Research publications

Find below selected recent publications of our team demonstrating the application of AI in an variety of domains including industrial sectors, healthcare, energy and security 

Some of our recent papers:



  • S. Moustakidis, P. Kampaktsis, A. Tzani, I. Doulamis, A. Tzoumas, A. Drosou, G. Filippatos, A. Briasoulis, Machine Learning Based Prediction of 1-year Survival after Isolated Heart Transplant, The Journal of Heart and Lung Transplantation, 40, 4, Supplement, 2021,

  • Ntakolia, C.; Kokkotis, C.; Moustakidis, S.; Tsaopoulos, D. Prediction of Joint Space Narrowing Progression in Knee Osteoarthritis Patients. Diagnostics 2021, 11, 285.

  • Kokkotis, C.; Moustakidis, S.; Baltzopoulos, V.; Giakas, G.; Tsaopoulos, D. Identifying Robust Risk Factors for Knee Osteoarthritis Progression: An Evolutionary Machine Learning Approach. Healthcare 2021, 9, 260.

  • Ntakolia, C., Anagnostis, A., Moustakidis, S. et al. Machine learning applied on the district heating and cooling sector: a review. Energy Systems 2021.


  • Moustakidis, S., Papandrianos, N.I., Christodolou, E. et al. Dense neural networks in knee osteoarthritis classification: a study on accuracy and fairness. Neural Computing & Applications (2020).

  • K. Liakos, G. Georgakilas, S. Moustakidis, N. Sklavos & F. Plessas, Conventional and machine learning approaches as countermeasures against hardware trojan attacks. Microprocessors And Microsystems 2020, 79, 103295. doi: 10.1016/j.micpro.2020.103295

  • C. Kokkotis, S. Moustakidis, E. Papageorgiou, G. Giakas, & D. Tsaopoulos, Machine learning in knee osteoarthritis: A review. Osteoarthritis And Cartilage Open 2020, 2(3), 100069. doi: 10.1016/j.ocarto.2020.100069

  • C. Kokkotis, S. Moustakidis, G. Giakas, D. Tsaopoulos, Identification of Risk Factors and Machine Learning-Based Prediction Models for Knee Osteoarthritis Patients. Applied Sciences 2020, 10(19), 6797

  • S. Moustakidis, P. Karlsson, A novel feature extraction methodology using Siamese convolutional neural networks for intrusion detection. Cybersecurity 3(16), 2020.



  • S. Moustakidis, E. Christodoulou, E. Papageorgiou, C. Kokkotis, N. Papandrianos and D. Tsaopoulos, Application of machine intelligence for osteoarthritis classification: a classical implementation and a quantum perspective, Quantum Machine Intelligence, 2019. Available: 10.1007/s42484-019-00008-3 

  • S. Moustakidis, M. Omar, J. Aguirre, P. Mohajerani, and V. Ntziachristos, V., Fully automated identification of skin morphology in raster‐scan optoacoustic mesoscopy using artificial intelligence. Medical Physics, 46(9), 4046-4056, 2019. doi: 10.1002/mp.13725 

  •   S. Moustakidis, I. Meintanis, G. Halikias, and N. Karcanias, An Innovative Control Framework for District Heating Systems: Conceptualisation and Preliminary Results, Resources, vol. 8, no. 1, p. 27, 2019. Available: 10.3390/resources8010027 

      till 2018


  • S. Moustakidis et al., Excitation-invariant pre-processing of thermographic data, Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, vol. 232, no. 4, pp. 435-446, 2018. Available: 10.1177/1748006x18770888

  • S. Moustakidis et al., Non-destructive inspection of aircraft composite materials using triple IR imaging. IFAC-PapersOnLine 2016, 49, 291-296.

  • S. Moustakidis et al., An Intelligent Methodology for Railways Monitoring Using Ultrasonic Guided Waves, Journal of Nondestructive Evaluation, vol. 33, no. 4, pp. 694–710, Oct. 2014. 

  • S. Moustakidis, G. Mallinis, N. Koutsias, J. B. Theocharis and V. Petridis, SVM-based fuzzy decision trees for classification of high spatial resolution remote sensing images, IEEE Transactions on Geoscience and Remote Sensing, 50 (1) , art. no. 5976442 , pp. 149-169, 2012. 

  • S. Moustakidis, J. B. Theocharis, and G. Giakas, A fuzzy decision tree-based SVM classifier for assessing osteoarthritis severity using ground reaction force measurements, Medical Engineering and Physics 32(10): 1145-1160, 2010. 

  • S. Moustakidis and J. B. Theocharis, SVM-FuzCoC: A novel SVM-based feature selection method using a fuzzy complementary criterion, Pattern Recognition, vol. 43, pp. 3712-3729, 2010

  • S. Moustakidis, J. B. Theocharis, and G. Giakas, Subject Recognition Based on Ground Reaction Force Measurements of Gait Signals, IEEE Transactions on Systems, Man, and Cybernetics—Part B, vol.38, no.6, pp.1476-1485, Dec. 2008