Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19

Edited by:   Victor Chang (Professor of Data Science and Information Systems at Teesside University UK), Mohamed Abdel-Basset (Zagazig University, Egypt), Muthu Ramachandran (Integrated Cloud Solutions and Public Intelligence, Leeds, UK), Nicolas Green (Bioelectronics and Microfluidity, Electronics and Computer Science, University of Southampton, UK), Gary Wills (Cyber Physical Research Group, Electronics and Computer Science, University of Southampton, UK)
Imprint:   Academic Press Inc
Country of Publication:   United Kingdom
Dimensions:   Height: 235mm,  Width: 191mm, 
ISBN:   9780323900546
ISBN 10:   0323900542
Pages:   500
Publication Date:   07 April 2022
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active

Victor Chang, PhD, is a Full Professor of Data Science and Information Systems and Research Group leader at Teesside University since September 2019. He was previously a Senior Associate Professor, Director of PhD and Director of MRes at International Business School Suzhou (IBSS), Xi'an Jiaotong-Liverpool University, China. He was also a very active and contributing key member at Research Institute of Big Data Analytics, XJTLU, and an Honorary Associate Professor at University of Liverpool. Before becoming an academic, he has achieved 97% on average in 27 IT certifications. He is Editor-in-Chief of IJOCI & OJBD journals, Associate Editor of IEEE TII, Information Fusion, and JGIM, Scientific Report, IJBSR and IDD journals. He is a founding and Conference Chair of IoTBDS, COMPLEXIS, FEMIB and IIoTBDSC conferences. He authored 5 books and edited 2 and is widely regarded as one of the most active and influential young scientist and expert in IoT/Data Science/Cloud/security/AI/IS, as he has experience to develop 10 different services for multiple disciplines. Mohamed Abdel-Baset, PhD, current research interests are Optimization, Operations Research, Data Mining, Computational Intelligence, Applied Statistics, Decision support systems, Robust Optimization, Engineering Optimization, Multi-objective Optimization, Swarm Intelligence, Evolutionary Algorithms, and Artificial Neural Networks. He is working on the application of multi-objective and robust meta-heuristic optimization techniques. He is also Editor/reviewer in different international journals and conferences. He holds the program chair in many conferences in the fields of decision-making analysis, big data, optimization, complexity and internet of things, as well as editorial collaboration in some journals of high impact. Muthu Ramachandran, PhD, has more than thirty years of teaching and research experience both in academia and industrial research setting. Prior to this, he spent eight years in industrial research at Philips Research Labs and subsequently at Volantis Systems Ltd, where he has worked on various research projects including software engineering, cloud computing, data science, IoT, and machine learning. Currently, Dr. Ramachandran is leading research in the areas of Cloud Software Engineering, Big Data Software Engineering, IoT Software Engineering, Software Security Engineering, SOA, Cloud Computing, and in the main areas of Software Engineering on RE, CBSE, software architecture, reuse, quality and testing. He has published 15 books, 50 book chapters, 100s of journal articles and conferences. He has also been chair and keynote speaker of conferences on SE-CLOUD, IoTBDS, and COMPLEXIS. Nicolas G Green, PhD, is an Associate Professor in the School of Electronics and Computer Science at the University of Southampton, with research primarily focusing on design and development of technology and systems for Lab-on-a-Chip and Point of Care applications in medicine and environmental science. He is an expert on electrical and optical techniques for the detection, measurement, characterization, classification and separation of biological cells, bacteria, viruses and biomolecules. He is also developing strategies for the application of machine learning for assisting medical experts and practitioners in diagnoses. Gary Wills, PhD, research project focuses on Secure Systems Engineering and applications for industry, medicine, and FinTech. Dr. Wills's work cross-discipline with colleagues from industry and academia. His research can be grouped under a number of themes: Machine learning, Internet of things, Blockchain, Security, Computational Finance, Data Protection, and Cloud Services. He has published widely on these topics, in books, book chapters, official reports, journal articles and conferences paper. Gary has co-edited a number of special issues, and regularly reviews articles for international journals.