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(IFTM University)
Dr. Ritu Nagila is an Assistant Professor in the Department of Computer Science & Engineering, School of Computer Science and Applications at IFTM University, Moradabad, Uttar Pradesh. Her academic interests include Artificial Intelligence, Machine Learning, Deep Learning, Big Data Analytics, Medical Image Processing, Data Mining and Intelligent Healthcare Systems. She is dedicated to excellence in teaching, research and student mentorship and has published research papers, contributed book chapters, served as a reviewer for scholarly journals and holds many Indian patent. Dr. Nagila is committed to fostering innovation, practical learning and research-driven education while inspiring students to develop the technical knowledge and professional skills needed to address real-world challenges.
Multimodal Artificial Intelligence: Foundations, Intelligent Applications, and Emerging Trends presents a comprehensive overview of the fundamental concepts, advanced methodologies, practical applications, and emerging developments in multimodal artificial intelligence. The book explores the integration of diverse data modalities, including text, images, audio, video, and sensor information, to enhance intelligent analysis, prediction, classification, and decision-making. It covers a wide range of applications, including healthcare monitoring, clinical decision support, personalized education, student performance prediction, intelligent transportation, autonomous vehicles, smart agriculture, environmental monitoring, industrial automation, cybersecurity, financial fraud detection, e-commerce recommendation systems, and smart energy management. The volume also examines contemporary technologies such as machine learning, deep learning, computer vision, natural language processing, Transformer architectures, attention mechanisms, generative AI, foundation models, and agentic AI. Furthermore, it addresses important challenges associated with multimodal data integration, privacy, security, computational complexity, explainability, interoperability, and responsible AI implementation. This book serves as a valuable academic reference for researchers, faculty members, postgraduate students, research scholars, and industry professionals interested in developing reliable, scalable, and intelligent multimodal AI solutions across diverse application domains.