Skander Bdioui

Blind source separation of speech dataset : -Using Independent Component Analysis -Using unsupervised Variational autoencoders

Classification of dysarthric speech : Applying deep learning models for dysarthric speech classification -Extracted acoustic features MFCCs -Developed and trained CNN, RNN

My graduation project consists on the optimisation of the implementation of neural network type (MLP) in FPGA and its use in biomedical field (Classification of breast cancer).

Doing an internship in Farhat Hachad hospital made me gain more knowloadge and capability to deal with basic medical equipments repair and check I’ve dealt with so different devices mainly Syringe driver electrocardiogram,panoramic Xrays.

Develop a web site platform (appointment management between Doctor and Secretary) using NodeJS and Angular.

Setting up Gamma Camera and all the side features (Example how to prepare radioactif substances) and I got the chance to engage with patients in order to prepare them for the procedure.

Preventive and corrective maintenance of medical equipment such as (electrocardiogram ,autoclave computer tomography etc..).I got to work with a team and I obtained the skill to blend with my teammates to provide a good teamwork.