Professor Kawa Nazemi edited together with colleagues from the London South Bank University, Instituto Superior de Engenharia de Lisboa, and the Central Washington University enhanced contributions of selected papers of the International Conference on Information Visualisation particularly on the intersection of artificial intelligence and visualization. The book will appear in the series Studies in Computational Intelligence by Springer Nature.

Among the selected conference publications that can be found in the book, the research group published three chapters. The chapters “Guided Visual Analytics—A Visual Analytics Guidance Approach for Systematic Reviews in Research” and “Integrating Machine Learning in Visual Analytics for Supporting Collaboration in Science” describe Visual Analytics Applications and Case Studies. The chapter “Similarity in Visual Analytics—A Visual Analytics Approach for Finding Similar Publications” describes visual discovery in Text Mining and Natural Language Processing.

This collection is aimed at anyone developing and applying new AI/machine learning and visualization methods. Researchers, practitioners, and students will find numerous examples of the current integration of AI/machine learning and visualization in visual knowledge discovery. The book gives an outlook on future developments in this field. New researchers will find encouragement to join the field and participate in its further development. Teachers in AI/ML and visualization courses can use the book as a supplementary resource in their undergraduate and graduate courses.