Seung Hyun Kim Data-verified

OverviewAI-generated summary

Seung Hyun Kim's research focuses on the application of advanced computational techniques, particularly deep learning and machine learning, to address challenges in diverse fields such as medicine, materials science, and public health. He has investigated the use of deep semi-supervised learning for automatic segmentation of the inferior alveolar nerve using convolutional neural networks and developed deep learning algorithms for real-time counting of wheezing events from lung sounds, with implications for disease prediction and early intervention. His work also extends to materials science, where he has explored the inverse design of high-strength medium-Mn steel using machine learning-aided genetic algorithms.

Kim has also contributed to health sciences by analyzing factors affecting neutralizing antibody production after COVID-19 vaccination and comparing nicotine dependence and biomarker levels among different tobacco product users. Further research includes studying alterations in lung microbial communities in obese allergic asthma and the immune response evoked by oral lymphatic delivery of specific compounds. His scholarly output is reflected in a h-index of 29, over 164 publications, and more than 3,300 citations, designating him as a highly cited researcher.

Metrics

• h-index: 29
• Publications: 164
• Citations: 3,312