New book by Pradipta Biswas connects AI, UI/UX, and intelligent interfaces
The UI/UX design process is getting more and more complex, and it’s no exaggeration to say the field has entered a new phase. What used to revolve around screens, flows, and colors now involves Artificial Intelligence, XR systems (extended reality), human-robot interaction, and even space simulations in virtual reality. This shift is exactly what the new book by researcher Pradipta Biswas aims to translate for designers, engineers, and product managers who want to understand the impact of AI on interfaces without having to dive into heavy mathematical theory.
Published by Taylor & Francis under the title Intelligent User Interface: Usable Artificial Intelligence and Artificial Intelligence for Usability, the book sets out to demystify the latest AI and machine learning models and show, through real case studies, how to design intelligent interfaces in different contexts: XR, robot interaction, cockpit design, and trajectory prediction. Instead of staying only in theory, the book brings practical examples, lists of free software, and project ideas that can be explored by students and early-career researchers.
The central focus is clear: explaining how AI can make interfaces more usable and, at the same time, how to think about usability when intelligent models are running in the background. This two-way view is one of the book’s main differentiators. Biswas has worked for years on the frontier between human factors, computer vision, augmented and virtual reality, and human-computer interaction.
Who is Pradipta Biswas, and why this book matters
Pradipta Biswas is not new to this topic. He is an Associate Professor in the Department of Design and Manufacturing at the Indian Institute of Science (IISc), and he also works as an associate faculty member at the Robert Bosch Centre for Cyber Physical Systems, a major reference in cyber-physical systems research. Beyond his academic career, he has a strong track record of participation in international standardization bodies related to telecom and accessibility.
Biswas was elected vice-chairman of the ITU Study Group 9, a study group of the International Telecommunication Union (ITU) focused on transmission and TV, and he also served as Co-Chair of the Intersector Rapporteur Group on Audiovisual Media Accessibility (IRG AVA) and the Focus Group on Smart TV. In practice, this means he helped steer global discussions on audiovisual accessibility, smart TV, and technical standards that directly impact how interfaces are designed for different audiences.
His connection with Cambridge also carries a lot of weight. During his PhD in Computer Science at the University of Cambridge, Biswas researched visual and auditory perception, rapid pointing movements, and problem-solving strategies in human-computer interaction contexts. During this period, he developed new algorithms for eye-tracking technology, including solutions applied to gaze- and gesture-controlled Head Up Displays, a technology with potential applications in aviation, automotive, and assistive systems.
After returning to India, he expanded this work in partnership with the Indian Air Force and began exploring more immersive applications. Biswas led the design of a virtual reality cockpit for India’s first crewed spaceflight mission and joined a select group of five researchers chosen to study human-machine interaction on the International Space Station, in research linked to the Axiom 4 mission. He also coordinated a pioneering toy hackathon focused on creating adapted toys that allow children with severe disabilities to communicate using eye-controlled interfaces.
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This background sets the stage for the book: it is not just a collection of concepts, but a synthesis of experiences in the lab, product development, participation in space missions, and the building of international standards.
What the book covers: from cockpits to space VR
The book’s content is broad, but guided by a clear thread: how to design intelligent interfaces that are both usable and explainable in complex contexts. Key topics include:
- Human factors applied to intelligent systems, considering cognitive limits, perception, reaction time, and mental workload.
- Computer vision and how vision algorithms are used to interpret gestures, gaze, body position, and objects in the environment.
- Augmented reality (AR), virtual reality (VR), and XR systems in general, with a focus on layout, visual comfort, and spatial navigation.
- Large Language Models (LLMs) as the foundation for conversational interfaces between humans and robots.
- Usability evaluation methods adapted to scenarios involving AI, robots, and immersive environments.
The book dives deep into state-of-the-art AI models, such as vision transformers used for image and video analysis, and LLM-based human-robot interfaces, where the robot understands complex natural language commands, responds contextually, and adjusts its behavior based on interaction history.
