My publications pertain to Scientific Machine Learning, particularly integrating numerical analysis with machine learning to solve PDEs and dynamical systems. I am also interested in Stochastic Processes and their applications, having worked particularly on credit risk modelling.
The detailed list can be found on my scholar profile.
Georgiou, K. C., Siettos, C., & Yannacopoulos, A. N. (2026). Learning Contractive Integral Operators with Fredholm Integral Neural Operators, arXiv preprint arXiv:2604.03034.
Georgiou, K., Fabiani, G., Siettos, C., & Yannacopoulos, A. N. (2025). HEATNETs: Explainable Random Feature Neural Networks for High-Dimensional Parabolic PDEs. arXiv preprint arXiv:2511.00886.
Georgiou, K., Siettos, C., & Yannacopoulos, A. N. (2025). Fredholm neural networks. SIAM Journal on Scientific Computing, 47(4), C1006-C1031.
Georgiou, K., Siettos, C., & Yannacopoulos, A. N. (2025). Fredholm Neural Networks for forward and inverse problems in elliptic PDEs. arXiv preprint arXiv:2507.06038.
Georgiou, K., & Yannacopoulos, A. N. (2024). Deep neural networks for probability of default modelling. Journal of Industrial and Management Optimization, 20(12), 3647-3677.
Georgiou, K., & Yannacopoulos, A. N. (2023). Probability of Default modelling with Lévy-driven Ornstein-Uhlenbeck processes and applications in credit risk under the IFRS 9. arXiv preprint arXiv:2309.12384.
Georgiou, K., Domazakis, G. N., Pappas, D., & Yannacopoulos, A. N. (2021). Markov chain lumpability and applications to credit risk modelling in compliance with the International Financial Reporting Standard 9 framework. European Journal of Operational Research, 292(3), 1146-1164.
Georgiou, K., & Chasapis, A. (2022). Novel time slicing approach for customer defection models in e-commerce: A case study. Data Science and Management, 5(3), 149-162.
Georgiou, K. (2023). Discrete, continuous and machine learning models with applications in credit risk (Doctoral dissertation, Athens University of Economics and Business).