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Contact Information


Postal Address

City, University of London
Northampton Square
United Kingdom



Dr Serafeim Moustakidis received his master’s and PhD degree in Electrical and Computer Engineering from the Aristotle University of Thessaloniki (AUTh). He has a wide experience in Artificial Intelligence (AI) and data processing with more than 10 years of research experience in various AI fields.

His research focuses in developing novel algorithms for solving important existing and/or emerging problems. His main scientific interests cover various fields such as Big Data, Biomechanics, Remote Sensing and Non Destructive Testing (NDT). He has been involved in numerous National and European projects as senior researcher or project manager as well as in the preparation of successful proposals for European projects.

He has worked for several research organisations across Europe (researcher in Centre for Research and Technology Hellas - CERTH, research associate at National Technical University of Athens - NTUA) and he is now a Research Fellow in Signal Processing for City University of London.


  1. PhD Electrical and Computer Engineering, Aristotle University of Thessaloniki, Greece
  2. MSc Electrical and Computer Engineering, Aristotle University of Thessaloniki, Greece


Conference papers and proceedings (9)

  1. Liakos, K., Moustakidis, S., Tsiotra, G., Bartzanas, T., Bochtis, D. and Parisses, C. (2017). Machine learning based computational analysis method for cattle lameness prediction.
  2. (2014). Long Range Ultrasonic inspection of aircraft wiring.
  3. (2013). High temperature transducers system for long range ultrasound non-destructive evaluation in aging power plants.
  4. (2012). An automated long range ultrasonic rail flaw detection system based on the support vector machine algorithm.
  5. (2010). A Fuzzy Complementary Criterion for structure learning of a neuro-fuzzy classifier.
  6. Moustakidis, S.P., Theocharis, J.B., Giakas, G. and IEEE, (2009). Feature Extraction based on a Fuzzy Complementary Criterion for Gait Recognition Using GRF Signals.
  7. (2006). An adaptive neuro-fuzzy control approach for nonlinear systems via Lyapunov function derivative estimation.
  8. Moustakidis, S.P., Rovithakis, G.A., Theocharis, J.B. and IEEE, (2006). An adaptive neuro-fuzzy control approach for nonlinear systems via lyapunov function derivative estimation.
  9. Nikolakis, G., Tzovaras, D., Moustakidis, S. and Strintzis, M.G. (2004). CyberGrasp and PHANTOM Integration: Enhanced Haptic Access for Visually Impaired Users. SPECOM'2004: 9th Conference Speech and Computer 20-22 September, Saint-Petersburg, Russia.

Journal articles (10)

  1. Moustakidis, S., Anagnostis, A., Chondronasios, A., Karlsson, P. and Hrissagis, K. (2018). Excitation-invariant pre-processing of thermographic data. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 232(4), pp. 435–446. doi:10.1177/1748006X18770888.
  2. (2016). Non-destructive inspection of aircraft composite materials using triple IR imaging. IFAC-PapersOnLine, 49(28), pp. 291–296. doi:10.1016/j.ifacol.2016.11.050.
  3. (2014). An Intelligent Methodology for Railways Monitoring Using Ultrasonic Guided Waves. Journal of Nondestructive Evaluation, 33(4), pp. 694–710. doi:10.1007/s10921-014-0264-6.
  4. (2012). A fast SVM-based wrapper feature selection method driven by a fuzzy complementary criterion. Pattern Analysis and Applications, 15(4), pp. 379–397. doi:10.1007/s10044-012-0293-7.
  5. (2012). Feature selection based on a fuzzy complementary criterion: Application to gait recognition using ground reaction forces. Computer Methods in Biomechanics and Biomedical Engineering, 15(6), pp. 627–644. doi:10.1080/10255842.2011.554408.
  6. (2012). SVM-based fuzzy decision trees for classification of high spatial resolution remote sensing images. IEEE Transactions on Geoscience and Remote Sensing, 50(1), pp. 149–169. doi:10.1109/TGRS.2011.2159726.
  7. (2010). A fuzzy decision tree-based SVM classifier for assessing osteoarthritis severity using ground reaction force measurements. Medical Engineering and Physics, 32(10), pp. 1145–1160. doi:10.1016/j.medengphy.2010.08.006.
  8. (2010). SVM-FuzCoC: A novel SVM-based feature selection method using a fuzzy complementary criterion. Pattern Recognition, 43(11), pp. 3712–3729. doi:10.1016/j.patcog.2010.05.007.
  9. (2008). Subject recognition based on ground reaction force measurements of gait signals. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 38(6), pp. 1476–1485. doi:10.1109/TSMCB.2008.927722.
  10. (2008). An adaptive neuro-fuzzy tracking control for multi-input nonlinear dynamic systems. Automatica, 44(5), pp. 1418–1425. doi:10.1016/j.automatica.2007.10.019.