Pradeep Kumar Singh

Central University of Jammu, Jaypee University of Information Technology, National Institute of Technology Raipur

Papers

Total Citations

H-Index

About

Pradeep Kumar Singh is a versatile researcher whose work bridges machine learning, audio processing, computer vision, and mobile ad-hoc networks (MANETs). His most impactful contribution is a comparative analysis of audio classification using MFCC and STFT features with machine learning techniques, which has garnered 66 citations since 2024, reflecting strong contemporary interest in automated audio analysis. This work demonstrates his ability to apply classical signal processing and modern ML to real-world data challenges. Singh has also contributed a comprehensive survey on object recognition and segmentation techniques (25 citations), providing a foundational resource for researchers in computer vision. His innovative side includes developing a semi-supervised self-training approach for detecting web robots in weblogs, and designing ToMRobot, a low-cost robot for MANET testbeds—addressing the critical affordability barrier that prevents many researchers from conducting real-world network experiments. Through these diverse contributions, Singh has shown a consistent focus on practical, accessible solutions, from audio classification to cost-effective robotics, making his work valuable for students and practitioners seeking applied ML and networking research.