Prof.  Prem Kumar  Singh
Gandhi Institute of Technology and Management-Visakhapatnam,  India

Title: Turiyam Set Based Intelligence System

Abstract:

Turiyam set given an alternative way to deal with unknown data sets and its exploration. One of the suitable examples is exploring unknown graph rather than true, false or misleading graph. In this talk the author will focus on exploring the unknown data sets and its pattern based on Turiyam set. In addition the author will also explore its differences from any of the available sets for dealing four dimensional data sets

Biography:

Dr. Prem Kumar Singh working as Full Professor at Department of Computer Science and Engineering, Gandhi Institute of Technology and Management-Visakhapatnam, Andhra Pradesh-India. He has more than 14 Years of experience in teaching, research and academics. He holds a Post-Doc in Computer Science from Faculty of Computer Science and Information Technology, University of Malaya-Kuala Lumpur which was fully funded by HIR Lab Malaysian Govt of Higher Education. He has completed a PhD degree in Computer Science from Vellore Institute of Technology-Vellore which was fully funded by NBHM Department of Atomic Energy, Govt of India. He has published more than 110 peer review research papers in several conferences and Journals. All of those researches cited more than 2200, 27 h-indexes and more than 58 i10 papers. His current research interests are soft computing, complex data analysis, graph theory, mathematical modelling and Quantum machine intelligence. Towards this direction, he has introduced bipolar, three-polar, m-polar, complex, Plithogenic and Turiyam graphs for knowledge processing tasks. He served as Technical Program Committee, Reviewer, Guest Editor, Editorial board member as well as Speaker for more than 300 peer reviewed conferences and journals. He is Editor-In-Chief for “Journal of Neutrosophic and Fuzzy Systems” and Associate Editor for “Journal of Artificial Intelligence and Technology”.  He is also listed as Top 2% Scientist by Stanford University in 2019, 2020, 2021, 2022 and 2023 as well.