The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Hyoungkwan Kim sits on this spectrum.
This scientist: 145 publications — 25th percentile
25% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 804 publications or more.
The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Hyoungkwan Kim sits on this spectrum.
This scientist: 42 D-Index — 35th percentile
35% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 107 D-Index or more.
Hyoungkwan Kim is a researcher affiliated with Yonsei University in South Korea, with a focus on engineering and earth and planetary sciences. Their academic work spans several interdisciplinary areas, including civil and structural engineering, geology, computer vision and pattern recognition, building and construction, and artificial intelligence.
The primary research topics covered by Kim include infrastructure maintenance and monitoring, 3D surveying and cultural heritage, building information modeling (BIM) and construction integration, construction engineering and safety, advanced neural network applications, robotics and sensor-based localization, and remote sensing and LiDAR applications.
Kim's recent published papers cover topics involving the intersection of artificial intelligence and construction automation. Notable publications include:
The frequent collaborators in Kim's research include Juhyeon Kim, Jeehoon Kim, Duho Chung, Seongdeok Bang, and Somin Park. These co-authorships suggest a collaborative approach to research within the fields of construction automation and data-driven infrastructure analysis.
Kim's scholarly articles appear primarily in venues focused on civil engineering and construction technology. The most frequent publication outlets are:
The research spans multiple subfields reflecting an integration of traditional engineering disciplines with emerging technologies such as artificial intelligence and robotics, particularly applied to construction and infrastructure monitoring. This includes development and application of deep learning techniques for 3D reconstruction and synthetic data generation, as well as the use of transformer-based models for damage information retrieval.
JoonOh Seo;SangUk Han;SangHyun Lee;Hyoungkwan Kim
Seongdeok Bang;Somin Park;Hongjo Kim;Hyoungkwan Kim
Hongjo Kim;Hyoungkwan Kim;Yong Won Hong;Hyeran Byun
Kyeongseok Kim;Hyoungbae Park;Hyoungkwan Kim
Kinam Kim;Hongjo Kim;Hyoungkwan Kim
Changyoon Kim;Taeil Park;Hyunsu Lim;Hyoungkwan Kim
Mohamed Al-Hussein;Muhammad Athar Niaz;Haitao Yu;Hyoungkwan Kim
Hongjo Kim;Kinam Kim;Hyoungkwan Kim
Du Y. Kim;Seung H. Han;Hyoungkwan Kim;Heedae Park
Junhao Zou;Junhao Zou;Hyoungkwan Kim;Hyoungkwan Kim
Seung Heon Han;Sungmin Yun;Hyoungkwan Kim;Young Hoon Kwak
Changyoon Kim;Byoungil Kim;Hyoungkwan Kim
Francis Baek;Inhae Ha;Hyoungkwan Kim
Inhae Ha;Hongjo Kim;Somin Park;Hyoungkwan Kim
Somin Park;Seongdeok Bang;Hongjo Kim;Hyoungkwan Kim
Seung H. Han;Du Y. Kim;Hyoungkwan Kim
Seongdeok Bang;Hongjo Kim;Hyoungkwan Kim
Seongdeok Bang;Francis Baek;Somin Park;Wontae Kim
Hongjo Kim;Hongjo Kim;Seongdeok Bang;Hoyoung Jeong;Youngjib Ham
Unknown
Seung H. Han;Sang H. Park;Du Y. Kim;Hyoungkwan Kim
Byungil Kim;Hyounkyu Lee;Hyungbae Park;Hyoungkwan Kim
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