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Hacene Karrad has two years of work experience. In 2018, they worked as a Computer Vision Engineer/Data Scientist at Alteia. Hacene also held an Intern Position in Computer Vision and Machine Learning on GCP at Veolia France, where their main goal was to perform weakly supervised instance segmentation of waste conveyors in order to mechanically separate different types of waste in a sorting center. Hacene used convolutional neural networks that were trained on Google Cloud Platform.

Hacene Karrad obtained a Licence in Electrical and Electronics Engineering from Universit\u00e9 M'Hamed Bougara de Boumerdes in 2012-2015. Hacene then earned a Master 2 (M2) in Computer Engineering from the same university in 2015-2017. Hacene concluded their education history with a Master 2 (M2) in Syst\u00e8me Embarqu\u00e9s et Traitement de l'Information from Paris-Sud University (Paris XI) in 2017-2018.