Researcher Publishes New Book on the UI/UX Design Process With Artificial Intelligence
UI/UX Design has never been as fast-moving a field as it is right now.
With Artificial Intelligence fully embedded in everyday interfaces, machine learning reshaping how systems respond to users, and augmented reality technologies moving from labs into real products, designers and developers are scrambling to keep up. The pace of change is intense, and anyone working in the space knows that standing still for even a few months is enough to feel behind. It is no exaggeration to say the field is going through one of its biggest transformations since the arrival of smartphones.
The problem is that most of the content available on these topics is either too technical for beginners or too shallow for anyone with some actual experience. You find dense academic papers that seem written for PhD candidates, or superficial blog posts that barely scratch the surface of what really matters. This imbalance ends up creating a real barrier for professionals who want to genuinely level up without necessarily becoming data science or machine learning engineering specialists.
That is exactly the gap an Indian researcher decided to address with a new book — and the timing could not be better.
Pradipta Biswas, a Gates Cambridge Scholar and Associate Professor at the prestigious Indian Institute of Science, has just released the book Intelligent User Interface: Usable Artificial Intelligence and Artificial Intelligence for Usability, published by Taylor & Francis. The work sets out to translate the latest advances in intelligent interfaces into a language any tech professional can follow. No data science degree required. 🎯
What Makes This Book Different
Biswas’s approach is to connect three worlds that rarely show up together in the same material: UI/UX Design, Artificial Intelligence, and Extended Reality (XR). The book does not treat these topics as separate areas, and that is precisely the big conceptual shift at the heart of the work. In the real-world practice of designing and developing interfaces today, these three dimensions are increasingly intertwined. A designer working on AR applications needs to understand, at least at a high level, how machine learning models influence interface behavior. And anyone building systems with embedded AI needs to seriously consider how users will perceive, interpret, and trust those model-generated responses.
What Biswas does is offer a bridge between theory and practical application. That means readers will find both the conceptual foundations of Human-Computer Interaction and concrete case studies on the development of intelligent interfaces for extended reality (XR) systems, human-robot interaction, cockpit design, and trajectory prediction. This kind of approach is rare because it requires the author to have command over multiple fields at once and, more importantly, to know how to explain the connections between them in a clear and coherent way.
Receive the best innovation content in your email.
All the news, tips, trends, and resources you're looking for, delivered to your inbox.
By subscribing to the newsletter, you agree to receive communications from Método Viral. We are committed to always protecting and respecting your privacy.
For those unfamiliar with the term, trajectory prediction is the process of forecasting the future positions of agents — such as vehicles or pedestrians — over time. This technology is fundamental to autonomous driving, enabling the system to anticipate movements and ensure safe navigation. XR systems, on the other hand, encompass digital tools, platforms, and technologies that allow users to experience and interact with virtual, augmented, and mixed reality environments through advanced hardware like headsets and smart glasses.
Biswas has an academic track record that justifies this ambition. Beyond the Gates Cambridge Scholarship, where he completed his PhD in Computer Science, he has accumulated years of research in accessibility, user modeling, and adaptive interfaces — topics that sit directly at the center of what AI is transforming today. He is not an outsider trying to ride a wave. He is someone who has spent decades studying exactly the intersections the book sets out to explore, and that shows in how the content is structured. 📚
AI and UI/UX: A Relationship Growing Closer by the Day
One of the central points the book addresses is the relationship between machine learning models and interface design. For a long time, these two fields lived in parallel universes. The design team focused on user experience, the data team trained the models, and the two rarely had structured conversations. The result was interfaces with embedded AI that technically worked but were confusing, unintuitive, and often scared users away rather than engaging them.
Biswas argues that this needs to change, and the book presents frameworks to help designers and developers think together about how machine learning models shape user experience. This ranges from more basic issues like explainability — that is, how the system communicates to the user why it made a particular suggestion or decision — to more complex questions of trust and control, which involve giving users the feeling that they are still in charge even when an algorithm is guiding much of the interaction. These are real challenges faced daily by product teams at companies of all sizes.
The work covers a broad range of subjects that support this integration, including:
- Human factors and their influence on interface design
- Computer vision applied to interactive systems
- Augmented Reality (AR) and Virtual Reality (VR) systems
- Large Language Models (LLMs) and their applications in interfaces
- Usability evaluation techniques
- LLM-based human-robot interfaces
- Virtual reality spacecraft simulation systems
- Vision transformers and other modern AI systems
The field of Human-Computer Interaction has a lot to contribute here, and the book brings back that tradition in a smart way. Classic HCI principles like immediate feedback, user control, and error prevention gain a new layer of complexity when the system in question is based on generative AI or models that learn from user behavior. Understanding how to adapt those principles to this new landscape is one of the most valuable skills a UX professional can develop right now, and that is exactly the kind of thinking Biswas’s work encourages. 🤖
Augmented Reality as the Interface of the Future
Augmented Reality and Extended Reality systems take up a significant portion of the book, and that makes perfect sense. After years of being treated as a promising but still immature technology, AR is finally reaching products with real scale. Smart glasses, industrial applications, corporate training tools, and augmented retail experiences are already a reality at many companies, and the number of professionals who need to design interfaces for these contexts is growing fast.
