Postdoctoral Researcher at 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.
  • Bachelor. Mathematics, National and Kapodistrian University of Athens – School of Science, Greece.
  • Ph.D. Computational Mechanics, NTUA – School of Civil Engineering, Greece.
  • M.Sc. Analysis and Design of Structures, NTUA – School of Civil Engineering, Greece.
  • M. Eng. Civil Engineering, NTUA – School of Civil Engineering, Greece.

Publications

Papers in Scientific Journals

  • 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
  • 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
  • . Lu, J. Yvonnet, L. Papadopoulos, I. Kalogeris, V. Papadopoulos, A stochastic FE2 data-driven method for nonlinear multiscale modeling, Materials, vol. 14, 2021
  • 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
  • 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
  • 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
  • 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
  • V. Papadopoulos, I. Kalogeris, D. Giovanis, A spectral stochastic formulation for nonlinear framed structures, Probabilistic Engineering Mechanics, vol. 55, pp. 90-101, 2019
  • 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
  • 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

Conference Presentations

  • 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.

 

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