About the Book
Prediction of the Future Pandemic: Artificial Intelligence and Nanotechnology Approaches provides a comprehensive account of the applications, challenges, and breakthroughs in using AI and nanotechnology for pandemic prediction. The book emphasizes interdisciplinary collaboration among experts and a global perspective on the prediction of future pandemics. Sections provide a comprehensive exploration of cutting-edge methodologies that leverage AI and nanotechnology to predict, analyze, and combat future pandemics. This book aims to bridge the gap between theoretical concepts and practical applications, offering insights into the integration of these advanced technologies for more accurate, timely, and ethical pandemic predictions.
Table of Contents:
1. The Role of Emerging Technology in Pandemic Predictions
2. Interdisciplinary Perspectives on Future Pandemic Prediction
3. Role of Artificial Intelligence in Pandemic Prediction
4. Nanotechnology Applications in Pandemic Prediction
5. AI and Nanotechnology Integration and Future Pandemic Prediction
6. Comparative Analysis of AI and Nanotech Approaches for Pandemic Prediction
7. Quantum Leaps in Pandemic Prediction: AI Synergy
8. AI Healers: Redefining Pandemic Response
9. Role of Nanomaterials in Prevention Strategies
10. Viral Detection: Nanosensors in Quarantine Enforcement
11. Future Implications, Opportunities and Limitations in Pandemic Prediction
12. Pandemics of Tomorrow: How AI and Nanotech will Transform Global Health?
About the Author :
Dr. Ali Ahmadian is a senior research scientist the Mediterranea University of Reggio Calabria, Italy and an Associate Fellow Researcher at the Institute of IR 4.0, The National University of Malaysia. As an active researcher, he is dedicated to research in applied mathematics. He received his Ph.D. in early of 2014 as the best postgraduate student from Universiti Putra Malaysia (UPM). After his Ph.D. He took a postdoctoral fellowship at same university as part of the numerical analysis research group and at the same time joint to the University of Malaya as an Associate Researcher. He was promoted as a Fellow Researcher on December 2017 in UPM. In 2019, he joined the National University of Malaysia as a senior lecturer where he currently works in the Institute of IR 4.0. In general, his primary mathematical focus is the development of computational methods and models for problems arising in computer science, biology, physics, and engineering under fuzzy and fractional calculus (FC); in this context, he has worked on projects related to nano-communication networks, drug delivery systems, acid hydrolysis in palm oil frond, and carbon nanotubes dynamics, nanofluids, viscosity, AI and etc. He is a member of editorial board in Sustainable Computing: Informatics and Systems, Soft Computing, Journal of control and Decision, Progress in Fractional Differentiation and Applications (Natural Sciences Publishing) and Mathematical Problems in Engineering (Hindawi) and lead guest editor of special issues in more than 50 international journals from Elsevier, Springer, Wiley and so on. He is an author of more than 350 research papers published in as Nature, IEEE, Elsevier, Springer, Wiley and etc. He is an author and editor of four books published and in process in CRC Press and Elsevier, respectively. He also presented his research works in 38 international conferences held in Canada, Serbia, China, Turkey, Malaysia and UAE. He also received Premio Anassilaos Giovani Award for his achievement in art, culture, economics and science from Italy in November 2021. Dr. Ferial Ghaemi is a postdoctoral research fellow at RMIT University's Melbourne campus. As an experienced researcher and lecturer with a demonstrated history in higher education and industry, she is dedicated to advancing research in nanotechnology. She holds a Ph.D. in nanotechnology, with a specialized focus on the fabrication of nanomaterials and analytical chemistry.
Dr. Ashok Kumar Yadav holds a B.Tech. from AKTU Lucknow and an M.Tech. and Ph.D. from JNU New Delhi, India. With over eight years of combined teaching and research experience, he is currently an Assistant Professor in the Department of Information Technology at Rajkiya Engineering College, Azamgarh, India. Before this, he served as an Assistant Professor (On ad-hoc) at the University of Delhi. Dr. Yadav's research expertise spans across multi-attribute decision-making (MADM), blockchain technology, machine learning, and mobility management in mobile communication. His significant contributions include publications in renowned journals such as Elsevier, Springer, World Scientific, and Taylor & Francis, as well as presentations at prominent international conferences. Among his notable works, Dr. Yadav is the author of "Blockchain Technology and Its Applications" and co-author of "Mastering Disruptive Technologies: Applications of Cloud Computing, IoT, Blockchain, Artificial Intelligence & Machine Learning Techniques." Additionally, he has edited two books for IGI Global. Dr. Yadav's academic achievements include six SCI-indexed publications, two Scopus-indexed papers, and six patents. He is actively involved in academia as a reviewer for international journals and a contributor to program committees at various conferences. His excellence has been recognized with the Best Paper Award at the IEEE World Conference on Applied Intelligence and Computing in 2022, and at the International Conference on Artificial Intelligence and Smart Communication (AISC) in 2023.
Dr M. J. Ebadi obtained a Ph.D. degree in applied mathematics in 2018. Dr Ebadi’s research interests span a wide range of topics, including artificial intelligence, neural networks, deep learning, numerical optimization, optimal control, numerical analysis, fractional calculus, and fuzzy mathematics.
Soheil Salahshour has, since 2012, been a University Professor with the Department of Mathematics in different universities, and recently moved to the Istanbul Okan University. His research interests include fractional models and Calculus, Fuzzy expert systems, evolutionary algorithms, optical soliton solutions, data science and big data applications.
