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Books in Computer science

The Computing collection presents a range of foundational and applied content across computer and data science, including fields such as Artificial Intelligence; Computational Modelling; Computer Networks, Computer Organization & Architecture, Computer Vision & Pattern Recognition, Data Management; Embedded Systems & Computer Engineering; HCI/User Interface Design; Information Security; Machine Learning; Network Security; Software Engineering.

  • Federated Learning in Metaverse Healthcare

    Personalized Medicine and Wellness
    • 1st Edition
    • September 12, 2025
    • Shubham Mahajan + 1 more
    • English
    Federated Learning in Metaverse Healthcare: Personalized Medicine and Wellness explores the integration of the metaverse with healthcare, offering immersive experiences and personalized care. The book introduces federated learning, emphasizing its advantages over traditional centralized machine learning in healthcare. It provides a historical context and discusses the technological advancements that led to the emergence of metaverse healthcare. Privacy-preserving methods crucial for protecting sensitive healthcare data within federated learning environments are also examined, underscoring the importance of secure communication protocols. Other important points include the transformation of healthcare delivery through virtual environments, remote consultations, and immersive experiences.The role of telemedicine in facilitating remote diagnostics and consultations via virtual platforms, and the applications of augmented reality wearables for real-time health monitoring and wellness tracking are detailed. Additionally, the book discusses federated learning's ability to deliver personalized treatment plans tailored to individual patient needs, its role in predictive modeling for disease risks and prevention, as well as virtual health coaches offering personalized guidance for wellness management. The challenges and ethical dilemmas of metaverse healthcare and federated learning, along with potential solutions, are also considered.

  • Quantum Computational AI

    Algorithms, Systems, and Applications
    • 1st Edition
    • September 11, 2025
    • Long Cheng + 2 more
    • English
    Quantum Computational AI: Algorithms, Systems, and Applications is an emerging field that bridges quantum computing and artificial intelligence. With rapid advancements in both areas, this book serves as a vital resource, capturing the latest theories, algorithms, and practical applications at their intersection. It aims to be both informative and accessible, making it perfect for academics, researchers, industry professionals, and students eager to lead in these technologies. The book explores quantum algorithms, system design, and demonstrates real-world applications across various sectors. It provides a comprehensive understanding of how quantum principles can advance AI, revealing unprecedented possibilities and benefits.

  • Metaverse in the Healthcare Industry

    Potential Applications, Tools, and Techniques
    • 1st Edition
    • September 6, 2025
    • Hemachandran Kannan + 4 more
    • English
    Metaverse in the Healthcare Industry: Potential Applications, Tools, and Techniques explores the intersection of rapidly evolving metaverse technology and its implications for the healthcare sector. The book provides a comprehensive overview of virtual and augmented reality, artificial intelligence, and other immersive technologies that have gained significant attention within the context of the metaverse in healthcare. It emphasizes how these technologies can revolutionize healthcare by enabling virtual clinics, patient education, remote medical training, therapeutic interventions, and much more. By bringing together diverse perspectives, it contributes to the ongoing discourse on the future of healthcare delivery and innovation.This book also delves into technical aspects of metaverse development and its integration with existing healthcare systems. It discusses ethical considerations and challenges associated with implementing metaverse technologies in healthcare settings. Additionally, it highlights the potential to reshape the healthcare landscape by fostering innovation, improving patient care, and revolutionizing medical training and research. Readers will gain insights into applications, tools, and techniques for leveraging the metaverse to create more effective and accessible healthcare solutions.