The challenge of designing for AR is fundamentally different from designing for traditional screens. There is no longer a fixed rectangle where the interface lives. Digital content blends with the user’s physical environment, and that creates a whole set of new UI/UX Design problems that conventional practices simply do not solve. How do you ensure readability in environments with variable lighting? How does the user navigate virtual elements without losing awareness of what is happening around them? How can Artificial Intelligence help adapt the interface in real time based on the physical context detected by the device’s camera or sensors? These are complex questions, and the book tackles each one of them with a depth rarely found in other materials on the topic.
Beyond that, Biswas connects AR interface design with the principles of Human-Computer Interaction, showing how classic research on perception, attention, and cognitive load applies directly to this new type of experience. This is especially useful for designers who have a solid foundation in traditional UX and want to transition into augmented reality projects without having to start from scratch. The continuity between what is already known and what is new comes through clearly throughout the entire narrative of the book. 🕶️
A Book Also Designed as a Practical Tool
Beyond its solid conceptual foundation, the book includes elements that make it a practical tool for everyday use. The work features graphic illustrations throughout the chapters and a list of quick facts to make it easier to review and retain the key concepts in each section. This goes a long way for anyone who needs to reference the material quickly during a project or study session.
Another important differentiator is that Biswas provides a list of free software available for download related to the topics covered in the book. This kind of supplementary resource makes a huge difference for anyone who wants to get hands-on and experiment in practice with what they learned from the reading. Theory comes alive when you can open a tool and test a concept right then and there.
The book also introduces new project ideas around intelligent interfaces that can be explored by students and early-career researchers. This curation of research and experimentation opportunities shows a genuine concern for shaping the next generation of professionals in the field, not just informing the current one.
The primary target audience for the work includes engineering and design students and professors, interface designers, and product managers who want to understand the latest advances in AI and machine learning without having to dive into excessive theoretical detail — but with enough depth to apply that knowledge to their projects and product development.
The book also discusses the latest standards and guidelines relevant to areas like UI/UX design and layout, and details the equipment needed to set up an intelligent interaction design lab involving robots, drones, and XR systems. This is particularly valuable for universities and research centers that are building out their spaces to keep up with these new technological demands.
Who Is Pradipta Biswas
To understand the significance of this publication, it is worth knowing a bit more about the author’s background. Pradipta Biswas is an Associate Professor in the Department of Design and Manufacturing and an Associate Professor at the Robert Bosch Centre for Cyber Physical Systems at the Indian Institute of Science. His work extends well beyond the academic environment.
He was elected Vice Chair of ITU Study Group 9 at the International Telecommunication Union, and has also served as co-chair of the Intersector Rapporteur Group on Audiovisual Media Accessibility (IRG AVA) and the Focus Group on Smart TV, both at the ITU. These positions place Biswas in a role of direct influence over the international standards that govern how interfaces and audiovisual media are designed globally.
During his PhD in Computer Science at Cambridge, funded by the Gates Cambridge Scholarship (class of 2006), Biswas explored visual and auditory perception, rapid aiming movements, and problem-solving strategies in the context of human-machine interaction. He also invented new algorithms, including applications for eye-tracking technology. Among the technologies he has patented is an interactive Head-Up Display controlled by gaze and gestures.
Since returning to India, he has expanded his work in eye-tracking technology through a collaboration with the Indian Air Force. Biswas also led a project to design a virtual reality cockpit for India’s first crewed space mission and was one of five Indian researchers selected to conduct human-machine interaction studies on the International Space Station during the Axiom 4 mission. He also led the country’s first-of-its-kind toy hackathon, focused on helping children with severe disabilities communicate through gaze-controlled interfaces. 🛰️
The release of Pradipta Biswas’s book comes at a time when the tech industry is desperately searching for professionals capable of working at the intersection of design, AI, and new forms of interaction.
This is not just a matter of intellectual curiosity. Companies of all sizes are investing heavily in intelligent interfaces, and the shortage of people who understand both the design side and the AI model side is a real bottleneck in the market. A work that helps fill that gap, especially in an accessible and well-grounded way, has immediate practical value for anyone already in the field or looking to break into it.
What sets materials like this apart from others that try to cover the same ground is precisely the depth with which the connections between disciplines are explored. UI/UX Design, Artificial Intelligence, Augmented Reality, and machine learning models are not treated as isolated topics in an extended table of contents. They appear in constant dialogue, reflecting exactly the way these technologies coexist in the real products being built today. That internal coherence is the work’s greatest strength, and it is likely what will make it circulate widely across design and development communities in the coming months. 🚀
