Junbo Li

37 papers receiving 434 citations

Peers

Junbo Li
Comparison fields: 5 of 88
  • Algebra and Number Theory 154
  • Geometry and Topology 161
  • Statistical and Nonlinear Physics 110
  • Mathematical Physics 31
  • Management Science and Operations Research 42
Replace K. J. Harrison with:
K. J. Harrison Australia
Β Neumann Australia
Katsuhiro Uno Japan
Judith Palagallo United States
Joseph P. Brennan United States
I. Lukovits Hungary
Daniel B. Shapiro United States
Erica Flapan United States
Junbo Li relative to K. J. Harrison Australia K. J. Harrison's profile →
Citations per field
00.5×10×15×20×24.5×
K. J. Harrison · 1×
Citations per year

Countries citing papers authored by Junbo Li

Since Specialization
Citations

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

Fields of papers citing papers by Junbo Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012122
2 200838
3 200928
4 202026
5 200826
6 201426
7 202225
8 202119
9 200816
10 201214
11 201312
12 201011
13 201311
14 20227
15 20136
16 20125
17 19995
18 20224
19 20124
20 20204

About Junbo Li

Junbo Li is a scholar working on Geometry and Topology, Algebra and Number Theory, Statistical and Nonlinear Physics, Management Science and Operations Research and Artificial Intelligence, having authored 41 papers that have together received 438 indexed citations. Recurring topics across this work include Algebraic structures and combinatorial models (15 papers), Advanced Topics in Algebra (13 papers), Nonlinear Waves and Solitons (11 papers), Multi-Criteria Decision Making (6 papers), 2D Materials and Applications (2 papers), Homotopy and Cohomology in Algebraic Topology (2 papers), Neural Networks and Applications (2 papers) and Subterranean biodiversity and taxonomy (2 papers). The work is most often cited by research in Algebra and Number Theory (154 citations), Geometry and Topology (161 citations), Statistical and Nonlinear Physics (110 citations), Mathematical Physics (31 citations) and Management Science and Operations Research (42 citations). Junbo Li has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yucai Su, Jian‐qiang Wang, Yang Zhao, Yanli Zhao, Yuechao Wu, Chengyuan Wang, Gang Li, Junkuo Gao, Huacheng Zhang and Qichun Zhang. Their work appears in journals such as Journal of Intelligent & Fuzzy Systems, Applied Physics Letters, Journal of Forecasting, Zootaxa and Journal of Geochemical Exploration.

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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