Data Analytics and Management (eBook)

Proceedings of ICDAM

Ashish Khanna, Deepak Gupta, Zdzisław Pólkowski, Siddhartha Bhattacharyya, Oscar Castillo (Herausgeber)

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2021 | 1st ed. 2021
XXIV, 937 Seiten
Springer Singapore (Verlag)
978-981-15-8335-3 (ISBN)

This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2020), held at Jan Wyzykowski University, Poland, during June 2020. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students.

Dr. Ashish Khanna has expertise in Teaching, Entrepreneurship, and Research & Development of 16 years. He received his Ph.D. degree from National Institute of Technology, Kurukshetra, in March 2017. He has completed his M.Tech. and B.Tech. from GGSIPU, Delhi. He has completed his PDF from the Internet of Things Lab at Inatel, Brazil. He has around 100 research papers along with book chapters including more than 40 papers in SCI Indexed Journals with cumulative impact factor of above 100 to his credit. Additionally, he has authored and edited 19 books. Furthermore, he has served the research field as a Keynote Speaker/Session Chair/Reviewer/TPC member/ Guest Editor, and many more positions in various conferences and journals. His research interest includes image processing, distributed systems and its variants, and machine learning. He is currently working at the CSE, Maharaja Agrasen Institute of Technology, Delhi. He is Convener and Organizer of ICICC Springer conference series.

Dr. Deepak Gupta is an eminent academician and plays versatile roles and responsibilities juggling between lectures, research, publications, consultancy, community service, Ph.D. and postdoctorate supervision, etc. With 12 years of rich expertise in teaching and two years in industry, he focuses on rational and practical learning. He has contributed massive literature in the fields of-computer interaction, intelligent data analysis, nature-inspired computing, machine learning, and soft computing. He is working as an Assistant Professor at Maharaja Agrasen Institute of Technology (GGSIPU), Delhi, India. He has served as Editor-in-Chief, Guest Editor, and Associate Editor in SCI and various other reputed journals. He has authored/edited 33 books with national/international level publisher (Elsevier, Springer, Wiley, Katson). He has published 96 scientific research publications in reputed international journals and conferences including 46 SCI Indexed Journals of IEEE, Elsevier, Springer, Wiley, and many more.

Dr. Zdzis?aw Pólkowski is an Adjunct Professor at Faculty of Technical Sciences at the Jan Wyzykowski University, Poland. He is also the Rector's Representative for International Cooperation and Erasmus Programme and Former Dean of the Technical Sciences Faculty during the period of 2009-2012. His area of research includes management information systems, business informatics, IT in business and administration, IT security, small medium enterprises, CC, IoT, big data, business intelligence, and block chain. He has published around 60 research articles. He has served the research community in the capacity of Author, Professor, Reviewer, Keynote Speaker, and Co-Editor. He has attended several international conferences in the various parts of the world. He is also playing the role Principal Investigator.

Dr. Siddhartha Bhattacharyya [FIEI, FIETE, LFOSI, SMIEEE, SMACM, SMIETI, LMCSI, LMISTE, MIET (UK), MIAENG, MIRSS, MIAASSE, MCSTA, MIDES, MISSIP, MSDIWC] is currently the Principal of RCC Institute of Information Technology, Kolkata, India. In addition, he is also serving as the Professor of Computer Application and Dean (Research and Development and Academic Affairs) of the institute. He is the recipient of several coveted awards like Adarsh Vidya Saraswati Rashtriya Puraskar, Distinguished HoD Award, Distinguished Professor Award, Bhartiya Shiksha Ratan Award, Best Faculty for Research, and Rashtriya Shiksha Gaurav Puraskar. He received the Honorary Doctorate Award (D. Litt.) from The University of South America and the SEARCC International Digital Award ICT Educator of the Year in 2017. He has been appointed as the ACM Distinguished Speaker for the tenure 2018-2020. He is a co-author of 4 books and the co-editor of 16 books and has more than 200 research publications in international journals and conference proceedings to his credit.

Dr. Oscar Castillo holds the Doctor in Science degree (Doctor Habilitatus) in Computer Science from the Polish Academy of Sciences (with the Dissertation 'Soft Computing and Fractal Theory for Intelligent Manufacturing'). He is a Professor of Computer Science in the Graduate Division, Tijuana Institute of Technology, Tijuana, Mexico. Currently, he is President of HAFSA (Hispanic American Fuzzy Systems Association) and Past President of IFSA (International Fuzzy Systems Association). Prof. Castillo is also Chair of the Mexican Chapter of the Computational Intelligence Society (IEEE). His research interests are in Type-2 Fuzzy Logic, Fuzzy Control, Neuro-Fuzzy, and Genetic-Fuzzy hybrid approaches. He has published over 300 journal papers, 10 authored books, 40 edited books, 200 papers in conference proceedings, and more than 300 chapters in edited books, in total 865 publications according to Scopus (H index=60), and more than 1000 publications according to Research Gate (H index=72 in Google Scholar).

Erscheint lt. Verlag	4.1.2021
Reihe/Serie	Lecture Notes on Data Engineering and Communications Technologies
Reihe/Serie	Lecture Notes on Data Engineering and Communications Technologies
Zusatzinfo	XXIV, 937 p. 512 illus., 384 illus. in color.
Sprache	englisch
Themenwelt	Mathematik / Informatik ► Informatik ► Datenbanken
	Informatik ► Netzwerke ► Sicherheit / Firewall
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Technik
Schlagworte	Big Data • Computational Intelligence • data analytics • Data Management • Deep learning • ICDAM 2020 • ICDAM Proceedings • machine learning
ISBN-10	981-15-8335-8 / 9811583358
ISBN-13	978-981-15-8335-3 / 9789811583353

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