023.101323.

Loverdos, D. and Sarhosis, V. (2023) ‘Geometrical digital twins of masonry structures for documentation and structural assessment using machine learning’, Engineering Structures, 275(PA), p. 115256. Available at: https://doi.org/10.1016/j.engstruct.2022.115256.

Vandenabeele, L., Loverdos, D., Pfister, M. and Sarhosis, V. (2023) ‘Deep Learning for the Segmentation of Large- Scale Surveys of Historic Masonry: A New Tool for Building Archaeology Applied at the Basilica of St Anthony in Padua’, International Journal of Architectural Heritage, 00(00), pp. 1–13. Available at: https://doi.org/10.1080/15583058.2023.2260771.

Loverdos, D. and Sarhosis, V. (2022) ‘Automatic image-based brick segmentation and crack detection of masonry walls using machine learning’, Automation in Construction, 140, p. 104389. Available at: https://doi.org/10.1016/j.autcon.2022.104389.

Loverdos, D. and Sarhosis, V. (2022) ‘A geometrical digital twin generator for the detailed structural analysis of our existing masonry infrastructure stock: Image2DEM’, SSRN Electronic Journal [Preprint]. Available at: https://doi.org/10.2139/ssrn.4252611.

Loverdos, D., Sarhosis, V., Adamopoulos, E. and Drougkas, A. (2021) ‘An innovative image processing-based framework for the numerical modelling of cracked masonry structures’, Automation in Construction, 125, p. 103633. Available at: https://doi.org/10.1016/j.autcon.2021.103633.

Ferrante, A., Loverdos, D., Clementi, F., Milani, G., Formisano, A., Lenci, S. and Sarhosis, V. (2020) ‘Discontinuous approaches for nonlinear dynamic analyses of an ancient masonry tower’, Engineering Structures, 230(November 2020), p. 111626. Available at: https://doi.org/10.1016/j.engstruct.2020.111626.

Presentations

Loverdos, D., Sarhosis, V. and Liu, B. (2024) ‘Developing three dimensional geometrical digital-twins for masonry arch bridges using deep learning’, in 18th International Brick and Block Masonry Conference (IB2MaC 2024). Springer, pp. 1–1. Available at: https://doi.org/10.1007/978-3-031-73314-7_36.

Liu, Bowen, Loverdos, Dimitrios, Sarhosis, V., Firoozmand, F., Liu, B, Loverdos, D and Sarhosis, & V (2024) ‘AI-aided detection of the response of free-standing ancient columns subjected to earthquake: A preliminary study’, in 18th world conference on earthquake engineering (WCEE2024). Milan. Available at: https://www.researchgate.net/publication/381982077.

Loverdos, D., Liu, B. and Sarhosis, V. (2024) ‘Automated post-earthquake damage-assessment of masonry buildings using computer-vision’, in 18th world conference on earthquake engineering (WCEE2024). Milan. Available at: https://www.researchgate.net/publication/382530888.

Loverdos, D., Sarhosis, V. and Bowen Liu (2023) ‘Automation in Documentation of Ageing Masonry Infrastructure Through Image-Based Techniques and Machine Learning’, in 11th European Workshop on Structural Health Monitoring (EWSHM2023). Palermo, pp. 727–735. Available at: https://doi.org/10.1016/j.autcon.2022.104389.

Muhit, B.I., Kawabe, D., Loverdos, D., Liu, B., Yukihiro, Y., Kim, C.-W. and Sarhosis, V. (2023) ‘A Framework for Digital Twinning of Masonry Arch Bridges’, in 8th International Symposium on Life-Cycle Civil Engineering (IALCCE2023). Milan, Italy. Available at: https://doi.org/10.1201/9781003323020-99.