  • Applied Mathematical Modeling for Biomedical Robotics and Wearable Devices

    • 1st Edition
    • August 29, 2025
    • S. Sountharrajan + 3 more
    • English
    Applied Mathematical Modelling for Biomedical Robotics and Wearable Devices delves into the innovative convergence of mathematical frameworks and biomedical engineering. The book begins by exploring how advanced mathematical modelling underpins the development and optimization of robotic systems and wearable technologies tailored for medical applications. With a strong emphasis on practical implementation, it serves as a bridge between theoretical concepts and real-world engineering challenges in the healthcare sector. Readers will gain insights into the transformative role of mathematical techniques that drive precision, functionality, and human-centric design in cutting-edge medical technologies.The book also covers interdisciplinary applications, integrating domains like biomechanics, sensor technology, and data analytics. By highlighting case studies and real-world scenarios, it showcases practical advancements in wearable devices that monitor health metrics and robotic systems that assist in surgical procedures.

  • Minds, Machines, and Misinformation

    Decoding Bias, Algorithms, and Trust
    • 1st Edition
    • August 11, 2025
    • Don Donghee Shin
    • English
    Algorithms have become the key organizer through which power is enacted in our society. A huge amount of data regarding our daily routines are monitored and analyzed to make recommendations that manage, control, and lead our behaviors in everyday life. AI, Humans, and Misinformation: How Does AI Alter Human Behavior and How Do Humans Influence Algorithmic Misinformation? is a guide to understanding the dynamics of AI and misinformation in human contexts by addressing meaningful questions—How does AI alter human behavior and how do humans influence algorithmic decision-making? In answering these questions, this book examines the role of misinformation, disinformation, and fake news, and shows readers how to develop AI methods and algorithms that combat misinformation by using AI design choices that provide users and developers alike with meaningful control over AI. This book brings together various perspectives on algorithms into an integrated conceptual framework, and provides a broad socio-technical analysis, addressing critical and ethical issues of misinformation and fake news. The book offers a compelling insight into the misinformation phenomenon and the future of AI-based society. Readers will find an integrated technical analysis of the logic and social implications of algorithmic processes. Reporting from the cutting edge of critical technical methods and research, the result is useful and constructive for developing the relations between algorithms and humans. This is an imperative methodology for understanding what is at stake as industry and government use AI to reshape the world.

  • Motion Control of Soft Robots

    • 1st Edition
    • July 30, 2025
    • Wenyu Liang + 3 more
    • English
    Motion Control of Soft Robots provides an overview of the general concepts and most recent technological updates in soft robot motion control. The book provides systematic coverage of theoretical and practical aspects in system modeling and motion control strategies, presenting novel ideas, methods, and future outlook related to motion control of soft actuators and robots, including model-based control, model-free control, and bioinspired control. This book is useful for researchers, engineers, and students of robotics who can expect to learn how to design and implement various techniques to obtain solutions to control problems in soft robot control and nonlinear system control.

  • Quantum Health AI

    The Revolution of Medicine, Public Health, and Global Health by Quantum Computing-Powered Artificial Intelligence
    • 1st Edition
    • July 30, 2025
    • Dominique J. Monlezun
    • English
    Quantum Health AI: The Revolution of Medicine, Public Health, and Global Health is the first comprehensive book defining the transformation of the global health ecosystem by the fusion of our most powerful technologies—quantum computing and artificial intelligence—while defending an actionable human-centred approach to doing so responsibly, equitably, and sustainably. We can continue to watch wars, diseases, poverty, polarization, cyber-crime, and climate change only worsen. Our strongest technologies can remain centralized in a small number of companies and countries for their profit and power. Or we can cooperatively put quantum AI to work for the health of all of us, by better managing this technology’s overarching strategic competition between democracies and autocracies, along with the public and private sectors (balancing human security with national security, economic growth with household livelihoods, individual rights with the common good). This book draws on the decade plus of original research and first-hand perspective of the world’s first triple doctorate-trained physician-data scientist and AI ethicist. It unpacks the history, science, values, and political economics framing and driving quantum AI (including its physics, metaphysics, ethics, governance, computing, sensing, communication, materials, and security), the global health ecosystem (healthcare systems, public health agencies, biotechnology companies, and development institutions), and their growing integration, wins, and challenges. This one-stop book provides a global, inclusive, and practical guide for understanding and shaping these societal and technological trends. It thus empowers health, technology, and policy students, practitioners, professionals, researchers, and leaders in organizations, universities, companies, and governments—ultimate... to make and maintain the human-centred quantum AI safeguarding and advancing humanity’s health, home, and future.

