1. G. Baxevani, V. Harmandaris, E. Kalligiannaki, I. Tsantili. Bottom-up transient time models in coarse-graining molecular systems. Accepted SIAM MMS, 2023, preprint arXiv:2302.05159

2. Y. Pantazis, E. Kalligiannaki, Y. Kamarianakis, K. Kotsovos, I. Gereige, M. Abdullah, A. Jamal, A. Tzavaras and T. Katsaounis, Efficiency evaluation and comparisons of solar cell technologies based on measurements from the Arabian peninsula, EuroSun, 2022

3. Y. Kamarianakis, Y. Pantazis, E. Kalligiannaki, T. Katsaounis, K. Kotsovos, I. Gereige, M. Abdullah, A. Jamal, and A. Tzavaras, KNN-based ensembles for day-ahead solar power output forecasting, EuroSun, 2022

4. Y. Pantazis, E. Kalligiannaki, Y. Kamarianakis, K. Kotsovos, I. Gereige, M. Abdullah, A. Tzavaras, and T. Katsaounis, Performance evaluation and comparison of solar cell technologies based on historical data, 8th World Conference on Photovoltaic Energy Conversion, 2022

5. Y. Kamarianakis, Y. Pantazis, E. Kalligiannaki, K. Kotsovos, I. Gereige, M. Abdullah, A. Tzavaras and T. Katsaounis, Day-ahead forecasting of solar irradiance: KNN-based ensembles, 8th World Conference on Photovoltaic Energy Conversion, 2022

6. A. Chazirakis, V. Kirieri, E. Kalligiannaki, V. Harmandaris. Neural Network Potential Surfaces: A comparison of two approaches. Procedia Computer Science, 178, 345-354, 2020. DOI:10.1016/j.procs.2020.11.036

7. T. Jin, A. Chazirakis, E. Kalligiannaki, V. Harmandaris, and M. Katsoulakis Data-driven Uncertainty Quantification for Systematic Coarse-grained Models. Soft Materials, 18:2-3, 348-368, DOI:10.1080/1539445X.2020.1765803, arXiv:2007.00340

• Interacting particle systems. Complex fluids and polymers. Surface processes.
• Uncertainty quantification. Statistical inference. Multi-scale modeling.
• Stochastic simulations. Markov chain Monte Carlo methods. Multi-level & Multi-Index Monte Carlo methods.
• Statistical mechanics. Semiclassical asymptotics, high frequency fields near caustics.