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

Research and interests

• Computational Mechanics
• Stochastic Finite Elements Method
• Machine Learning
• Uncertainty Quantification
• Surrogate Modeling
• Software Engineering

Education

• Ph.D. Candidate Civil Engineering, NTUA – School of Civil Engineering, Greece.
• M.Sc. Computational Mechanics, NTUA – School of Chemical Engineering, Greece.
• M.Eng. Civil Engineering, Aristotle University of Thessaloniki – School of Civil Engineering, Greece.
• B.Sc. Civil Engineering, Aristotle University of Thessaloniki – School of Civil Engineering, Greece.

Publications

• S. Pyrialakos S., Kalogeris I., Sotiropoulos G., Papadopoulos V., “A neural network-aided Bayesian identification framework for multiscale modeling of nanocomposites”, Computer Methods in Applied Mechanics and Engineering, vol. 384, 2021.
• Kalogeris I., Pyrialakos S., Bakalakos S., Kokkinos O., Papadopoulos V., “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.
• Pyrialakos S., Kalogeris I., Sotiropoulos G., Papadopoulos V., “Bayesian Inference on Multiscale Models of Carbon-Reinforced Polymers accelerated by Deep Neural Networks”, 4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2021), Virtual Congress, 28-30 June 2021.
• Pyrialakos S., Kalogeris I., Sotiropoulos G., Papadopoulos V., “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.
• Pyrialakos S., Kalogeris I., Papadopoulos V., “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.