Soon‐Geul Lee

2.3k citations
131 papers · 1.8k · h-index 24

Impact in

Papers in

Soon‐Geul Lee

113 papers receiving 1.8k citations

Peers

Soon‐Geul Lee
Comparison fields: 5 of 102
  • Control and Systems Engineering 1.3k
  • Automotive Engineering 432
  • Mechanical Engineering 639
  • Computer Vision and Pattern Recognition 227
  • Mechanics of Materials 190
Replace Xincheng Tian with:
Xincheng Tian China
Javier Cuadrado Spain
Jae‐Bok Song South Korea
Aurelio Piazzi Italy
Mohamed Abderrahim Spain
Tatsuo Narikiyo Japan
Goele Pipeleers Belgium
M. F. Golnaraghi Canada
Rui Song China
Gianni Ferretti Italy
Soon‐Geul Lee relative to Xincheng Tian China Xincheng Tian's profile →
Citations per field
00.5×3.3×
Xincheng Tian · 1×
Citations per year

Countries citing papers authored by Soon‐Geul Lee

Since Specialization
Citations

This map shows the geographic impact of Soon‐Geul Lee's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Soon‐Geul Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Soon‐Geul Lee more than expected).

Fields of papers citing papers by Soon‐Geul Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Soon‐Geul Lee. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Soon‐Geul Lee. The network helps show where Soon‐Geul Lee may publish in the future.

Co-authors

The 25 scholars most cited alongside Soon‐Geul Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Soon‐Geul Lee Line = papers co-authored together Soon‐Geul Lee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 131 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013116
2 2013114
3 201191
4 201274
5 201373
6 201771
7 201370
8 201359
9 201457
10 201755
11 201351
12 201345
13 201441
14 201841
15 201336
16 201432
17 201331
18 200730
19 201330
20 201530

About Soon‐Geul Lee

Soon‐Geul Lee is a scholar working on Control and Systems Engineering, Biomedical Engineering, Mechanical Engineering, Automotive Engineering and Computer Vision and Pattern Recognition, having authored 131 papers that have together received 1.8k indexed citations. Recurring topics across this work include Dynamics and Control of Mechanical Systems (43 papers), Control and Dynamics of Mobile Robots (20 papers), Vibration and Dynamic Analysis (19 papers), Vehicle Dynamics and Control Systems (16 papers), Robotic Locomotion and Control (16 papers), Robotics and Sensor-Based Localization (14 papers), Robotic Path Planning Algorithms (14 papers) and Hydraulic and Pneumatic Systems (13 papers). The work is most often cited by research in Control and Systems Engineering (1.3k citations), Automotive Engineering (432 citations), Mechanical Engineering (639 citations), Computer Vision and Pattern Recognition (227 citations) and Mechanics of Materials (190 citations). Soon‐Geul Lee has collaborated with scholars based in South Korea, Vietnam and Japan. Frequent co-authors include Lê Anh Tuấn, Jae-Jun Kim, Viet-Hung Dang, Won Gu Lee, Yong Tae Kang, Byung‐Soo Kim, Jung‐Yeul Jung, Jae Won Lee, Donghan Kim and Nak Young Chong. Their work appears in journals such as International Journal of Precision Engineering and Manufacturing, Mechanical Systems and Signal Processing, Journal of Vibration and Control, International Journal of Refrigeration and International Journal of Robust and Nonlinear Control.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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