Seyeon Lee

50 papers receiving 534 citations

Peers

Seyeon Lee
Comparison fields: 5 of 96
  • Condensed Matter Physics 201
  • Artificial Intelligence 148
  • Electrical and Electronic Engineering 215
  • Biomedical Engineering 154
  • Control and Systems Engineering 67
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Gaurav Nanda United States
Jiyuan Zheng United States
Shan Lin China
Md Shafayat Hossain United States
Felix Schmitt Germany
Alexander Müller Germany
A.L. Beck United States
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Citations per field
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Citations per year

Countries citing papers authored by Seyeon Lee

Since Specialization
Citations

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

Fields of papers citing papers by Seyeon Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202080
2 201651
3 202236
4
Pre-training Text-to-Text Transformers for Concept-centric Common Sense
202130
5 200929
6 200728
7 201123
8 201121
9 202118
10 202118
11 202116
12 201415
13 201012
14 201112
15 202111
16 201011
17 202110
18 202010
19 20218
20 20178

About Seyeon Lee

Seyeon Lee is a scholar working on Electrical and Electronic Engineering, Condensed Matter Physics, Biomedical Engineering, Sociology and Political Science and Information Systems, having authored 53 papers that have together received 554 indexed citations. Recurring topics across this work include Superconducting Materials and Applications (19 papers), Physics of Superconductivity and Magnetism (19 papers), Frequency Control in Power Systems (11 papers), Topic Modeling (5 papers), Natural Language Processing Techniques (4 papers), Sustainability in Higher Education (4 papers), Educational Research and Pedagogy (3 papers) and Design Education and Practice (3 papers). The work is most often cited by research in Condensed Matter Physics (201 citations), Artificial Intelligence (148 citations), Electrical and Electronic Engineering (215 citations), Biomedical Engineering (154 citations) and Control and Systems Engineering (67 citations). Seyeon Lee has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Xiang Ren, Bill Yuchen Lin, Kyeongdal Choi, Ji-Kwang Lee, Rahul Khanna, Woo‐Seok Kim, Song–Yop Hahn, Chan Park, Young Yim Doh and Ki-Chul Seong. Their work appears in journals such as IEEE Transactions on Applied Superconductivity, International Journal of Sustainability in Higher Education, Development Policy Review, Frontiers in Psychology and Journal of Nanoscience and Nanotechnology.

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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