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About the Author

Dr. Deepak Sinwar is an Associate Professor at the Department of Computer and Communication Engineering, Manipal University Jaipur, Jaipur, Rajasthan, India. He received his Ph.D and M.Tech degrees in Computer Science and Engineering in 2016 and 2010 respectively; and B.Tech (with honors) in Information Technology in 2008. On his credit, he has published more than 50 articles in peer reviewed journals, conference proceedings, and book chapters.

He has published three edited books published by Springer, CRC Press, and Scrivener (Wiley). He is currently editing three more books for reputed publishers including CRC Press (Taylor & Francis) and Springer. He has worked as guest editor for a special issue entitled, “Sustainable development in Computational Intelligence and Computer Vision” of “International Journal of Social Ecology and Sustainable Development (IJSESD) – IGI Global. He has published 3 patents and 7 copyrights in the field of computer software. He has supervised 1 Ph.D thesis, 11 M.Tech dissertations and currently supervising 4 Ph.D scholars. He has organized three international conferences viz. ICICV-2020, ICICV-2021 and ICICV-2022 supported by Springer. Dr. Sinwar is a recipient of “Top Researcher of the Year – 2021” by Manipal University Jaipur, India for his research contributions in year 2021. He has organized and attended various workshops during his teaching career. His research interests include Computational Intelligence, Data Mining, Machine Learning, Reliability Theory, Computer Networks and Pattern Recognition. He is an enthusiastic and motivating technocrat with more than 12 years of research and academic experience. He is a life member of Indian Society for Technical Education (India), senior member of IEEE and member of ACM professional society.



Computational Intelligence based Optimization of Manufacturing Process for Sustainable Materials

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Computational Intelligence based Optimization of Manufacturing Process for Sustainable Materials

ABOUT THE BOOKThe text comprehensively discusses computational models including artificial neural networks, agent-based models, and decision field theory for reliability engineerin..

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