Sungsu Lim

799 citations
49 papers · 455 · h-index 13

Impact in

Papers in

Sungsu Lim

41 papers receiving 436 citations

Peers

Sungsu Lim
Comparison fields: 5 of 88
  • Statistical and Nonlinear Physics 188
  • Artificial Intelligence 188
  • Computer Networks and Communications 119
  • Signal Processing 50
  • Transportation 23
Replace Shanqing Yu with:
Shanqing Yu China
Ronghui Hou China
Taotao Cai Australia
Haicheng Tao China
Qi Cao China
Weidong Xiao China
Peng Jia China
Anupam Biswas India
Yingtong Dou United States
Alper Özcan Türkiye
Sungsu Lim relative to Shanqing Yu China Shanqing Yu's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sungsu Lim

Since Specialization
Citations

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

Fields of papers citing papers by Sungsu Lim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201462
2 202259
3 201330
4 202223
5 200622
6 201820
7 201120
8 201418
9 201317
10 202116
11 201614
12 201613
13 201312
14 202311
15 201611
16 201111
17 202110
18 202310
19 201310
20 20157

About Sungsu Lim

Sungsu Lim is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Computer Networks and Communications and Information Systems, having authored 49 papers that have together received 455 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (23 papers), Advanced Graph Neural Networks (12 papers), Opinion Dynamics and Social Influence (9 papers), Advanced Clustering Algorithms Research (5 papers), Peer-to-Peer Network Technologies (3 papers), Digital and Cyber Forensics (3 papers), Graph Theory and Algorithms (3 papers) and Transportation Planning and Optimization (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (188 citations), Artificial Intelligence (188 citations), Computer Networks and Communications (119 citations), Signal Processing (50 citations) and Transportation (23 citations). Sungsu Lim has collaborated with scholars based in South Korea, United States and Hong Kong. Frequent co-authors include Jae-Gil Lee, Kyomin Jung, Byung Suk Lee, Won-Yong Shin, Hwan Kim, Jungeun Kim, Sejeong Kwon, Cheng Xiang, John C. S. Lui and Minhoo Kim. Their work appears in journals such as Information Sciences, IEEE Access, The European Physical Journal B, PLoS ONE and Mathematical and Computer Modelling.

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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