Nowadays with the growth of material data from experiments and simulations, a huge amount of data are available which present a new challenge in term of how to process these amount of data. This state requires a new and efficient approach that can deal with both: big data analysis and prediction models. Thanks to the recent development of the Artificial Intelligence (AI) and Machine Learning, which significantly contributed to the field of material characterization in various ways. Enhancing our ability to understand, analyse, and optimize materials. Some of the key contributions we can mention: Predictive modelling, Data analysis and pattern recognition, Image and spectroscopy analysis, Property optimization, Material quality control, Accelerated materials discovery, etc. Overall, AI and ML are transformative tools for material characterization, offering improved accuracy, efficiency, and insights that can lead to the development of advanced materials with enhanced properties for a wide range of applications. This presentation is an attempt to underline the recent advanced in the application of AI and Machine Learning in the above subjects.
David BASSIR is as Professor at the French University of Technology UTBM and also a Senior Research at Borelli Center at the ENS- Paris Saclay University. Previously, he was the dean of IUT at the University of Lorraine (France), Consult for Science and Technology at the French Embassy (China), General Director of Research at the Ecole Spéciale des Travaux Publics, du Batiment et de l'Industrie (Paris) and Space Craft engineer at GECI Technology in different space agencies such as Arianespace and Astrium Group. He joined the Mechanical Department of the UTBM as Associate professor in 2001 and the Chair Aerospace Structures in 2008 at Technical University of Delft as visiting professor. He holds a Master and a PhD degree in structural optimization from the University of Franche-Comté (France). He has published more than 150 papers in journals, books and conference proceedings, including more than 45 articles in indexed journals. He is the Editor-in-Chief of the Int. journal IJSMDO (Scopus, EI) that is published by EDP Sciences.