Yan-Li Lee

422 citations
21 papers · 261 · h-index 9

Impact in

Papers in

Yan-Li Lee

18 papers receiving 256 citations

Peers

Yan-Li Lee
Comparison fields: 5 of 56
  • Statistical and Nonlinear Physics 157
  • Artificial Intelligence 174
  • Signal Processing 16
  • Transportation 9
  • Information Systems 30
Replace Timothy La Fond with:
Timothy La Fond United States
Ian X. Y. Leung United Kingdom
Matthew J. Rattigan United States
Ralitsa Angelova Germany
Ayushi Dalmia India
Krzysztof Juszczyszyn Poland
Polykarpos Meladianos France
Zhizhi Yu China
Cécile Bothorel France
Song Bian China
Yan-Li Lee relative to Timothy La Fond United States Timothy La Fond's profile →
Citations per field
00.5×10×13.8×
Timothy La Fond · 1×
Citations per year

Countries citing papers authored by Yan-Li Lee

Since Specialization
Citations

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

Fields of papers citing papers by Yan-Li Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201976
2 202058
3 202040
4 202314
5 202213
6 202410
7 202410
8 20219
9 20178
10 20247
11 20246
12 20243
13 20242
14 20241
15 20191
16 20221
17 20211
18 20221
19 20250
20 20250

About Yan-Li Lee

Yan-Li Lee is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Molecular Biology, Information Systems and Computer Networks and Communications, having authored 21 papers that have together received 261 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (13 papers), Advanced Graph Neural Networks (5 papers), Opinion Dynamics and Social Influence (4 papers), Bioinformatics and Genomic Networks (4 papers), Recommender Systems and Techniques (4 papers), Data Management and Algorithms (2 papers), Peer-to-Peer Network Technologies (2 papers) and Sentiment Analysis and Opinion Mining (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (157 citations), Artificial Intelligence (174 citations), Signal Processing (16 citations), Transportation (9 citations) and Information Systems (30 citations). Yan-Li Lee has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Tao Zhou, Dong Hao, Ye Yuan, Guannan Wang, Cong Wang, Duanbing Chen, Yajun Du, Liming Pan, Xianyong Li and Kexin Yang. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, Information Sciences, Applied Mathematics and Computation, Expert Systems with Applications and Information Fusion.

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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