About the Author: Vinit Kumar Gunjan is Associate Professor in Department of Computer Science & Engineering and Dean of Academic affairs at CMR Institute of Technology Hyderabad (Affiliated to Jawaharlal Nehru Technological University, Hyderabad). He is an active researcher; he has published research papers in IEEE, Elsevier and Springer conferences, authored several books and edited volumes of Springer series, most of which are indexed in SCOPUS database. He was awarded with the prestigious Early Career Research Award in the year 2016 by Science Engineering Research Board, Department of Science & Technology, Government of India. He is Senior Member of IEEE, active Volunteer of IEEE Hyderabad Section, and 2021 Additional Secretary; he is 2021 Vice Chairman--IEEE Computational Intelligence Society; he is volunteered in the capacity of Treasurer, Secretary and Chairman of IEEE Young Professionals Affinity Group and IEEE Computer Society. He was involved as organizer in many technical and non-technical workshops, seminars and conferences of IEEE and Springer. During the tenure, he had an honour of working with top leaders of IEEE and was awarded with outstanding IEEE Young Professional Award in 2017 by IEEE Hyderabad Section.

Jacek M. Zurada is Professor of Electrical and Computer Engineering and Director of the Computational Intelligence Laboratory at the University of Louisville, Kentucky, USA, where he served as Department Chair and Distinguished University Scholar. He received his M.S. and Ph.D. degrees (with distinction) in electrical engineering from the Technical University of Gdansk, Poland. He has published over 420 journal and conference papers in neural networks, deep learning, computational intelligence, data mining, image processing, and VLSI circuits. He has authored or co-authored three books, including the pioneering text Introduction to artificial neural systems, co-edited the volumes computational intelligence: imitating life, knowledge-based neurocomputing, and co-edited twenty volumes in Springer Lecture Notes on Computer Science. In addition to his pioneering neural networks textbook, his most recognized achievements include an extension of complex-valued neurons to associative memories and perception networks; sensitivity concepts applied to multilayer neural networks; application of networks to clustering, biomedical image classification, and drug dosing; blind sources separation; and rule extraction as a tool for prediction of protein secondary structure.