Stefanos D. Nikolopoulos

Ph.D Student at National Technical University of Athens [full CV]

Research and interests

  • Software Engineering
  • Machine Learning
  • Data-Driven Modelling
  • Physics Informed Neural Networks
  • Surrogate Modelling
  • Bioengineering

Education

  • Ph.D. Candidate Civil Engineering, NTUA – School of Civil Engineering, Greece.
  • M.Sc. Applied Mechanics, NTUA – School of Applied Mathematics, Greece.
  • M.Eng. Civil Engineering, University of Patras – School of Civil Engineering, Greece.
  • B.Sc. Civil Engineering, University of Patras – School of Civil Engineering, Greece.

Publications

  • S. Nikolopoulos, I. Kalogeris, V. Papadopoulos, “Machine Learning Accelerated Transient Analysis of Stochastic Nonlinear Structures”, Engineering Structures, 2022.
  • 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. 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. 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.
  • S. Nikolopoulos, P. A. Gourgiotis, T. Zisis, “Analysis of the Tilted Shallow Wedge Problem in Couple-Stress Elasticity”, Journal of Elasticity, vol. 144 205-221, 2021.

 

  • Stefanos Nikolopoulos, Ioannis Kalogeris, Vissarion Papadopoulos, “A Data-Driven Surrogate for parametrized time-dependent PDEs based on Convolutional Autoencoders”, International Congress on Computational Mechanics (10th GRACM), Virtual Congress, 5-7 July 2021.

 

 

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