Heena Kwatra, Dr. S. Ananthi, Dr. Mohammad Irshad, Dr. S. Muthurajan
Indexed In: Google scholar
Release Date: To be updated | Copyright:©2026 | Pages: 594
ISBN10: 0 | ISBN13: 0
Artificial Intelligence, Machine Learning, and Cloud Computing in Higher Education: Intelligent Learning Systems, Analytics, and Digital Transformation explores how emerging technologies are reshaping modern academia. The book examines AI-driven personalized learning, machine learning–based predictive analytics, and scalable cloud infrastructures that enhance teaching, research, and administration. It highlights intelligent tutoring systems, data-informed decision-making, and adaptive learning environments that improve student outcomes. Additionally, it addresses challenges such as data privacy, ethical considerations, and digital equity. Through case studies and practical insights, the book provides educators, researchers, and policymakers with strategies to harness technology for innovation, efficiency, and sustainable transformation in higher education.
The book covers the integration of artificial intelligence, machine learning, and cloud computing in higher education systems. It explores intelligent learning platforms, adaptive and personalized education models, and predictive analytics for student performance and retention. Topics include cloud-based infrastructure for scalable education delivery, data-driven decision-making, and automation in academic administration. It also addresses ethical issues such as data privacy, security, and bias in AI systems. Case studies, frameworks, and real-world applications are presented to illustrate digital transformation in universities. The coverage supports educators, researchers, and policymakers in understanding and implementing advanced technologies for improved teaching, learning, and institutional effectiveness.
Heena Kwatra is an Assistant Professor in the Department of Computer Science and Engineering at Bharati Vidyapeeth’s College of Engineering, New Delhi. She is actively engaged in teaching and academic activities while working in the areas of edge computing and deep learning. Her work focuses on developing lightweight AI models for real-time activity and health monitoring on edge devices. She has experience in computer vision, machine learning, and embedded AI applications. Her academic interests include intelligent edge systems, real-time object detection, and AI-driven monitoring solutions.
Dr. S. Ananthi has 10 years of experience in Research and Engineering Education. She has received her Master’s and PhD in Computer Science and Engineering from Annamalai University, Chidambaram. Her major research areas include Machine Learning, Artificial Intelligence, Digital Twin, and Cloud Computing. She worked as a Project fellow in UGC Major Research Funded Project (UGC MRP – Delhi) with grant of Rs. 30 Lakh. She has authored more than 40 research papers in reputed International Journals and IEEE conferences. She also authored 2 books in Artificial Intelligence and Cyber Security. She is a passionate researcher and also reviewer for IEEE Conferences and EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing. She served as a resource person and keynote speaker at various conferences and events. She has also participated in more than 25 International conferences and Won best paper awards. She has 10 patents, 317 Citations, 11 h-index and 12 i10-index. She is an AWS Certified Cloud Practitioner (CLF-01). She is an AWS Academy certified Educator and has eligibility to handle 16 Cloud related courses in AWS academy. She is an Intel Certified Instructor for Machine Learning, one API C SYCL Essentials, CUDA to C SYCL and Intel Rendering Toolkit. She also completed various industry internships from various companies on Cloud, DevOps, Artificial Intelligence, Machine Learning, Python and Data Analytics.
Dr. Mohammad Irshad is an Associate Professor at Saveetha School of Engineering, SIMATS, Chennai. His research focuses on conventional control techniques, evolutionary algorithm based optimal and robust control, IoT-based automation, and smart technologies, integrating theory with practical engineering innovation.
Dr. S. Muthurajan is an Assistant Professor in the Department of Marine Engineering at the Academy of Maritime Education and Training (AMET) deemed to be University, Chennai. He teaches Electrical and Electronics Engineering subjects for marine engineering students, including power electronics, automation, and industrial electronics. He is actively engaged in teaching, curriculum development, and academic activities related to engineering education. Him academic interests include artificial intelligence, automation technologies, intelligent systems, and the application of emerging digital technologies in engineering and maritime education. He is also involved in research, academic publications, and collaborative initiatives aimed at integrating modern technological advancements into engineering learning and practice.
