Jin S. Lee

1.9k citations
70 papers · 1.5k indexed · h-index 20

Impact in

Papers in

Jin S. Lee

70 papers receiving 1.4k citations

Peers

Jin S. Lee
Comparison fields: 5 of 86
  • Control and Systems Engineering 826
  • Mechanical Engineering 300
  • Computer Vision and Pattern Recognition 161
  • Artificial Intelligence 227
  • Biomedical Engineering 294
Replace Luc Baron with:
Luc Baron Canada
Tatsuo Narikiyo Japan
Ching‐Chang Wong Taiwan
Sung‐Soo Kim South Korea
Zafer Bingül Türkiye
Alan S. Morris United Kingdom
Rochdi Merzouki France
Claudia‐Adina Bojan‐Dragos Romania
Ju-Jang Lee South Korea
Jesús Alberto Meda-Campaña Mexico
Jin S. Lee relative to Luc Baron Canada Luc Baron's profile →
Citations per field
00.5×1.5×
Luc Baron · 1×
Citations per year

Countries citing papers authored by Jin S. Lee

Since Specialization
Citations

This map shows the geographic impact of Jin S. 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 Jin S. Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin S. Lee more than expected).

Fields of papers citing papers by Jin S. Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jin S. 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 Jin S. Lee. The network helps show where Jin S. Lee may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Jin S. 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 Jin S. Lee Line = papers co-authored together Jin S. Lee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201618
2 201617
3 201636
4 2016108
5 20133
6 201335
7 20127
8 20111
9 201036
10
Design and control of mobile robot with Mecanum wheel
200916
11
Adaptive transition disturbance observer for winding machine
20091
12 20096
13 20093
14
Global finite-time convergence of TCP Vegas without feedback information delay
20079
15 20055
16 20032
17 20021
18 199931
19 19984
20 19983

About Jin S. Lee

Jin S. Lee is a scholar working on Control and Systems Engineering, Management Information Systems, Statistics and Probability, Computational Theory and Mathematics and Human-Computer Interaction, having authored 70 papers that have together received 1.5k indexed citations. Recurring topics across this work include Iterative Learning Control Systems (15 papers), Fuzzy Logic and Control Systems (11 papers), Multilevel Inverters and Converters (10 papers), Advanced DC-DC Converters (9 papers), Microgrid Control and Optimization (9 papers), Adaptive Control of Nonlinear Systems (7 papers), Control and Dynamics of Mobile Robots (7 papers) and Neural Networks and Applications (7 papers). The work is most often cited by research in Control and Systems Engineering (826 citations), Mechanical Engineering (300 citations), Computer Vision and Pattern Recognition (161 citations), Artificial Intelligence (227 citations) and Biomedical Engineering (294 citations). Jin S. Lee has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Tae‐Yong Kuc, Minsung Kim, Kwanghee Nam, Hangil Joe, Son‐Cheol Yu, Byeongcheol Han, Maolin Jin, Liang Song, Jing Meng and Chulhong Kim. Their work appears in journals such as IEEE Transactions on Industrial Electronics, ISIJ International, International Journal of Control, Advanced Robotics and Fuzzy Sets and Systems.

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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