Soomin Lee

1.0k citations
31 papers · 521 indexed · h-index 12
Topics
Distributed Control Multi-Agent Systems (14 papers)Stochastic Gradient Optimization Techniques (5 papers)Sparse and Compressive Sensing Techniques (4 papers)

In The Last Decade

Soomin Lee

28 papers receiving 509 citations

Peers

Soomin Lee
Comparison fields: 5 of 53
  • Computer Networks and Communications 350
  • Artificial Intelligence 228
  • Computational Mechanics 153
  • Management Science and Operations Research 94
  • Electrical and Electronic Engineering 61
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Maben Rabi Sweden
Jie Lu China
Kunal Srivastava United States
Akshay Kashyap United States
Shakoor Muhammad Pakistan
Robert Nishihara United States
Seyed Mehdi Abedi Pahnehkolaei Iran
Y. Xia China
Peng Hui Tan Singapore
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Citations per field
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Citations per year

Countries citing papers authored by Soomin Lee

Since Specialization
Citations

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

Fields of papers citing papers by Soomin Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Soomin Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Soomin Lee. A scholar is included among the top collaborators of Soomin Lee based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Soomin Lee. Soomin Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 0
4 3
5 3
6 14
7
Select, Extract and Generate: Neural Keyphrase Generation with Syntactic Guidance.
1
8 1
9 13
10
Blockchain Technology and the Potential Applicability in the Feed Industry
3
11 16
12 64
13 14
14 1
15 23
16 14
17 46
18 23
19 1
20 4

About Soomin Lee

Soomin Lee is a scholar working on Computer Networks and Communications, Numerical Analysis and Artificial Intelligence, having authored 31 papers that have together received 521 indexed citations. Recurring topics across this work include Distributed Control Multi-Agent Systems (14 papers), Stochastic Gradient Optimization Techniques (5 papers) and Sparse and Compressive Sensing Techniques (4 papers). The work is most often cited by research in Computer Networks and Communications (350 citations), Management Science and Operations Research (94 citations) and Computational Mechanics (153 citations). Soomin Lee has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include Angelia Nedić, Maxim Raginsky, Yi Zhou, Guanghui Lan, Michael M. Zavlanos, Alejandro Ribeiro, Tetsuo Katsuura, Xiao Bai, Santiago Paternain and Wasi Uddin Ahmad. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Automatic Control and IEEE Transactions on Signal Processing.

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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