S. Rajaram

|Rajaram Sivasubramanian - Editor|Dr. S. Rajaram is currently working as a Professor and Head in the Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Madurai – 15 (A Govt. Aided Autonomous Institution Affiliated to Anna University) Tamilnadu, India. He obtained his B.E degree in Electronics & Communication Engineering from Thiagarajar College of Engineering, Madurai, in the year of 1994, and his M.E. degree in the specialization of Microwave and Optical Engineering from Alagappa Chettiar College of Engineering and Technology in the year of 1996. He obtained his Ph.D. degree in the year 2008 from Anna University, Chennai. He did his Post-Doctoral Research at the Georgia Institute of Technology, Atlanta, USA. He is a recognized Ph. D Supervisor at Anna University, Chennai, and guided more than 15 Ph.D. scholars. He has published more than 250 research articles around the world including reputed journal transactions like IEEE, IET, Springer, Taylor & Francis, and Elsevier.

Publications

5G and Fiber Optics Security Technologies for Smart Grid Cyber Defense
5G and Fiber Optics Security Technologies for Smart Grid Cyber Defense
G. Prabhakar, N. Ayyanar, S. Rajaram. © 2024. 519 pages.
In the digital age, smart grids stand as the backbone of modern energy systems, facilitating efficient energy distribution and management. However, this sophistication comes at...
Machine Learning Optimization Techniques for 3D IC Physical Design
Machine Learning Optimization Techniques for 3D IC Physical Design
Gracia Nirmala Rani D., J. Shanthi, S. Rajaram. © 2020. 15 pages.
The importance and growth of the digital IC have become more popular because of parameters such as small feature size, high speed, low cost, less power consumption, and...
Data Classification: Its Techniques and Big Data
Data Classification: Its Techniques and Big Data
A. Sheik Abdullah, R. Suganya, S. Selvakumar, S. Rajaram. © 2017. 18 pages.
Classification is considered to be the one of the data analysis technique which can be used over many applications. Classification model predicts categorical continuous class...