Impact of AI and Data Science in Response to Coronavirus Pandemic (eBook)

The book presents advanced AI based technologies in dealing with COVID-19 outbreak and provides an in-depth analysis of variety of COVID-19 datasets throughout globe. It discusses recent artificial intelligence based algorithms and models for data analysis of COVID-19 symptoms and its possible remedies. It provides a unique opportunity to present the work on state-of-the-art of modern artificial intelligence tools and technologies to track and forecast COVID-19 cases. It indicates insights and viewpoints from scholars regarding risk and resilience analytics for policy making and operations of large-scale systems on this epidemic. A snapshot of the latest architectures, frameworks in machine learning and data science are also highlighted to gather and aggregate data records related to COVID-19 and to diagnose the virus. It delivers significant research outcomes and inspiring new real-world applications with respect to feasible AI based solutions in COVID-19 outbreak. In addition, it discusses strong preventive measures to control such pandemic.

Dr. Sushruta Mishra is from Odisha, India. He has completed B.Tech from ITER, BBSR in 2009; M.Tech degree from IIIT, BBSR in 2012. He has completed Ph.D from KIIT University, BBSR in 2017. Currently he is working as Assistant Professor in KIIT University, BBSR in Department of School of Computer Engineering. He has one year of software industry experience at Infosys and more than 7 years of teaching experience. He teaches several academic subjects such as Data Mining, Computer Networks, Database Management System, Software Engineering, Internet and Web technology and many other courses. His prime research area of interest includes Machine learning, Sentiment Analysis, Cognitive Computing and Robotics. Dr. Mishra has published more than 30 research and development articles in various reputed journals, conferences and book chapters. 

Dr. Pradeep Kumar Mallick is currently working as Senior Associate Professor  in the School of Computer Engineering , Kalinga Institute of Industrial technology (KIIT) Deemed to be University, Odisha, India .He has also served as Professor and Head Department of Computer Science and Engineering , Vignana Bharathi Institute of Technology, Hyderabad . He has completed his    Post Doctoral Fellow (PDF) in Kongju National University South Korea ,  PhD from Siksha Ó' Anusandhan University, M. Tech. (CSE) from Biju Patnaik University of Technology (BPUT), and MCA from Fakir Mohan University Balasore, India. Besides academics, he is also involved various administrative activities, Member of Board of Studies, Member of Doctoral Research Evaluation Committee, Admission Committee etc. His area of research includes Algorithm Design and Analysis, and Data Mining, Image Processing, Soft Computing, and Machine Learning. Now he is the editorial member of Korean Convergence Society for SMB .He has published 14 books and more than 90 research papers in National and international journals and conference proceedings in his credit.

Dr. Hrudaya Kumar Tripathy is an Associate Professor of School of Computer Engineering, KIIT University, Bhubaneswar, India. He has completed Doctorate in Computer Science from Berhampur University, Master in Computer Science Engineering from Indian Institute of Technology, Guwahati and received Post Doctoral Fellowship from Ministry of Higher Education Malaysia. He is having 19 years of teaching experience with post-doctorate research experience in the field of Soft Computing, Machine Learning, Speech Processing, Mobile Robotics, and Big Data Analysis. He had been a visiting faculty for a couple of years in Asia Pacific University, Kuala Lumpur, Malaysia and the University of Utara Malaysia, Sintok, Malaysia. Dr. Tripathy has awarded as Young IT professional award in 2013 on a regional level from Computer Society of India (CSI). He is having more than 100 research publications in different national/international journals and conferences and received many certificates of merits and highly applauded in a presentation of research papers. 

Dr. Gyoo-Soo Chea has received Ph.D (Electrical Engineering) from Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA. After receiving Ph.D, he worked at Amphenol Mobile, Korea as a RF manager from June 2001 to February 2003. He has been with Baekseok University in Korea as a Professor since 2003. He has granted department scholarship (Kyungpook National University grant) during March 1991 - February 1993 and associated with IEEE Antennas and Propagation Society, January 2001 - present. He serves Editor-in-Chief of The Korea Institute of Information, Electronics, and Communication Technology since 2013. His research interests are antennas and dual-band inverted-F antenna. 

Dr. Bhabani Shankar Prasad Mishra born in Talcher, Odisha, India in 1981. He received the B.Tech. in Computer Science and Engineering from Biju Pattanaik Technical University, Odisha in 2003,  M.Tech. degree in Computer Science and Engineering from the KIIT University, in 2005, Ph.D. degree in Computer Science from F.M.University, Balasore,Odisha, India, in 2011 and Post Doc in 2013 from Soft Computing Laboratory, Yansei University, South Korea. Currently he is working as an Associate Professor and Dean at School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India. His research interest includes Pattern Reorganization, Data Mining, Soft Computing, Big Data and Machine Learning. He has published more than 80 research articles in reputed Journal and Conferences, has edited more than five books of current importance. Under his guidance, 2 PhD scholars are already been awarded. Dr. Mishra was the recipient of the Gold Medal and Silver Medal during his M.Tech for the best Post Graduate in the University. He is the member of different technical bodies ISTE, CSI and IET.

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The book presents advanced AI based technologies in dealing with COVID-19 outbreak and provides an in-depth analysis of variety of COVID-19 datasets throughout globe. It discusses recent artificial intelligence based algorithms and models for data analysis of COVID-19 symptoms and its possible remedies. It provides a unique opportunity to present the work on state-of-the-art of modern artificial intelligence tools and technologies to track and forecast COVID-19 cases. It indicates insights and viewpoints from scholars regarding risk and resilience analytics for policy making and operations of large-scale systems on this epidemic. A snapshot of the latest architectures, frameworks in machine learning and data science are also highlighted to gather and aggregate data records related to COVID-19 and to diagnose the virus. It delivers significant research outcomes and inspiring new real-world applications with respect to feasible AI based solutions in COVID-19 outbreak. In addition, itdiscusses strong preventive measures to control such pandemic.