Yogesh Kumar

Punjab Engineering College, Uttarakhand Technical University, University of Petroleum and Energy Studies

Papers

Total Citations

133

H-Index

About

Yogesh Kumar is a prolific researcher whose work sits at the dynamic intersection of artificial intelligence, machine learning, and their real-world applications. His research spans several high-impact domains, including healthcare informatics, computer vision, and deep reinforcement learning, establishing him as a versatile contributor to modern AI scholarship. Kumar's most influential work, "Machine Learning Aspects and its Applications Towards Different Research Areas" (2020), has garnered 82 citations, reflecting its broad utility as a foundational reference for researchers exploring intelligent systems and statistical learning methodologies. Complementing this, his 2020 paper on machine learning and deep learning in healthcare — cited 40 times — demonstrates his commitment to translating AI advances into clinically meaningful applications, covering areas such as patient management and novel medical measure development. His 2017 systematic survey on facial expression recognition techniques highlights an early interest in human-computer interaction and computer vision, contributing to robotics and mobile application development. More recently, his 2024 empirical study comparing deep reinforcement learning algorithms for the CartPole problem underscores his expanding focus toward autonomous systems and control theory. Collectively, Kumar's body of work reflects a researcher dedicated to bridging theoretical machine intelligence with practical, societally beneficial applications across diverse technical fields.