This book offers a comprehensive introduction and in-depth exploration of the latest advancements in multimodal imaging, physics-informed AI models, explainable artificial intelligence (XAI), and large language models (LLMs). The authors delve into their practical applications in physical inspection and diagnostics across the electronics and biomedical fields, highlighting how these leading-edge technologies are transforming fault detection, defect analysis, and intelligent decision-making. Additionally, this book explores the integration of AI-driven imaging with virtual reality (VR) and simulation-based learning, providing insights into real-time diagnostics, automated inspection, and interactive education. Through detailed discussions, case studies, and emerging trends, this book serves as a vital resource for researchers, engineers, and professionals seeking to enhance imaging-based AI systems for precision inspection and diagnostics.

• Provides a comprehensive and integrated approach to next-generation imaging and AI-driven decision-making

• Includes use cases, case studies, and deployment strategies to help professionals implement real, AI-driven imaging

• Discusses how AI models can be validated and optimized for regulatory compliance in healthcare and electronics

Navid Asadi is an Associate Professor in the Electrical and Computer Engineering Department at the University of Florida with an affiliation to the Materials Science and Engineering department. He investigates novel techniques for electronics inspection and assurance, system and chip level decomposition and security assessment, anti-reverse engineering, 3D imaging, invasive and semi-invasive methods, supply chain security, etc. Dr. Asadi is director of the Security and Assurance (SCAN) lab house to more than $12M advanced imaging and characterization equipment. He also serves as the associate director of the Florida Semiconductor Institute (FSI), and the Microelectronics Security Training (MEST) center which is a multi-million dollar program to train and reskill the professional engineers in the area of security. Dr. Asadi  has received his NSF CAREER award in 2022 and several best paper awards from IEEE International Symposium on Hardware Oriented Security and Trust (HOST) and the ASME International Symposium on Flexible Automation (ISFA). He was also winner of D.E. Crow Innovation award from University of Connecticut. He is also founder and the general chair of the IEEE Physical Assurance and Inspection of Electronics (PAINE) Conference. His projects are sponsored by various government agencies and industry including but not limited to NSF, AFRL, AFOSR, ONR, SRC, Meta, Cisco, Analog Devices, etc.

Shajib Ghosh is a Postdoctoral Associate in the Department of Electrical and Computer Engineering at the University of Florida, where he conducts research in the Security and Assurance (SCAN) lab under the supervision of Dr. Navid Asadi. He received his Ph.D. and M.S. in Electrical and Computer Engineering from the University of Florida and his B.Sc. in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology (BUET). His research lies at the intersection of artificial intelligence, intelligent physical inspection, computational imaging, and microelectronics reliability and assurance, with particular emphasis on machine learning and deep learning, computer vision, physics-informed machine learning, multimodal AI, and large language and vision-language models. His work focuses on developing AI-enabled methods for nondestructive inspection, reconstruction, defect detection and characterization, failure analysis, and physical assurance of electronic devices and advanced semiconductor packages. He is particularly interested in combining measurement physics with data-driven and generative AI approaches to develop reliable, explainable, and automated inspection and decision-support systems for next-generation microelectronics.