Wah / Al-Jumeily / Berry Data Science and Emerging Technologies

Proceedings of DaSET 2024
Erscheinungsjahr 2025
ISBN: 978-981-967749-8
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 734 Seiten

Reihe: Intelligent Technologies and Robotics (R0)

The book presents selected papers from the Third International Conference on Data Science and Emerging Technologies (DaSET 2024), held hybrid at UNITAR International University. Malaysia, from December 11–12, 2024. This book aims to present current research and applications of data science and emerging technologies. The deployment of data science and emerging technology contributes to the achievement of the Sustainable Development Goals for social inclusion, environmental sustainability, and economic prosperity. Data science and emerging technologies such as generative AI, artificial intelligence and blockchain are useful for various domains such as marketing, health care, education, finance, banking, environmental, and agriculture. An important grand challenge in data science is to determine how developments in generative AI, computational, and social-behavioral sciences can be combined to improve well-being, emergency response, sustainability, and civic engagement in a well-informed, data-driven society. The topics of this book include, but are not limited to: generative AI, artificial intelligence, machine and deep learning, statistical learning, and health and industrial applications.

Zielgruppe

Research

Autoren/Hrsg.

Wah, Yap Bee

Al-Jumeily, Dhiya

Berry, Michael W.

Inhaltsverzeichnis

Data Science and Analytics.- Machine Learning Techniques and Applications.- Healthcare and Medical AI Applications.- Cybersecurity and Awareness.- Business, Education, IoT, and the Environment.

Über Autor(innen)

Professor Yap Bee Wah is the deputy vice-chancellor of Research and Consultancy at UNITAR International University Malaysia. She has been the founding and general chair for DaSET since 2022 and the editor of the proceedings published in Lecture Notes on Data Engineering and Communications Technologies published by Springer. She was the conference chair of the International Conference on Soft Computing in Data Science (2015–2019 and 2021) and editor of the SCDS conference proceedings published in the Springer CCIS series. She is also one of the editors of the book titled ‘Supervised and Unsupervised Learning for Data Science’ published by Springer Nature Switzerland AG 2020.
 
Professor Dhiya Al-Jumeily OBE is a professor of Artificial Intelligence (AI) and the president of the eSystems Engineering Society. His research focuses on developing AI analytics for improving healthcare and the environment fulfilling the United Nations SDGs. His research has been well-recognized and featured in 300+ peer-reviewed articles, 40+ books/book chapters, and attracted over £7.5M. Dhiya has successfully supervised 25+ PhD students to completion and has been an external examiner in UK and global universities. He is actively involved as a member of the editorial board/review committee for numerous international journals. Dhiya has been the founder/general series chair of the IEEE International Conference on Developments in eSystems Engineering (DeSE) since 2007 and DASET since 2022.
 
Professor Michael W. Berry is the co-author and editor of seventeen books covering topics in scientific computing, information retrieval, text/data mining, and data science.  He is a co-editor of the Soft Computing in Data Science volumes from 2015-2021 and Data Science and Emerging Technologies 2022 proceedings by Springer.   He is also the co-author of popular books published by SIAM (Society for Industrial and Applied Mathematics): Understanding Search Engines: Mathematical Modeling and Text Retrieval, Second Edition, and Computational Information Retrieval.  He has published over 115 refereed journal and conference publications. He is a member of SIAM, ACM, MAA, ASEE, and the IEEE Computer Society and is on the editorial board of Foundations of Data Science (AIMS) and the SIAM Journal on Matrix Analysis and Applications  (SIAM).