Harnessing AI for Human-Animal Communication - Tapa dura

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Adnène Arbi is an Associate Professor at the National Institute of Applied Sciences and Technology (INSAT). His current research activities are in the field of Applied Mathematics and Artificial Intelligence (AI). Major research projects include modelling of mathematical neural networks and model predictive control. He published more than 34 papers in peer-reviewed international journals since 2014. He edited two books on Neural Networks, Iot, AI, and Data-driven control published in 2025-2026. He is a member of the editorial board of the journals: Journal of Algorithms & Computational Technology, Innovative Applied Mathematics and Computational Sciences, Frontiers in Applied Mathematics and Statistics and Karshi Multidisciplinary International Scientific Journal. He served as a reviewer for more than 100 papers for international journals such as the IMA Journal of Mathematical Control and Information, Mathematics and Computers in Simulation, Chaos, Solitons & Fractals, Journal of Intelligent & Fuzzy Systems, Computational and Applied Mathematics. American Association for Sciences and Technology, Mathematical Methods in the Applied Sciences, Neural Networks, Asian Journal of Control, Neural processing letters, International Journal of Statistical Distributions and Applications, IEEE Transactions on Neural Networks and Learning Systems, IMA Journal of Mathematical Control and Information, JCAS: International Journal of Control, Automation and Systems. He is an Expert/Consultant for the Science for Africa Foundation (2023). He has co-organized two international workshops and conferences since 2022. He is a member of the Laboratory of Engineering Mathematics at Tunisia Polytechnic School, University of Carthage, Tunisia. Besides, he is a member of international member of laboratoire Artificial Intelligence Research and Applications (AIRA), Hassan I University, Settat, Morocco. H-index: 19; Total citations: 721; Expertise: Time scales, Dynamical Systems, Time delay systems, Neural Networks, Model Predictive Control.