Related Publications:
Prantikos, K.; Lee, T.; Hua, T.Q.; Tsoukalas, L.H.; Heifetz, A. Explainable machine learning for incipient anomaly detection in compact molten salt heat exchanger with overlapping feature distributions. Sci. Rep. 2026, 16, 8293. https://doi.org/10.1038/s41598-025-27112-8
Pantopoulou, M.; Kultgen, D.; Tsoukalas, L.; Heifetz, A. Monitoring of Liquid Metal Reactor Heater Zones with Recurrent Neural Network Learning of Temperature Time Series. Energies 2026, 19, 1462. https://doi.org/10.3390/en19061462
Pantopoulou, S.; Cilliers, A.; Tsoukalas, L.H.; Heifetz, A. Transformers and Long Short-Term Memory Transfer Learning for GenIV Reactor Temperature Time Series Forecasting. Energies 2025, 18, 2286. https://doi.org/10.3390/en18092286
Pantopoulou, S.; Weathered, M.; Lisowski, D.; Tsoukalas, L.; Heifetz, A. Temporal Forecasting of Distributed Temperature Sensing in a Thermal Hydraulic System with Machine Learning and Statistical Models. IEEE Access 2025, 13, pp. 10252-10264. https://doi.org/10.1109/ACCESS.2025.3526438
Appiah, R.; Heifetz, A.; Kultgen, D.; Tsoukalas, L.H.; Vilim, R.B. Dynamic Control of Sodium Cold Trap Purification Temperature Using LSTM System Identification. Energies 2024, 17, 6257. https://doi.org/10.3390/en17246257
Prantikos, K.; Chatzidakis, S.; Tsoukalas, L.H.; Heifetz, A. Physics-Informed Neural Network with Transfer Learning (TL-PINN) Based on Domain Similarity Measure for Prediction of Nuclear Reactor Transients. Scientific Reports 2023, 13, 16840. https://doi.org/10.1038/s41598-023-43325-1
Kontogiannis, D.; Bargiotas, D.; Daskalopulu, A.; Arvanitidis, A.I.; Tsoukalas, L.H. (2022). Structural Ensemble Regression for Cluster-Based Aggregate Electricity Demand Forecasting. Electricity 2022, 3, 480-504. https://doi.org/10.3390/electricity3040025
Kontogiannis, D.; Bargiotas, D.; Daskalopulu, A.; Arvanitidis, A.I.; Tsoukalas, L.H. (2022). Error Compensation Enhanced Day-Ahead Electricity Price Forecasting. Energies 2022, 15, 1466. https://doi.org/10.3390/en15041466
Arvanitidis, A.I.; Bargiotas, D.; Daskalopulu, A.; Kontogiannis, D.; Panapakidis, I.P.; Tsoukalas L.H. (2022). Clustering Informed MLP Models for Fast and Accurate Short-Term Load Forecasting. Energies 2022, 15, 1295. https://doi.org/10.3390/en15041295
Laitsos, V.; Vontzos, G.; Bargiotas, D.; Daskalopulu, A.; Tsoukalas, L.H. Enhanced Automated Deep Learning Application for Short-Term Load Forecasting. Mathematics 2023, 11, 2912. https://doi.org/10.3390/math11132912
Sgourou, E.N.; Daskalopulu, A.; Tsoukalas, L.H.; Stamoulis, G.; Vovk, R.V.; Chroneos, A. Seventy-Five Years since the Point-Contact Transistor: Germanium Revisited. Appl. Sci. 2022, 12, 11993.
Pantopoulou, S., Lisowski, D., Cilliers, A., Tsoukalas, L.H., Heifetz, A., "LSTM Validation of Fiber Optics Distributed Temperature Sensing", American Nuclear Society Winter Meeting, Washington DC, USA, November 30 - December 3, 2021.
Pantopoulou, S., Pantopoulou M., Tsoukalas, L. H., “Secure Decision Making and Inference in Critical Systems,”. In 2021 12th International Conference on Information, Intelligence, Systems and Applications (IISA) (pp. 1-4). IEEE.
Lagari, P.L., Alamaniotis, M., Pantopoulou, S., Tsoukalas, L.H., “A Library of Radionuclide Gamma Profiles for the Identification of Unknown Sources,” Nuclear Technology, 2021.
Lagari, P.L., Tsoukalas, L.H., Safarkhani, S., Lagaris, I.E., “Systematic construction of neural forms for solving partial differential equations inside rectangular domains, subject to initial, boundary and interface conditions,” International Journal on Artificial Intelligence Tools, 2020.
Pantopoulou, S., Lagari, P. L., Townsend, C. H., & Tsoukalas, L. H. (2020, July). Critical Systems under Cyber Threats. In 2020 11th International Conference on Information, Intelligence, Systems and Applications (IISA) (pp. 1-4). IEEE.
Townsend, C., Bean R., PUR-1: A fully digital I&C installation driving innovation, Nuclear News, ANS, February 2019, pp. 37-39.
Lagari, P.L., Tsoukalas, L.H., Lagaris, I.E., “Variance Counterbalancing for Stochastic Large-Scale Learning, “International Journal on Artificial Intelligence Tools, 2020.
Fainti, R., Karasimou, M., Tsionas, I., Tsoukalas, L.H. Alamaniotis, M., "Load Management of Electric Vehicles Charging in New Generation Power Markets based on Fuzzy Logic and the Concept of Virtual Budget", 9th International Conference on Information, Systems and Applications (IISA), Zakynthos, Greece, July 2018, pp. 1-7. Invited
Alamaniotis, M., Tsoukalas, L.H., "Peak Locating in Gamma-Ray Spectra Using Wavelet Processing and Support Vector Regression with Applications to Nuclear Nonproliferation", Advances in Nuclear Nonproliferation and Policy Conference, Orlando, FL, USA, November 11-15, 2018, pp. 1-4.
Alamaniotis, M., Mathew, J., Chroneos, A., Fitzpatrick, M., Tsoukalas, L.H., Probabilistic Kernel Machines for Predictive Monitoring of Weld Residual Stress in Energy Systems, Engineering Applications of Artificial Intelligence, Elsevier, 2018, pp. 1-28.
Alamaniotis, M., Gatsis, N., Tsoukalas, L.H., Virtual Budget: Integration of Electricity Load and Price Anticipation for Load Morphing in Price-Directed Energy Utilization, Electric Power Systems Research, Elsevier, vol. 158, 2018, pp. 284-296.