Assistant Professor designate at the school of Mechanical Engineering, National Technical University of Athens [full CV]

Research and interests

• Applied and Computational Mechanics
• Stochastic Finite Elements Method
• Machine Learning
• Uncertainty Quantification
• Surrogate Modeling
• Theoretical Mathematics

Education

• Postdoctoral studies in Computational Mechanics, ETH Zurich – School of Mechanical and Process Engineering, Greece.
• Postdoctoral studies in Computational Mechanics, NTUA – School of Civil Engineering, Greece.
• Ph.D. Computational Mechanics, NTUA – School of Civil Engineering, Greece.
• M.Sc. Mathematics, NTUA – National and Kapodistrian University of Athens – School of Science, Greece.
• M.Sc. Analysis and Design of Structures, NTUA – School of Civil Engineering, Greece.
• Bachelor. Mathematics, National and Kapodistrian University of Athens – School of Science, Greece.
• M. Eng. Civil Engineering, NTUA – School of Civil Engineering, Greece.

Selected Publications

Papers in Scientific Journals

1. Papadopoulos L., Atzarakis, K., Sotiropoulos, G., Kalogeris I., Papadopoulos V. , Fusing nonlinear solvers with transformers for accelerating the solution of parametric transient problems, Computer Methods in Applied Mechanics and Engineering, 2024
2. Nikolopoulos S., Kalogeris I., Stavroulakis G., Papadopoulos V. , AI-enhanced iterative solvers for accelerating the solution of large-scale parametrized systems, International Journal for Numerical Methods in Engineering, 2023
3. Attia M., Khandaker M.A.H., Pyrialakos S., Kalogeris I., Enhancing the performance of anti-blast windows through the use of carbon nanotube reinforced polymer gaskets, Journal of Building Engineering, 2023
4. Pyrialakos S., Kalogeris I., Papadopoulos V., Multiscale analysis of nonlinear systems using a hierarchy of deep neural networks, International Journal of Solids and Structures, 2023
5. Papadopoulos L., Bakalakos S., Nikolopoulos S., Kalogeris I., Papadopoulos V., A computational framework for the indirect estimation of interface thermal resistance of composite materials using XPINNs, International Journal of Heat and Mass Transfer, vol. 200, 2023
6. Kalogeris I., Pyrialakos S., Kokkinos O., Papadopoulos V., Stochastic optimization of carbon nanotube reinforced concrete for enhanced structural performance, Engineering with Computers, doi: https://doi.org/10.1007/s00366-022-01693-8, 2022
7. Nikolopoulos S., Kalogeris I., Papadopoulos V., Machine learning accelerated transient analysis of stochastic nonlinear structures, Engineering Structures, vol. 257. 2022
8. Fuhg, J.N., Kalogeris I., Fau, A., Bouklas, N., Interval and fuzzy physics-informed neural networks for uncertain fields, Probabilistic Engineering Mechanics, vol. 68, 2022
9. S. Nikolopoulos, I. Kalogeris, V. Papadopoulos, Non-intrusive surrogate modeling for parametrized time-dependent PDEs using convolutional autoencoders, Engineering Applications of Artificial Intelligence, vol. 109. 2022
10. S. Bakalakos, I. Kalogeris, V. Papadopoulos, M. Papadrakakis, P. Maroulas, D.A.  Dragatogiannis, C.A Charitidis, An integrated XFEM modeling with experimental measurements for optimizing thermal conductivity in carbon nanotube reinforced polyethylene, Modelling and Simulation in Materials Science and Engineering, 2022
11. Χ. Lu, J. Yvonnet, L. Papadopoulos, I. Kalogeris, V. Papadopoulos, A stochastic FE2 data-driven method for nonlinear multiscale modeling, Materials, vol. 14, 2021
12. S. Pyrialakos, I. Kalogeris, G. Sotiropoulos, V.  Papadopoulos, A neural network-aided Bayesian identification framework for multiscale modeling of nanocomposites, Computer Methods in Applied Mechanics and Engineering, vol. 384, 2021
13. I. Kalogeris, V. Papadopoulos, Diffusion maps-aided Neural Networks for the solution of parametrized PDEs, Computer Methods in Applied Mechanics and Engineering, vol. 376, 2021
14. S. Bakalakos, I. Kalogeris, V. Papadopoulos, An extended finite element method formulation for modeling multi-phase boundary interactions in steady state heat conduction problems, Composite Structures, vol. 258, 2021
15. I. Kalogeris, V. Papadopoulos, Diffusion maps-based surrogate modeling: An alternative machine learning approach, International Journal of Numerical Methods in Engineering, vol. 121, pp. 602- 620, 2020
16. V. Papadopoulos, I. Kalogeris, D. Giovanis, A spectral stochastic formulation for nonlinear framed structures, Probabilistic Engineering Mechanics, vol. 55, pp. 90-101, 2019
17. I. Kalogeris, V. Papadopoulos, Limit analysis of stochastic structures in the framework of the probability Density Evolution Method, Engineering Structures, vol. 160, pp. 304-313, 2018
18. I. Kalogeris, V. Papadopoulos, A Galerkin-based formulation of the probability density evolution method for general stochastic finite element systems, Computational Mechanics, vol. 57, pp. 701-716, 2016

