Fabing Duan

63 papers receiving 1.2k citations

Peers

Fabing Duan
Comparison fields: 5 of 70
  • Statistical and Nonlinear Physics 946
  • Statistics, Probability and Uncertainty 426
  • Computer Networks and Communications 376
  • Statistics and Probability 90
  • Cognitive Neuroscience 190
Replace Sanya Mitaim with:
Sanya Mitaim United States
Steeve Zozor France
Zhongkui Sun China
J.H. Michels United States
Donatello Materassi United States
Stefan Klus Germany
R. Yamapi Cameroon
Alexandre Mauroy Belgium
Michael Schanz Germany
A. Venkatesan India
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Citations per year

Countries citing papers authored by Fabing Duan

Since Specialization
Citations

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

Fields of papers citing papers by Fabing Duan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002144
2 201178
3 200366
4 200460
5 200354
6 200446
7 201337
8 200636
9 200734
10 200234
11 201731
12 200630
13 201930
14 201125
15 201222
16 201522
17 201422
18 201821
19 200519
20 202119

About Fabing Duan

Fabing Duan is a scholar working on Statistical and Nonlinear Physics, Statistics, Probability and Uncertainty, Computer Networks and Communications, Molecular Biology and Cognitive Neuroscience, having authored 65 papers that have together received 1.2k indexed citations. Recurring topics across this work include stochastic dynamics and bifurcation (50 papers), Probabilistic and Robust Engineering Design (25 papers), Diffusion and Search Dynamics (15 papers), Neural dynamics and brain function (12 papers), Nonlinear Dynamics and Pattern Formation (11 papers), Ecosystem dynamics and resilience (8 papers), Distributed Sensor Networks and Detection Algorithms (7 papers) and Neural Networks and Applications (6 papers). The work is most often cited by research in Statistical and Nonlinear Physics (946 citations), Statistics, Probability and Uncertainty (426 citations), Computer Networks and Communications (376 citations), Statistics and Probability (90 citations) and Cognitive Neuroscience (190 citations). Fabing Duan has collaborated with scholars based in China, Australia and France. Frequent co-authors include François Chapeau‐Blondeau, Derek Abbott, Bohou Xu, Jianlong Li, David Rousseau, Ronghao Bao, Yan Pan, Limin Luo, Yu Hen Hu and Hon Keung Tony Ng. Their work appears in journals such as Physics Letters A, Physica A Statistical Mechanics and its Applications, Chaos Solitons & Fractals, Physical review. E and PLoS ONE.

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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