Textbook in PDF format This book aims to mainstream UI/UX design process by explaining latest AI/ML models in a comprehensible way and highlighting case studies on developing intelligent user interfaces for XR systems, human robot interaction, cockpit design and trajectory prediction. The book also discusses the latest standards and guidelines relevant to UI/UX design, layout and equipment list for setting up a lab on intelligent interaction design involving robots, drones and XR systems. Features: Covers a wide array of topics ranging from human factors, computer vision, AR/VR systems, large language models (LLMs) and usability evaluation techniques including statistical hypothesis techniques Discusses latest AI systems such as vision transformers, LLM-based human robot interface and virtual reality-based spacecraft simulation systems Provides a list of freely downloadable software on the covered topics Contains graphical illustrations and a list of quick facts for easy review and recall of basic concepts in each chapter Gives new project ideas on intelligent user interfaces that can be explored by students and early career rsearchers Artificial Intelligence and Machine Learning (AI/ML) and user interface and user experience (UI/UX) design are well-known disciplines with a plethora of offline and online resources. This book aims to mainstream UI/UX design by presenting relevant theories of AI with case studies of intelligent user interfaces from a wide range of applications. The book covers topics ranging from basic human factors, AI/ML, computer vision, natural language processing (NLP), large language models (LLMs), human–robot interaction, cockpit design, trajectory prediction and standardization. Each chapter is carefully drafted to introduce readers to the historical aspects, current trends and relevance to interface or interaction design with a list of five bullet points as quick facts for ease in remembering. None of the topics are discussed in too many details, and all basic concepts and terms are explained to ensure accessibility for readers with different backgrounds. Each chapter contains links to multiple lecture notes and video lectures to dive into the details of individual topics. Chapter 9 on human–robot interaction also discusses sample codes to develop LLM-enabled human–robot interfaces for rovers and manipulators. The intended audience of this book is engineering and design students and faculty members, user interface designers, and product managers who would like to be aware of latest AI/ML without diving into too many theoretical details, and use it for their project or product development