Seung Hyun Kim Source Confirmed

OverviewAI-generated summary

Seung Hyun Kim's research interests encompass the application of advanced computational techniques, particularly deep learning and machine learning, to address challenges in diverse scientific domains. His work includes the development of algorithms for automatic segmentation of anatomical structures, such as the inferior alveolar nerve, utilizing convolutional neural networks.

Kim has investigated the real-time counting of wheezing events from lung sounds using deep learning, with implications for disease prediction and early intervention. His research also extends to the inverse design of materials, such as high-strength medium-Mn steel, employing machine learning-aided genetic algorithms. Furthermore, his publications demonstrate a focus on analyzing factors affecting biological responses, including neutralizing antibody production after COVID-19 vaccination and alterations in lung microbial communities in conditions like obese allergic asthma.

With a significant publication record (161 publications) and a citation count of 3,252, Kim holds an h-index of 29. He is recognized as a highly cited researcher. His collaborative network includes researchers such as Mayumi Nakagawa from the University of Arkansas for Medical Sciences.

Metrics

• h-index: 29
• Publications: 161
• Citations: 3,252