Jayesh Rane
Papers
7
Total Citations
127
H-Index
6
About
Jayesh Rane is an emerging researcher whose work sits at the dynamic intersection of artificial intelligence, industry transformation, and corporate systems. His scholarship spans machine learning, deep learning, natural language processing, generative AI, and their real-world applications across finance, manufacturing, and construction. In 2024 alone, Rane produced a remarkable body of highly cited work, establishing himself as a prolific voice in applied AI research. His most influential contribution, "Artificial Intelligence-driven corporate finance" (49 citations), explores how machine learning, NLP, and robotic process automation can revolutionize corporate governance, sustainability, and financial decision-making. Equally notable is his investigation into how generative AI models like ChatGPT are accelerating the transition toward Industry 4.0, 5.0, and Society 5.0 frameworks (24 citations), positioning intelligent automation as a cornerstone of future industrial and social development. His technical review of deep learning optimization algorithms (19 citations) further demonstrates his command of foundational AI methodology. Rane also addresses practical adoption challenges, examining AI implementation in construction and business analytics contexts. With over 120 cumulative citations across seven papers published within a single year, Jayesh Rane is rapidly carving out a distinctive and impactful presence in interdisciplinary AI research.
Research Focus
Key Achievements
Top Papers
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- 3Techniques and optimization algorithms in deep learning: A review19 citations · 2024
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