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"Cutting-Edge Artificial Intelligence Applications" is a comprehensive exploration of the latest advancements in AI and their implications for various industries. The book structured around the key themes discussed at the International Conference on Cutting-Edge Artificial Intelligence Applications, making it a valuable resource for anyone interested in the transformative power of AI. The book divided into seven parts, each focusing on a specific domain where AI is making significant contributions. The first part lays the foundation by exploring the evolution of AI, its theoretical frameworks, and the ethical considerations that accompany its widespread adoption. It provides readers with a solid understanding of the principles driving AI innovation and the societal impacts of these technologies. Subsequent parts delve into AI applications in healthcare, engineering, data science, industry, and smart agriculture. Each chapter within these parts offers a detailed examination of how AI being used to solve real-world problems, from improving medical diagnostics to optimizing manufacturing processes and enhancing agricultural productivity. The book also addresses the challenges and opportunities associated with AI deployment, offering insights into the future directions of AI research and development. One of the unique aspects of this book is its focus on the ethical implications of AI. As AI technologies continue to evolve, issues such as data privacy, algorithmic bias, and the equitable distribution of AI benefits are becoming increasingly important. The book provides a thoughtful analysis of these challenges, encouraging readers to consider the broader implications of AI on society. Whether you are a researcher, a student, or a professional, "Cutting-Edge Artificial Intelligence Applications" offers a wealth of knowledge and practical insights. It designed to be both informative and thought provoking, providing readers with the tools they need to understand and navigate the rapidly changing world of AI.
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Prof. Dr. Mohamed Gouskir : Associate Professor in Computer Science at ENSA Beni Mellal. Ph.D in CS (2015) with expertise in medical image processing and AI. Coordinates "AI & Cybersecurity" program and general chair of the international conference on CEAIA. Published on biomedical imaging and machine learning applications.
Prof. Dr. Ibtissame Aouraghe : Associate Professor specializing in AI and healthcare technologies at ENSA Beni Mellal. Ph.D. (2020) focused on AI-driven detection of neurodegenerative diseases through Arabic handwriting analysis. Combines academic research with industry experience as former Scientific Consultant at Leyton Canada. Published in renowned journals on AI diagnostics.
Prof. Dr. Hanaa Hachimi : Full Professor at ENSA, Ibn Tofail University (Kenitra). Dual Ph.D.s in Applied Mathematics/Computer Science (2013) and System Reliability. President of Moroccan Society of Engineering Sciences, Editor-in-Chief of IJOA, and Director of Systems Engineering Lab. IEEE Senior Member specializing in optimization, cryptography, and AI.
Prof. Dr. Soufiane Belhouideg : Associate Professor in Mechanical Engineering and Deputy Director at ENSA Beni Mellal. PhD from the University of Grenoble, specializing in mechanical and materials. He leads cutting-edge research on 3D printing and smart materials, including applications for COVID-19 medical equipment. He teaches mechanical behaviour, numerical mechanics, and energetics.
Prof. Dr. Belaid Bouikhalene : Professor of Mathematics/Computer Science at Sultan Moulay Slimane University. Director of ENSA Beni Mellal and head of LIMATI research lab (2018-2024). 261+ publications in mathematical applications, AI, and e-learning. Leads multiple international projects (Erasmus+, Tempus) on digital education.
Prof. Dr. Yahya Rokni Associate Professor of Agri-Food Sciences at ENSA Beni Mellal. Holds a Ph.D. in Microbiology, Biochemistry, and Biotechnology, with industry experience as a Quality Assurance Manager in table olive production. Expert in food safety systems (HACCP, ISO 22000) and bioprocess optimization. Supervises student projects in food technology.
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