Data Science and Emerging Technologies

Proceedings of DaSET 2025
Erscheinungsjahr 2026
ISBN: 978-3-032-23406-3
Verlag: Springer

Buch, Englisch, Band 302, 537 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 984 g

Reihe: Lecture Notes on Data Engineering and Communications Technologies

This book presents selected research papers from Fourth International Conference on Data Science and Emerging Technologies (DaSET 2025), held hybrid at UNITAR International University. Malaysia, from December 9–10, 2025. This book presents current research and applications of data science and emerging technologies. The topics of this book include 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.

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Computer Vision, Remote Sensing, and Geospatial AI.- Industrial, Environmental, and Emerging Technologies.- Time Series Analysis and Forecasting.- Statistical Methods, Process Control, and Anomaly Detection.- Advanced AI Architectures, Interpretability, and Large Models.- Applied Data Science for Health, Public Services, and Social Impact.

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 & 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. She actively published papers in ISI and Scopus journals such as Expert Systems with Applications Journal of Statistical Computation and Simulation, Communications in Statistics-Computation and Simulation, Journal of Clinical and Translational Endocrinology, and Computers, Materials, and Continua.
 
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 500+ peer-reviewed articles, 40+ books/book chapters, and attracted over £7.5M. Dhiya has successfully supervised 30+ Ph.D. 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 since 2007 and DASET since 2022. On 31 December 2020, Dhiya was promoted and appointed by THE LATE QUEEN to the Most Excellent Order of the British Empire, “OBE-Ordinary Officers of the Civil Division of the said Most Excellent Order for the “Services to Scientific Research”.
 
Professor Michael W. Berry is the co-author and editor of eighteen books covering topics in scientific computing, information retrieval, text/data mining, and data science. He is the co-editor of the Soft Computing in Data Science volumes (published by Springer) from 2015 to2021 and Data Science and Emerging Technologies volumes (published by Springer) from 2022 to 2024.
He is also the co-author of popular books published by Society for Industrial and Applied Mathematics (SIAM): 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).