Proceedings of the Sixth International Conference on Emerging Trends in Mathematical Sciences & Computing (IEMSC-25)
Description
The Proceedings of the Sixth International Conference on Emerging Trends in Mathematical Sciences & Computing (IEMSC-25) highlight a rich collection of contemporary research contributions from distinguished academicians, researchers, and industry experts worldwide. This volume highlights the convergence of mathematical sciences and computational innovations, offering insights into both theoretical advancements and practical applications across a diverse range of domains. The included papers explore frontier topics such as machine learning applications in weather prediction, financial analytics, healthcare safety, sentiment analysis, equity portfolio optimization, and cybersecurity; cutting-edge AI methodologies including zero-shot learning, explainable AI, and generative adversarial networks; mathematical modeling in areas like fluid dynamics, fuzzy optimization, neutrosophic decision-making, and b-metric space theory; as well as interdisciplinary studies spanning quantum agrigenomics, socio-economic analyses, IoT-driven energy management, renewable energy control, and sustainable food systems. From predictive modeling of satellite collision risks to AI-powered medical diagnostics, from advances in cryptography to language recognition for low-resource dialects, the proceedings reflect a truly multidisciplinary synergy. This volume stands as a valuable reference for researchers, practitioners, and policymakers. This volume delivers both in-depth technical insights and fresh viewpoints on blending mathematical precision with advanced computational approaches to tackle modern-day challenges.
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Persons
Dr. Biswadip Basu Mallik is currently a Professor of Mathematics in the Department of Basic Science & Humanities at the Institute of Engineering & Management (School of University of Engineering and Management), Kolkata, India. With more than 23 years of experience in teaching and research, he has published numerous research papers and book chapters in scientific journals from esteemed international publishers, including CRC Press, Wiley, Springer, IGI Global, Nova Science, and IEEE.
Dr. Sharmistha Ghosh is a Professor at the Institute of Engineering and Management, Salt Lake Campus, University of Engineering and Management, Kolkata, India. She received her doctorate in Mathematics from the Indian Institute of Technology, Kharagpur, India. She also studied Industrial Mathematics at the University of Kaiserslautern, Germany.
Santanu Das is currently working as an Assistant Professor in Department of Basic Science and Humanities at Institute of Engineering & Management, Kolkata. He completed his under graduation and Post graduation in Mathematics from Jadavpur University and is currently pursuing his PhD from the same University. His field of research work is Cosmology and Dynamical system. He is the Faculty coordinator of Society for Data science IEM student chapter.
Dr. Sen is currently working as assistant professor in Mathematics, Institute of Engineering and Management, Salt Lake Kolkata. Dr. Sen completed his schooling from Kanchrapara Harnett High School.After that, he went to Jadavpur University.
Mr. Subrata Jana, double M.Sc. (Applied Mathematics, Applied Statistics and Analytics), M. Phil is an assistant professor of Mathematics and Statistics in the department of basic science and humanities at Techno International New Town, West Bengal, India. Also he is working as a guest faculty of West Bengal State University, Barasat, West Bengal at the Department of Management and Marketing. Currently he is pursuing Ph.D. at Jadavpur University, Department of Mathematics.
Content
1. Impact of Demographic Factors on E-Commerce Sales Events: An Empirical Study of Indian Consumers.- 2. Waves at spring contact of two fiber-reinforced thermo-elastic mediums.- 3. Aqua-sentinels safeguarding inland waters from plastic peril.- 4. Predicting Cyclonic Events: A Machine Learning Approach Using Weather Data.- 5. Comparative Study of Machine Learning Algorithms for Loan Prediction in Banking.