Ahmed Kharrat received the MS Degree in Computer Science (2007) from the National Engineering School of Sfax (Tunisia). Currently, he is a PhD student at Faculty of Economics and Management of Sfax (Tunisia). Her main research interests include Cognitive Informatics and Image Processing.

- Kharrat, A., Gasmi, K., Ben Messaoud, M., Benamrane, N., & Abid, M. (2013). Medical Image Classification Using an Optimal Feature Extraction Algorithm and a Supervised Classifier Technique. In Y. Wang (Ed.), Advances in Abstract Intelligence and Soft Computing (pp. 43-56). Hershey, PA: Information Science Reference. doi:10.4018/978-1-4666-2651-5.ch004

- Ahmed Kharrat, Mohamed Ben Messaoud and Mohamed Abid," Brain tumour diagnostic segmentation based on optimal texture features and support vector machine classifier”, Int. J. Signal and Imaging Systems Engineering, Vol. 7, No. 2, pp. 65-74, 2014.

- Kharrat, A., & Abid, M. (2014). Toward Efficient Segmentation of Brain Tumors Based on Support Vector Machine Classifier Through Optimized RBF Kernel Parameters and Optimal Texture Features. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 8(2), 15-33. doi:10.4018/IJCINI.2014040102

- Ahmed Kharrat, Mohamed BENHLIMA, Mounir BENAYED (2015)" Feature selection based in hybrid optimisation method for IRM classification”, 15^th IEEE International Conference on Intelligent Systems Design and Applications (ISDA 2015), December 14-16, 2015 in Morocco, 446-451.

- Ahmed Kharrat, Mahmoud NEJI (2017) “A Hybrid Feature Selection For MRI Brain Tumor Classification”, In: Abraham A., Haqiq A., Muda A., Gandhi N. (eds) Innovations in Bio-Inspired Computing and Applications. IBICA 2017. Advances in Intelligent Systems and Computing, LNCS, vol .735, pp. 329-338. Springer, Cham (2018). https://doi.org/doi.org/10.1007/978-3-319-76354-5-30