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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.

  • AI and Data Science in Medical Research

    • 1st Edition
    • May 1, 2026
    • Olfa Boubaker
    • English
    AI and Data Science in Medical Research focuses on the integration of AI and data science into medical research, highlighting their impact on drug discovery, medical imaging, diagnostics, and genomic medicine. The book addresses the acceleration of therapeutic compound discovery and optimization of drug development pipelines through AI. The volume also discusses advancements in medical imaging, including early disease detection and neuroimaging. Additionally, it covers the application of AI in genomic medicine, offering insights into personalized treatment strategies.The volume concludes with an examination of AI's role in public health surveillance, particularly in disease detection and epidemiological research.

  • Foundations of Human-Computer Interaction

    Designing for Cognitive Alignment
    • 1st Edition
    • May 1, 2026
    • Robert Atkinson
    • English
    Foundations of Human-Computer Interaction: Designing for Cognitive Alignment covers the fundamentals of human-computer interaction (HCI), usability, and user-centred design. It provides a holistic and engaging exploration of HCI by integrating historical perspectives, behavioural and cognitive insights, neuroscientific principles, and advanced technological tools. This comprehensive approach ensures graduate students and undergraduate not only understand the theoretical frameworks but also see their practical applications in real-world scenarios. The pedagogy emphasizes interactive learning, critical thinking, and iterative design processes, making the content accessible and engaging for both novices and advanced learners. This book also discusses contemporary challenges such as dark patterns and surveillance capitalism, and offers an understanding of the ethics and code of conduct to enable the student and practitioner take their thinking and designs forward into the marketplace in a responsible way.

  • Distributed AI in the Modern World

    Technical and Social Aspects of Interacting Intelligent Agents
    • 1st Edition
    • May 1, 2026
    • Andrei Olaru + 3 more
    • English
    Distributed AI in the Modern World: Technical and Social Aspects of Interacting Intelligent Agents presents state-of-the-art insights into the various forms of distribution of artificial intelligence, with practical application instances. Sections provide readers with practical solutions at an architectural level, with solutions presented on the distribution of the learning process and the utilization of machine learning models in a distributed system, tools that enable the distribution and interaction of artificial learning entities, how multi-agent systems and machine learning can be combined, the physical embodiment of intelligent agents, and the interaction of intelligent computing units bound to physical space.Following sections emphasize the challenges that are common to all scenarios and solutions that apply in a wider range of cases. This book does not analyze the internal workings of machine learning models (for instance, in the case of multi-agent reinforcement learning), but instead provides readers with an overview of the challenges brought by the need of artificially intelligent entities to interact with other entities and with their environments, along with practical solutions at an architectural level.

  • AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice

    • 1st Edition
    • May 1, 2026
    • Olfa Boubaker + 1 more
    • English
    AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice examines the transformative role of AI and data science in improving diagnosis, treatment, and healthcare delivery. It shows how machine learning, deep learning, and advanced signal and image analysis enable breakthroughs in genomics, multi-omics integration, biomedical imaging, EEG-based seizure prediction, and real-time physiological monitoring. The book highlights AI-driven stratification of complex syndromes such as sepsis, stroke, and acute respiratory distress syndrome, demonstrating how data-driven models support early detection, personalized interventions, and actionable clinical decisions.The volume also presents system-level innovations, including AI-based forecasting for dialysis, blood supply management, and telemedicine optimization. It addresses ethical and regulatory challenges, fairness, transparency, data governance, and clinical validation, providing a practical roadmap for healthcare professionals, engineers, researchers, and policymakers. By integrating responsible, human-centered AI into precision medicine, the book illustrates clear pathways to enhance patient care, improve outcomes, and promote equitable healthcare.

  • Deep Learning Applications in Neuroinformatics

    Advances, Methods, and Perspectives
    • 1st Edition
    • May 1, 2026
    • Karthik Ramamurthy
    • English
    Deep Learning Applications in Neuroinformatics: Advances, Methods, and Perspectives explores how deep learning revolutionizes neuroinformatics, covering the latest methods and applications of deep learning in analyzing neuroimaging data from EEG, MRI, PET, and more. The book addresses critical neurological disorders like Alzheimer’s disease, Mild Cognitive Impairment, Stroke, and Autism Spectrum Disorder, bridging the gap between neuroscience and artificial intelligence. It is an ideal resource for researchers, practitioners, and students with insights from leading experts.

  • AI-Driven Human-Machine Interaction for Biomedical Engineering

    Concepts, Applications, and Methodologies
    • 1st Edition
    • May 1, 2026
    • Kapil Gupta + 4 more
    • English
    AI-Driven Human-Machine Interaction for Biomedical Engineering: Concepts, Applications, and Methodologies offers a comprehensive examination of the intricate relationship between humans and machines, particularly through the transformative lens of artificial intelligence (AI). As AI technologies rapidly evolve, understanding their implications for human-machine interaction (HMI) has become essential across various domains, especially healthcare. Structured into well-defined chapters, the book begins with an introduction to AI-driven HMI, laying the groundwork for understanding its significance in sustainable healthcare and beyond. Subsequent chapters explore critical topics such as machine learning principles, advanced biomedical data classification methods, and the role of AI in telemedicine.Readers will delve into cutting-edge techniques, from deep learning to non-invasive computer vision, while also examining the implications of these technologies across industries. Each chapter equips readers with actionable insights and highlights emerging trends, ethical considerations, and the future of AI in HMI, ensuring a well-rounded perspective on this dynamic field. This is an invaluable resource for researchers, academics, and students in the fields of Biomedical Engineering, Computer Science, Data Science, Artificial Intelligence, and Healthcare Technology.

  • Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence

    • 1st Edition
    • May 1, 2026
    • Manuel González Canché
    • English
    Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence empowers qualitative and mixed methods researchers in the data science movement by offering no-code, cost-free software access so that they can apply cutting-edge and innovative methods to synthetize qualitative data. The book builds on the idea that qualitative and mixed methods researchers should not have to learn to code to benefit from rigorous open-source, cost-free software that uses artificial intelligence, machine learning, and data visualization tools—just as people do not need to know C++ or TypeScript to benefit from Microsoft Word. The real barrier is the hundreds of R code lines required to apply these concepts to their databases. By removing the coding proficiency hurdle, this book will empower their research endeavors and help them become active members of and contributors to the applied data science community. The book offers a comprehensive explanation of data science and machine learning methodologies, along with access to software application tools to implement these techniques without any coding proficiency. The book addresses the need for innovative tools that enable researchers to tap into the insights that come out of cutting-edge data science tools with absolutely no computer language literacy requirements.

  • Foundations of High-Performance Computing

    A Comprehensive Guide to Systems, Concepts, and Programming
    • 1st Edition
    • April 27, 2026
    • Oscar Diez
    • English
    Foundations of High Performance Computing: A Comprehensive Guide to Systems, Concepts, and Programming offers a comprehensive reference on high-performance computing (HPC). Laying the groundwork for the companion text, High-Performance Computing: Applications and Frontiers, this book serves as a comprehensive introduction to the fundamental concepts, systems, and introductory programming techniques. It focuses on infrastructure, programming basics, and practical access to HPC systems, covering the evolution of HPC and offering an architectural overview of HPC systems. In addition, it explores resource management and performance metrics in parallel systems, discussing practical access to HPC and considering the concepts behind distributed and shared memory. Other sections focuses on OpenMP for multithreading, MPI programming, GPU computing, OpenACC, and CUDA, and parallel I/O, data management, filesystems, cloud based HPC, and virtualization. The book concludes with a reference and glossary, equipping the reader with a thorough grounding in the basics of HPC and providing a comprehensive, multidisciplinary guide on the principles and concepts that underpin high performance computing. It is designed for graduate students, early-career professionals, and researchers seeking to build a solid foundation in HPC.

  • Cybersecurity for Healthcare Systems in the Internet of Medical Things Era

    • 1st Edition
    • April 24, 2026
    • Janmenjoy Nayak + 2 more
    • English
    Cybersecurity for Healthcare Systems in the Internet of Medical Things Era is driven by the imperative to address the intricate convergence of healthcare, technology, and security. In response to the burgeoning challenges presented by the Internet of Medical Things (IoMT), this book is designed to be an indispensable resource for computer systems experts, healthcare staff, and executives. It goes beyond the surface, offering strategic insights and actionable strategies that encompass not only the IoMT landscape but also the intersection of artificial intelligence, signal processing, and cyber security. Cybersecurity for Healthcare Systems in the IoMT Era serves as a problem-solving compass for a diverse readership in the healthcare landscape. For healthcare professionals and IT leaders, the book untangles the complexities of integrating and securing Internet of Medical Things (IoMT) devices, offering a roadmap for understanding and navigating this rapidly evolving terrain. Biomedical engineers, burdened with strategic and everyday decisions, find in this book strategic insights and actionable strategies, empowering them to make informed choices amidst the ever-changing challenges posed by technology and cybersecurity threats. The authors present a comprehensive guide that not only elucidates the challenges and opportunities presented by IoMT but also explores how the synergy of AI and signal processing can elevate healthcare systems. This integration is crucial in deciphering the intricate nuances of medical data, enhancing diagnostics, and fortifying the security of interconnected healthcare networks.

  • Digital Outcasts

    Moving Technology Forward without Leaving People Behind
    • 2nd Edition
    • April 24, 2026
    • Kel Smith
    • English
    Digital Outcasts: Moving Technology Forward without Leaving People Behind, Second Edition comprehensively explores inclusive design in human-computer interaction. The book examines the real-life experiences of people with disabilities as they navigate systemic barriers in employment, education, healthcare, and social connectivity. This new edition covers the intersectionality of disability with other forms of economic and political discrimination, uncovering how biases related to race, gender, and ability are reflected in language models and AI algorithms. With digital access a foundational element of human existence, the consequences of exclusion are far-reaching and increasingly urgent.Citing case studies in law, creative arts, and social science, this updated edition also examines the historical and emergent impact people with disabilities have on culture and industry. Digital Outcasts emphases that disability has long served as a powerful catalyst for design innovation, driving transformational benefit for consumers of all abilities and backgrounds. Taking into account new legal and technological perspectives, this revision stands as an update on the progress we have made—and how far we have yet to go.

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