Industry 5.0: Emerging Paradigms for Business, Technology, and Society
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This book focuses on unearthing nuances of leveraging integrative and cohesive technologies in the Industry 5.0 paradigm for solving problems of business and social enterprises, which need not only be competitive but also sustain value creation for people at large.
The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of industrial engineering, manufacturing engineering, production engineering, business management, mechanical engineering, and engineering management.
Deergha Sharma is an associate professor of finance and Head of the Department of Management & Commerce at The NorthCap University, Haryana, India. She has authored more than twenty-five research publications featured in esteemed national and international journals, including those indexed in Scopus, Web of Science, and the ABDC Journal list. Her academic contributions also include an edited volume published by IGI Global (USA) and an Indian patent. Her primary research interests lie in banking operations, financial modeling, sustainability, decision-making, and the application of fuzzy logic in finance.
Manisha Gupta is currently working as an associate professor and Head of Department in Trinity Institute of Professional Studies Delhi . She has over 16 years of experience in academics and research. She has published research papers in journals and conferences of national and international repute. Her areas of research interest include consumer buying behavior, organizational behavior, and sustainability.
Raj K Kovid is Professor at School of Business, UPES (University of Petroleum and Energy Studies), Dehradun, India. His teaching and research area includes Market Strategy, M&A, Technology Adoption, Corporate Governance & CSR, Entrepreneurship & Innovation, . He has published research papers and book chapters in Scopus/ABDC indexed journals such as Management Decision, and edited books published by international publishers such as IGI, USA. He is involved with some journals in capacity of guest editor, board member and reviewer. His cases are available at Harvard Publishing, Emerald Publications and he has also conducted case method workshops. He has also consulted firms with respect to their growth strategies.
Thipendra P Singh is currently working as a Professor of Artificial Intelligence at Chandigarh University, Uttar Pradesh, India. Dr. Singh is also paneled as adjunct professor at School of Computing at Maryam Abacha American University of Nigeria. Dr. Singh holds prestigious fellowship of IEI. Beyond this he is also a senior member of IEEE and member of various other professional bodies including ACM, EAI, ISTE, IAENG etc. There are more than 120 publications to his credit in various National and International journals. He has been author/editor of more than 20 books on various allied topics of Computer Science.
Pradeep Kumar is currently a data analyst, at the Department of Social Development, in the Government of New Brunswick (GNB), Canada. He worked as a data analyst in computer vision with Eigen Innovations Inc. Fredericton. Prior to that, he was a Postdoctoral Fellow at the Institute of Biomedical Engineering at the University of New Brunswick, Canada. He has published more than 50 research articles in reputed journals and conferences. His expertise and research interests include human-computer interfaces, biometrics, time-series analysis, pattern recognition, and machine learning.
Ahatsham Hayat is a Graduate Research Assistant at the University of Nebraska-Lincoln, working in the Human-AI Learning (HAL 2.0) Lab. He serves as the lead scientist on the NSF-funded project AI for Behavior Interventions, where he designs AI-driven models to understand and support student learning and engagement through multimodal and longitudinal data. His research focuses on multimodal learning, time-series modeling, and enhancing the generalizability and robustness of deep learning systems. Ahatsham has published in top-tier conferences and journals and previously conducted research at ARDITI and MITI in Portugal, applying machine learning and computer vision to domains such as medical image analysis, agriculture, and educational technologies.
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