Data Science Advancements in Pandemic and Outbreak Management (Advances in Data Mining and Database Management)

ISBN 10: 1799867366 / ISBN 13: 9781799867364

Published by Engineering Science Reference, 2021

About this Item

Seller Inventory # I-9781799867364

Bibliographic Details

• Title: Data Science Advancements in Pandemic and Outbreak Management (Advances in Data Mining and Database Management)
• Publisher: Engineering Science Reference
• Publication Date: 2021
• Language: English
• ISBN 10: 1799867366
• ISBN 13: 9781799867364
• Binding: Hardcover
• Condition: New

About this title

Synopsis

"This book demonstrates how strategies and state-of-the-art information technologies have and/or could be applied to serve as the vehicle to advance pandemic and outbreak management including revisiting and critically reviewing past and current approaches, identifying good and bad practices and further developing adaptation for future pandemics and outbreaks"--

About the Authors

Eleana Asimakopoulou received the MA and PhD degrees in the area of Disaster Management from the University Westminster and Loughborough University, UK, in 2009 and 2008 respectively. She is been a lecturer and a visiting researcher in various institutions including the Hellenic National Defence College, Athens, Greece and an expert evaluator in national and European proposals for funding. Her research is in the area of utilizing disruptive technologies (IoT, grid and cloud computing) for disaster management. She has been involved in a number of projects and has published over 60 works. Dr Asimakopoulou is an editor of a book and an associate editor of a refereed international journal.

Nik Bessis is a full Professor of Computer Science and the Head of Department of Computing at Edge Hill University, UK. Prior to that, Nik was a full Professor of Computer Science and the Director of Distributed and Intelligent Systems (DISYS) research centre at the University of Derby, UK. He holds a PhD and a MA from De Montfort University, UK and a BA from TEI of Athens, Greece. Professor Bessis is a Fellow of HEA, BCS and a Senior Member of IEEE. His research is on social graphs for network and big data analytics as well as on developing data push and resource provisioning services in IoT, FI and clouds. He has led several projects worth over £3m. He has published over 250 works and won 4 best paper awards. He has chaired over 40 international events, delivered 4 keynote speeches, edited 4 SIs, 8 books and 9 conference proceedings. His latest 2 edited books on IoTs & big data have been ranked as top 25 & top 40 on Amazon AI book lists. He is also the founding editor-in-chief of IJDST. Professor Bessis has served as an expert evaluator for the Hellenic QAA and, as an assessor for more than 10 Professorships conferment worldwide.