Research Area
My research area include machine learning, deep learning, graph representation learning, and feature extraction as well as applications to computer vision (MRI analysis, brain tumor segmentation, hyperspectral image classification,…).
My research area include machine learning, deep learning, graph representation learning, and feature extraction as well as applications to computer vision (MRI analysis, brain tumor segmentation, hyperspectral image classification,…).
Akrem Sellami is currently a Teaching and Research Assistant (ATER) at Telecom Nancy (LORIA Laboratory). He was a Postdoctoral Researcher at the LORIA laboratory between June 2020 and June 2021. The research work focuses on deep learning and graph deep representation learning for medical/satellite images analysis.
He was a Postdoctoral Researcher of the Qarma (Machine Learning Team), which is situated within the Systems and Computer Science Laboratory (Laboratoire d’Informatique et Systèmes, a.k.a. LIS), Aix-Marseille University (AMU). The work of the postdoc is carried out jointly with the Banco (Neural Bases of Communication) team, Institute of Neuroscience of Timone (Institut de Neurosciences de la Timone a.k.a. INT ). This project is funded by the Institute of Language, Communication and the Brain (ILCB)
Post-doc research focuses on understanding the relationship between brain and behavior using machine learning models (deep learning, graph Kernels, multi-view learning) and multi-modal brain images.
Since Oct. 2017, he was a Teaching Assistant (ATER) at IUT Institute, Paris Descartes University. He received the Ph.D degree in Signal, Image, Vision (SIV) from the University of Bretagne Loire, IMT Atlantique, in 2017. From 2014, he enjoyed a research scholarship at the Image and Information Processing department (ITI) at Telecom Bretagne.
He teaches various aspects of Deep Learning, Computer Science, Data Science, Graph Theory, and Computer Systems.
His current research include deep learning, artificial intelligence, multiview learning, functional data analysis, hyperspectral image analysis, and neuroscience.