Another interesting point is the focus on space simulation in VR. Biswas discusses how virtual reality can be used to create spacecraft simulators, testing interface design, mission procedures, and interaction strategies in scenarios that are difficult or impossible to reproduce physically. This ranges from organizing panels and controls to how alerts and instructions are displayed in emergency situations.
Trajectory prediction and safe navigation in autonomous systems
One of the book’s key concepts is trajectory prediction, which is essential for autonomous vehicles, mobile robots, and systems that share space with people. Put simply, trajectory prediction is about estimating where an agent will be in the future – whether that agent is a car, a drone, a warehouse robot, or even a pedestrian on a sidewalk.
In applications like autonomous driving, these models help the system anticipate movements, avoid collisions, and plan safer routes. Biswas emphasizes that this is not just a technical challenge, but also an interface design problem. The user – driver, operator, or pedestrian – needs to clearly understand what the system is predicting and what action it will take next.
The book explores ways to make this prediction visible and understandable through UI:
- Visualization of future routes on navigation displays.
- Use of colors to indicate risk levels or proximity to obstacles.
- Smooth animations to show acceleration, braking, or evasive maneuvers.
- Integration with XR systems to project trajectories into the user’s field of view.
When people understand where the system intends to go and why, trust increases. This combination of algorithmic prediction and visual communication is a recurring theme in the book, especially in critical environments like aviation, industrial logistics, and healthcare.
XR, mixed reality, and space as part of the interface
Another strong pillar of the book is the analysis of XR systems – an umbrella term that includes augmented, virtual, and mixed reality. Biswas describes how these technologies use headsets, smart glasses, and other devices to blend digital and physical environments, turning space into a large interactive interface.
In the book, XR is addressed from both technical and design perspectives:
- How to position 3D elements in the field of view without causing fatigue or motion sickness.
- How to ensure that digital overlays do not block important real-world obstacles.
- How to calibrate depth, object size, and distance for different user profiles.
- How to use XR for training, simulation, and operation of complex systems such as cockpits and control centers.
The book also covers the equipment needed to build an intelligent interaction lab with robots, drones, and XR systems. This ranges from configuring sensors and cameras to selecting software for prototyping and experience evaluation, including a list of free tools that can be used in research and teaching.
LLMs, computer vision, and new intelligent interfaces
When it comes to artificial intelligence, Biswas goes far beyond traditional models. The book details how Large Language Models (LLMs) and vision transformers are changing the way interfaces are built, especially in human-robot interaction and immersive environments.
Some examples discussed in the book include:
- Conversational interfaces for robots, where people use natural language to instruct and correct the system.
- VR systems for space simulation, where AI helps generate scenarios, events, and behaviors.
- Computer vision applications that track gaze, gestures, and body position to control touchless interfaces.
These systems demand a UI/UX approach where designers understand at least the basics of:
- How the model is trained and what kind of data it consumes.
- What limitations, uncertainties, and potential biases exist.
- How to explain, in the interface, what the AI is doing.
The book reinforces that the interface needs to show just enough for users to trust it and feel in control, without dumping technical information that only gets in the way. To support this, Biswas presents explainability techniques designed from a UX perspective, not just from an AI engineering point of view.
Didactic structure, illustrations, and projects to explore
Beyond offering an up-to-date technical overview, the book was designed to be didactic and practical. Each chapter brings:
- Graphic illustrations that help visualize concepts and system architectures.
- A list of quick facts for fast review of the main points.
- Project ideas that can be used in undergraduate and graduate courses.
- References to free software related to the topic of the chapter.
The target audience is very clear: engineering and design students, faculty members, UI designers, UX specialists, and product managers who want to understand the latest in AI and machine learning applied to interfaces, without having to break down every mathematical detail of the models. The emphasis is on how to apply this knowledge in real projects and products.
For anyone working or planning to work with intelligent interfaces, robotics, XR, or advanced usability, Pradipta Biswas’s book works as an updated map of this new territory where UI/UX, AI, and physical systems blend all the time. It offers an integrated view of technology and user experience, built by someone who has tested these ideas in practice, from academic labs to space missions and defense-related projects.
