Mathematical Methods in Artificial Intelligence - (De Gruyter Proceedings in Mathematics) (Hardcover)

About the Book

The series is aimed specifically at publishing peer-reviewed reviews and contributions presented at conferences, workshops, and international seminars as well as edited volumes commemorating and honoring significant achievements by mathematicians. This content covers various topics within pure and applied mathematics and provides up-to-date coverage of new developments, methods, and applications.

Book Synopsis

In today's data-driven era, the convergence of mathematics, computing, artificial intelligence, and blockchain is emerging as a significant area at the intersection of applied mathematics and computer science, particularly in decision-making. This book explores the applications of advanced mathematical models and computational algorithms to AI-driven strategies and blockchain technologies.
It covers advanced linear algebra techniques, probability theory, optimization methods, game theory, cryptography, and statistical learning, providing deep mathematical insights into AI, blockchain, and data-driven decision-making. The book delves into matrix computations and eigenvalue problems relevant to deep learning, Bayesian inference for predictive modeling, and reinforcement learning for dynamic decision-making.
Additionally, optimization methods such as convex programming and Lagrangian multipliers enhance resource allocation, while cryptographic protocols ensure the security of blockchain systems. By integrating these mathematical frameworks, this book provides researchers, professionals, and students with practical tools for addressing complex business challenges ranging from fraud detection to automated contract execution.

About the Author

Dr. Abhishek Kumar, Senior Member of IEEE, is an Assistant Director and Professor in the Computer Science & Engineering Department at Chandigarh University, Punjab, India. With over 13 years of teaching experience, he has published 180+ peer-reviewed papers and successfully supervised four Ph.D. scholars, with four more currently under his guidance, along with 30+ M.Tech projects. He holds a Ph.D. from the University of Madras and completed postdoctoral research at Universidad de Castilla-La Mancha, Spain. His research interests span artificial intelligence, renewable energy systems, image processing, and data mining. An award-winning researcher, Dr. Kumar has received several accolades, including the Sir C.V. Raman National Award (2018), and holds a patent. An accomplished author and editor, he has authored seven books and edited 51 volumes with reputed publishers like IET, Elsevier, Wiley, Springer, and De Gruyter. Dr. Kumar also serves as Series Editor for book series such as Quantum Computing (De Gruyter), Intelligent Energy Systems (Elsevier), and MMDA De Gruyter.

Reyes Jose holds a full professor position at UABC, Tijuana campus, Baja California, Mexico. He is the President of the Mexican Network of Software Engineering (REDMIS, https: //conisoft.org/redmis/). He is a member of the National System of Researchers of Mexico(SNI), Level 2, and leads several research projects in collaboration with Industry. His research areas are Software Engineering (uncertainty in agile methodologies, quality improvement in Scrum), Human-Computer Interaction (user-centered design, adaptive user interfaces), and he is currently working with Quantum Computing. He was the General Chair for the National and International Conference on Software Engineering Research and Innovation (CONISOFT).

Angeles Quezada holds a Doctorate in Sciences from the Autonomous University of Baja California, a Master's degree in Computer Science from the Technological Institute of Tijuana, and a Bachelor's degree in Computer Science from the Technological Institute of Tapachula, Chiapas. She is currently a research professor pursuing a Master's Degree in Information Technologies at the Tijuana Technological Institute, where she participates in research projects and teaching. She is the author of various scientific publications, including indexed journals, book chapters, and conference articles. She is a member of the National System of Researchers SNI level 1 and a member of the Mexican Thematic Network of Software Engineering (REDMIS). Research areas include Human Computer Interaction, Artificial Intelligence, and Machine Learning.

Dhaya Chinnathambi is currently a computer science and engineering professor at Adhiparasakthi Engineering College, Tamil Nadu, India. She received her Bachelor's degree from Madras University, her Master's degree from Anna University, and her Doctorate from Pondicherry University. She has published papers in reputed International Journals, Conferences, and has published patents. Her areas of specialization include Machine Learning, Data Science, Software Architecture Evaluation, Genetic Algorithms, and MCDM. She served as a reviewer for Elsevier, ETRI, and some reputed journals and as an author for Book chapters in Wiley and IGI Global. Her academic dedication has been recognized through various awards, including the "Women Leadership Award" by the Computer Society of India and the "Young Researcher Award" for contributions to Science and Technology.