Selected Conference Presentations

• I. Kalogeris, L. Papadopoulos, K. Atzarakis, G. Sotiropoulos, V. Papadopoulos, A trasnformers-based AI approach for generating physics informed dynamics, Workshop for data-driven applications for Exascale Supercomputers, Athens, Greece, 2-3 Sept. 2024
• I. Kalogeris, S. Pyrialakos, V. Papadopoulos, Multiscale Analysis of Structures Composed of Composite Materials using a Hierarchy of Deep Neural Networks, 17th U.S. National Congress on Computational Mechanics, 17th USNCCM, Albuquerque, New Mexico, 23-27 July 2023
• I. Kalogeris, S. Pyrialakos, S. Bakalakos, O. Kokkinos, V. Papadopoulos, Machine learning-assisted stochastic optimization of structures comprised of nano-reinforced concrete, International Congress on Computational Mechanics organized by the Greek Association of Computational Mechanics, 10th GRACM, Virtual Congress, 5-7 July 2021
• S. Pyrialakos, I. Kalogeris, G. Sotiropoulos, V.  Papadopoulos, Bayesian Inference on Multiscale Models of Carbon-Reinforced Polymers accelerated by Deep Neural Networks, Engineering Mechanics Institute Conference (EMI), Virtual Congress, 25-28 May 2021
• S. Nikolopoulos, I. Kalogeris, V. Papadopoulos, An autoencoder-based surrogate modeling approach for parametrized time-dependent PDEs, 14th World Conference on Computational Mechanics, WCCM XIV, and 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2020), joint Virtual Congress, 11-15 January 2021
• S. Pyrialakos, I. Kalogeris, V.  Papadopoulos, A Bayesian identification framework for multiscale analysis of nanocomposites, 14th World Conference on Computational Mechanics (WCCM XIV) and 8th European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2020, joint Virtual Congress, 11-15 January 2021
• S. Nikolopoulos, I. Kalogeris, V. Papadopoulos, A machine learning approach for parametric time-history analysis, XI International Conference on Structural Dynamics, EURODYN 2020, 23-26 November 2020, Athens, Greece.
• I. Kalogeris, V. Papadopoulos, A Diffusion Maps-based surrogate model for uncertainty quantification, 3nd International Conference on Uncertainty Quantification in computational science and engineering, UNCECOMP, Hersonissos, 24-26 June 2019, Crete.
• V. Papadopoulos, I. Kalogeris, M. Ibraimakis, D. Giovanis, Consistent Bayesian update for multiscale analysis using subset simulation, 13th World Congress on Computational Mechanics, WCCM, , 22-28 July 2018, New York, USA.
• I. Kalogeris, V. Papadopoulos, D. Giovanis, A spectral stochastic finite element formulation for nonlinear analysis of stochastic structures, 8th Conference on Computational Stochastic Mechanics, CSM, 11-13 June 2018, Paros, Greece.
• V. Papadopoulos, I. Kalogeris, D. Giovanis, An SSFEM formulation for the stochastic analysis of nonlinear framed structures, 2nd International Conference on Uncertainty Quantification in computational science and engineering, UNCECOMP, 15-17 June 2017, Rhodes, Greece.
• I. Kalogeris, V. Papadopoulos , Probability Density Evolution Method for buckling analysis of stochastic systems, 7th European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2016, 5-10 June 2016 Crete, Greece.
• V. Papadopoulos, I. Kalogeris, A Streamline Upwind/Petrov-Galerkin solution of the Probability Density Evolution Method for static systems, Symposium on Reliability of Engineering System, SRES, Hangzhou, 15-17 October 2015, Shanghai, China.