Dr. Mahdi Amina

Research Associate

School of Engineering

Computing, Engineering & Physical Sciences Intelligent Systems Laboratory, CM234

Mahdi is a research associate currently working within Intelligent Systems group dealing with various interdisciplinary projects, mainly related to applying hybrid artificial intelligence and pattern recognition techniques in various fields of science. Mahdi has extensive background in embedding machine learning schemes for medical and microbiological applications, as well as energy sector both in Italy and UK.

Mahdi is research active in Intelligent Systems.

Full Profile

Mahdi commenced his career as Research Associate at UCLAN in 2015, succeeding to completion of a research fellowship in University of Genoa-Italy, where he worked toward real-time monitoring techniques for healthcare applications with sensory Human Interface Devices (HID).

Mahdi is currently involved in a number of funded projects concerning applications of artificial intelligence and pattern recognition within medical and biomedical field, as well as autonomous systems in aerospace and maritime sector. His PhD, which was focused on Hybrid Soft Computing Techniques for dynamic system modelling. 

His research interests mainly consist of Artificial Intelligence, Pattern recognition, Machine Learning, Decision support systems and Applied signal/image processing.



  • PostGrad Certificate – Leadership & Management, City University – London/UK, 2012
  • Ph.D - Machine Learning and Computational Intelligence, University of Westminster – London/UK, 2011
  • M.Sc - Broadband & High Speed Data Communication, University of Westminster – London/UK, 2007
  • BEng - Communication Engineering, Ferdowsi University – Mashhad/Iran, 2005


Teaching Activities and Responsibilities


  • Calculus and Linear System Tutor for Aerospace Engineering undergraduate course



    M. Amina, F.Masulli, S. Rovetta, “Genetic Algorithm-Based Neural Error Correcting Output Classifier” 2014 IEEE Symposium Series on Computational Intelligence (SSCI), Orlando, USA, Dec 2014,pp. 62-69, ISBN 978-1 -4799-4512-2

    M. Amina, V. S. Kodogiannis, I. Petrounias, and D. Tomtsis, "A hybrid intelligent approach for the prediction of electricity consumption," International Journal of Electrical Power & Energy Systems,Elsevier,vol.43,pp.99-108,2012.

    V.S. Kodogiannis, M.Amina and I.Petrounias, " A Clustering-Based Fuzzy Wavelet Neural Network Model for Short Term Load Forecasting" Inter'l. J. Neural Network Systems 23, World Scientific, DOI: 10.1142/S012906571350024X, 2013

    M. Amina, V. S. Kodogiannis, J. N. Lygouras, and G. J. E. Nychas, "Identification of the Listeria monocytogenes survival curves in UHT whole milk utilising linear local wavelet neural networks," Elsevier, Expert Systems with Applications, vol.39,pp.1435-1450, 2012