Inhwan Lee

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About

Inhwan Lee is a pioneering researcher at the intersection of machine learning, optical sensing, and robotics, with a primary focus on revolutionizing food quality assessment and processing. His most impactful work, "Integrating machine learning, optical sensors, and robotics for advanced food quality assessment and food processing" (2025, 19 citations), introduces a transformative approach that leverages machine learning to extract critical features from high-dimensional optical sensor data. This innovation enables non-destructive, real-time food quality evaluation, overcoming the limitations of traditional destructive and labor-intensive methods. Lee’s contributions extend to tactile sensing and flexible electronics, as demonstrated in his studies on improved flexible tactile sensor sensitivity (2015, 9 citations) and the development of epoxy-based flexible electrical conductors (2023, 4 citations). His work is notable for bridging the gap between advanced computational techniques and practical industrial applications, offering scalable solutions for real-time decision-making in food processing. With a growing citation impact, Lee’s research is shaping the future of smart food quality systems, making him a key figure in the integration of AI and robotics for sustainable food technology.