Kuntal Ghosh
Papers
2
Total Citations
6
H-Index
2
About
Kuntal Ghosh is a researcher whose work spans the critical domains of renewable energy optimization and machine learning. His contributions are particularly notable for addressing real-world inefficiencies in solar power generation and advancing reinforcement learning algorithms. In his 2016 study, Ghosh tackled a persistent challenge in rooftop solar photovoltaic (SPV) arrays: non-uniform illumination (NUI) caused by the sun’s movement. He developed a novel method to predict these irregular illumination patterns, a breakthrough that helps mitigate significant power losses and enhances the long-term reliability of stand-alone solar systems. More recently, Ghosh has ventured into artificial intelligence, exploring how the coupling of exploration and learning rates can optimize scaled reinforcement learning. His 2023 paper on this topic, which has already garnered 4 citations, demonstrates his ability to bridge theoretical concepts with practical algorithmic improvements. With a total of 6 citations across his key works, Ghosh’s research is steadily gaining recognition for its practical impact—offering solutions that improve energy efficiency and intelligent system design, making him a promising voice in sustainable technology and AI integration.
Research Focus
Key Achievements
Top Papers
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