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English
Engineering Science Reference
30 January 2026
Sustainable innovations in statistics and data science are increasingly vital in tackling complex global challenges such as climate change, public health crises, and resource management. By developing and applying advanced analytical methods, these fields enable more efficient, equitable, and informed decision-making across sectors. Integrating sustainability into data practices ensures that technologies support long-term environmental, social, and economic goals. This intersection not only enhances the accuracy and relevance of insights but also promotes ethical data use aligned with global sustainability standards. Sustainable Innovations in Statistics and Data Science brings together cutting-edge research, methodologies, and applications that address sustainability challenges across various fields. It delves into insights, techniques, and case studies that drive sustainable outcomes in environmental science, healthcare, urban planning, and other critical areas. Covering topics such as air pollution, environmental science, and urban development, this book is an excellent resource for researchers, academicians, graduate and postgraduate students, data science and statistics practitioners, policymakers, government officials, industry leaders, innovators, educators, curriculum developers, and more.
Edited by:   , , ,
Imprint:   Engineering Science Reference
Country of Publication:   United States
Dimensions:   Height: 254mm,  Width: 178mm, 
ISBN:   9798337314556
Pages:   376
Publication Date:  
Audience:   College/higher education ,  Professional and scholarly ,  Primary ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active

Rajesh R A distinguished professor in the Department of Statistics and Data Science at CHRIST (Deemed to be University), with a strong foundation in computer science and over two decades of teaching and research experience, Dr. Rajesh R holds a Ph.D. in Computer Science, two master’s degrees, and has an extensive academic portfolio. His expertise spans machine learning, data structures, algorithm optimization, and big data analytics. Dr. Rajesh has been instrumental in mentoring and supervising several Ph.D. scholars, many of whom have successfully defended their theses in cutting-edge areas such as data compression, medical imaging, and machine learning applications in healthcare, with a focus on real-world implementations. He has authored two textbooks on Visual C++ and published extensively, with over 55 research articles. Dr. Rajesh holds one granted patent and has multiple patent applications to his credit. He is an active member of various professional organizations and editorial boards, contributing significantly to the advancement of knowledge in his field. His exemplary contributions to education and leadership have earned him the Venus International Foundation’s Outstanding Faculty Award and the Dewang Mehta Education Leadership Award. Walaa H. El-Ashmawi is an Associate Professor at the Faculty of Computer Science, Misr International University, on leave from Suez Canal University, Egypt. She received her B.Sc. in 2001 and M.Sc. in 2008 from Egypt. She got her PhD. Degree in 2013 from Computer Science Department, College of Information Science and Engineering, Hunan University, China. Her research interests span various domains in the area of Computer Science including Artificial and Computational Intelligence, Meta-heuristic algorithms Optimization problems, and Machine Learning techniques. She is the author of over 40 published papers in various international journals and conferences. She led different administrative and academic positions as full-time and part-time. For more information, contact Dr. Walaa via email at w.hashmawi@ci.suez.edu.eg or walaa.hassan@miuegypt.edu.eg. Dr. Yousuf Nasser Said Al Husaini is an Assistant Dean and Assistant Professor at the Faculty of Computer Studies, Arab Open University - Oman. Dr. Al Husaini has actively contributed to multiple funded research projects, exploring innovative solutions. His research interests include Block chain, Artificial Intelligence, Machine and Deep learning and its applications in education and healthcare. He is also involved in various academic and professional committees, presenting his work at international conferences and serving as a reviewer for multiple prestigious journals and conferences. Dr. Jeevanand Edavazhikkal Sarvothama Shenoi , a distinguished professor at the Department of Statistics and Data Science at Christ University, Bangalore, is a prolific researcher and a committed mentor. Born in Chendamangalam, Kerala, to a farmer and a schoolteacher, he pursued his higher education in statistics, culminating in a Ph.D. from Cochin University of Science and Technology (CUSAT). With a career spanning over 30 years, Dr. Jeevanand has significantly contributed to Bayesian inference, reliability theory, and data analytics. He has published 65 research papers and completed over 700 consultancy projects. However, it is his commitment to mentorship, guiding young researchers, and actively engaging in academic research and teaching that truly sets him apart.

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