Yogendra Kumar

Papers

Total Citations

H-Index

About

Yogendra Kumar is an emerging researcher whose work spans the critical intersection of artificial intelligence, robotics, and computer vision. His primary research areas include software reliability analysis, underwater image enhancement, and assistive robotics for elderly care. Kumar’s most cited work, "Software Reliability Analysis with Various Metrics using Ensembling Machine Learning Approach" (17 citations), introduces ensemble learning techniques to improve software quality assurance, addressing a fundamental challenge in dependable systems. He has also made notable contributions to autonomous security systems, proposing the integration of robotics for military border surveillance to enhance national security. In the domain of marine technology, Kumar’s 2025 study on "Advancing Underwater Image Enhancement Using Hybrid Deep Learning Models" tackles the persistent problems of color distortion and light scattering in aquatic environments, with applications in marine biology and underwater exploration. Additionally, his work on microrobots for elderly care leverages advanced AI to address the critical societal need for in-home assistance technologies. While still early in his career, Kumar’s diverse portfolio demonstrates a commitment to solving real-world problems through innovative machine learning and robotic solutions, positioning him as a promising voice in applied AI research.