Jaydip Sen

Praxis Business School

Jaydip Sen is a professor in the Department of Data Science, Praxis Business School, Kolkata, India. His research areas include security and privacy issues in wireless ad hoc and sensor networks, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has published more than 200 papers in reputed indexed journals, refereed international conference proceedings, and 18 book chapters. He has authored three books and edited ten volumes. He is the editor of Knowledge Decision Support Systems in Finance and serves on the technical program committees of several high-ranked international conferences of the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM). He has contributed to several standardization efforts of the IEEE, including the 802.16m standards and the 3GPP LTE standards. Prof. Sen has been listed among the top 2% of scientists in the world by Stanford University for the last five consecutive years (2019–2023).

Jaydip Sen

9books edited

13chapters authored

Latest work with IntechOpen by Jaydip Sen

In the current era of pervasive computing and the Internet of Things (IoT), where technology seamlessly integrates into our environment and everyday objects, Wireless Sensor Networks (WSNs) will play increasingly critical roles in several applications and use cases. WSNs find diverse applications in the real world, including monitoring pollution levels in the environment and soil moisture for agriculture, as well as monitoring healthcare patients, traffic, and more. However, the design, optimization, and deployment of such networks face several challenges, including robust architectural design for complex applications, efficient routing, security and privacy of computing and communication, delay minimization, fault tolerance, and maintaining the quality of service in real-time applications. This book presents cutting-edge research and innovative applications in WSNs in various areas such as key management and security, efficiency in routing, machine learning models for dynamic adaptation, and temperature sensing. It is a valuable resource for researchers, engineers, practitioners, and graduate and doctoral students.

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