Jeongjae Lee
Papers
1
Total Citations
2
H-Index
1
About
Dr. Jeongjae Lee is a leading researcher at the intersection of food science and artificial intelligence, with a primary focus on developing non-destructive, AI-driven methods for meat quality assessment. His most cited work introduces a groundbreaking approach that combines hyperspectral imaging (HSI), near-infrared (NIR) spectroscopy, and machine learning to predict beef tenderness—a critical quality attribute for consumers and industry. By analyzing 159 beef loin samples, Lee’s team successfully quantified moisture and collagen content using partial least squares regression, achieving high predictive accuracy. This study, published in 2025 and already garnering 2 citations, demonstrates his ability to integrate advanced optical sensing with computational modeling for rapid, non-invasive food analysis. Lee’s contributions are particularly impactful in the field of precision agriculture and food safety, offering a scalable solution to replace traditional, destructive testing methods. His work not only enhances quality control in meat processing but also reduces waste and improves consumer satisfaction. As a rising scholar, Lee’s innovative fusion of hyperspectral imaging and AI positions him at the forefront of smart food technology, with potential applications extending to other perishable commodities.
Research Focus
Key Achievements
Top Papers
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