Sunil Kumar Gupta

University of Petroleum and Energy Studies

Papers

Total Citations

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About

Sunil Kumar Gupta is a researcher at the forefront of applying artificial intelligence and machine learning to the critical domain of food science and nutrition. His work centers on developing computational models that can decode the complex relationships between food composition, nutrient profiles, and human health outcomes. In his most-cited paper, "Artificial Intelligence and Machine Learning Approaches for Understanding Food and Nutrients" (2023), Gupta provides a comprehensive framework for how AI can revolutionize dietary assessment, personalized nutrition, and food safety. This work has already garnered attention, accumulating 3 citations and laying the groundwork for a new generation of data-driven nutritional research. Gupta’s contributions are particularly notable for bridging the gap between advanced computational techniques and practical applications in public health, offering tools that can analyze vast datasets to uncover hidden patterns in dietary habits and nutrient interactions. His research holds promise for enabling personalized dietary recommendations, improving food quality monitoring, and ultimately enhancing global health outcomes through smarter, AI-powered nutritional insights.