Bio
Rahul Reddy Nadikattu is a Ph.D. student in Information Technology at the University of the Cumberlands, based in San Jose, United States. His research interests span a wide array of computing disciplines, including artificial intelligence, machine learning, computer networks, and software engineering. He has authored a paper on the comparative study of machine learning and extreme learning machine techniques for breast cancer diagnosis. Beyond his own research, Rahul has actively contributed to the academic community as a reviewer and editor for the Global Journal of Computer Science and Technology (GJCST), where he has handled numerous manuscripts across various computer science domains. His work reflects a deep engagement with both theoretical and applied aspects of computing, from VLSI characterization to AI-driven compliance monitoring.
Educational Journey
University of the Cumberlands
Ph.D in Information Technology, Masters in Computer Engineering • Information Technology
University of the Cumberlands
Master of Science in Computer Information Systems • Information Technology
University of the Cumberlands
MS degree in Information Systems Security • Information Systems Security
Experience
Ph.D. Student
0 - 0 • Department of Information TechnologyGrants and Awards
Fellowship in Information Technology
Research
A Comparative Study between a Simulation of Machine Learning and Extreme Learning Machine Techniques on Breast Cancer Diagnosis
Breast Cancer is a developing and most normal disease among ladies around the globe. Breast malignancy is an uncontrolled and exorbitant development of abnormal cells in the Breast because of hereditary, hormonal, and way of life factors. During the starting stages, the tumor is restricted to the Breast, and in the latter part, it can spread to lymph hubs in the armpit and different organs like the liver, bones, lungs, and cerebrum. At the point when the bosom disease spreads to different pieces of the body, it is going to metastasize. The sickness is repairable in the beginning periods, yet it is identified in later stages, which is the fundamental driver for the passing of such a large number of ladies in this entire world. Clinical tests led in medical clinics for deciding the malady are a lot of costly, just as tedious as well.