  • Data Science for Teams

    20 Lessons from the Fieldwork
    • 1st Edition
    • July 30, 2025
    • Harris V. Georgiou
    • English
    Managing human resources, time allocation, and risk management in R&D projects, particularly in Artificial Intelligence/Machine Learning/Data Analysis, poses unique challenges. Key areas such as model design, experimental planning, system integration, and evaluation protocols require specialized attention. In most cases, the research tends to focus primarily on one of the two main aspects: either the technical aspect of AI/ML/DA or the teams’ effort, or the typical management aspect and team members’ roles in such a project. Both are equally import for successful real-world R&D, but they are rarely examined together and tightly correlated. Data Science for Teams: 20 Lessons from the Fieldwork addresses the issue of how to deal with all these aspects within the context of real-world R&D projects, which are a distinct class of their own. The book shows the everyday effort within the team, and the adhesive substance in between that makes everything work. The core material in this book is organized over four main Parts with five Lessons each. Author Harris Georgiou goes into the difficulties progressively and dives into the challenges one step at a time, using a typical timeline profile of an R&D project as a loose template. From the formation of a team to the delivery of final results, whether it is a feasibility study or an integrated system, the content of each Lesson revisits hints, ideas and events from real-world projects in these fields, ranging from medical diagnostics and big data analytics to air traffic control and industrial process optimization. The scope of DA and ML is the underlying context for all, but most importantly the main focus is the team: how its work is organized, executed, adjusted, and optimized. Data Science for Teams presents a parallel narrative journey, with an imaginary team and project assignment as an example, running an R&D project from day one to its finish line. Every Lesson is explained and demonstrated within the team narrative, including personal hints and paradigms from real-world projects.

  • Theoretical Foundations of Quantum Computing

    • 1st Edition
    • July 25, 2025
    • Daowen Qiu
    • English
    Theoretical Foundations of Quantum Computing is an essential textbook for introductory courses in the quantum computing discipline. Quantum computing represents a paradigm shift in understanding computation. This textbook delves into the principles of quantum mechanics that underpin this revolutionary technology, making it invaluable for undergraduate and graduate students in computer science and related fields. Structured into eight meticulously crafted chapters, it covers everything from the historical context of quantum computing to advanced theories and applications. The book includes core topics such as basic models, quantum algorithms, cryptography, communication protocols, complexity, and error correction codes.Each chapter builds upon the last, ensuring a robust understanding of foundational concepts and cutting-edge research. It serves as both a foundational resource for students and a comprehensive guide for researchers interested in quantum computing. Its clarity makes it an excellent reference for deepening understanding or engaging in advanced research.

  • Data-Driven Insights and Analytics for Measurable Sustainable Development Goals

    • 1st Edition
    • July 24, 2025
    • Tilottama Goswami + 2 more
    • English
    Data-Driven Insights and Analytics for Measurable Sustainable Development Goals discusses the growing imperative to understand, measure, and guide actions using data-driven insights. The SDGs encompass a broad spectrum of global challenges, from eradicating poverty and hunger to preserving the environment and fostering peace. To address these issues, one should be able to measure and analyze progress. This book bridges the gap between qualitative and quantitative assessments, recognizing that goals are not solely about numbers but also encompass complex social, environmental, and economic dynamics. By merging data science with qualitative analysis, readers can explore how SDGs intersect and influence each other.The book provides readers with an understanding of how to effectively leverage data science models and algorithms using descriptive analytics, allowing us to assess the current state of SDG performance and offering valuable insights into where we stand on these critical goals. Prescriptive analytics guides actions by offering actionable recommendations, while predictive analytics anticipates future trends and challenges, helping us navigate our path toward the SDGs effectively.

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