Bin Pi
Impact in
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- Opinion Dynamics and Social Influence
- Complex Network Analysis Techniques
- Safety Research top 10%
- Experimental Behavioral Economics Studies
Papers in
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- Opinion Dynamics and Social Influence 9
- Complex Network Analysis Techniques 3
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- Evolutionary Game Theory and Cooperation 13
- Co-authors
- Minyu Feng (14 shared papers)Jürgen Kurths (4 shared papers)Liang-Jian Deng (5 shared papers)M Nekrep Perc (4 shared papers)Qin Li (3 shared papers)Yuji Zhang (1 shared paper)Yuhan Li (1 shared paper)Helena Blažun Vošner (1 shared paper)
In The Last Decade
Bin Pi
16 papers receiving 244 citations
Bin Pi's Hit Papers
Peers
Comparison fields: 5 of 34
- Statistical and Nonlinear Physics 74
- Safety Research 42
- Sociology and Political Science 191
- Management Science and Operations Research 41
- Experimental and Cognitive Psychology 27
Countries citing papers authored by Bin Pi
This map shows the geographic impact of Bin Pi'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 Bin Pi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Pi more than expected).
Fields of papers citing papers by Bin Pi
This network shows the impact of papers produced by Bin Pi. 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 Bin Pi. The network helps show where Bin Pi may publish in the future.
Co-authors
The 10 scholars most cited alongside Bin Pi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 46 | |
| 2 | 2022 | 29 | |
| 3 | Dynamic Evolution of Complex Networks: A Reinforcement Learning Approach Applying Evolutionary Games to Community Structure Hit paper breakdown → | 2025 | 27 |
| 4 | 2023 | 26 | |
| 5 | 2022 | 23 | |
| 6 | 2024 | 18 | |
| 7 | 2025 | 13 | |
| 8 | 2023 | 13 | |
| 9 | 2023 | 12 | |
| 10 | 2025 | 11 | |
| 11 | 2023 | 8 | |
| 12 | 2024 | 7 | |
| 13 | 2025 | 5 | |
| 14 | 2022 | 5 | |
| 15 | 2025 | 5 | |
| 16 | 2022 | 1 | |
| 17 | 2026 | 0 |
About Bin Pi
Bin Pi is a scholar working on Statistical and Nonlinear Physics, Sociology and Political Science, Management Science and Operations Research, Safety Research and Genetics, having authored 17 papers that have together received 249 indexed citations. Recurring topics across this work include Evolutionary Game Theory and Cooperation (13 papers), Opinion Dynamics and Social Influence (9 papers), Game Theory and Applications (5 papers), Evolution and Genetic Dynamics (4 papers), Experimental Behavioral Economics Studies (4 papers), Complex Network Analysis Techniques (3 papers), Evolutionary Psychology and Human Behavior (2 papers) and Artificial Intelligence in Games (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (74 citations), Safety Research (42 citations), Sociology and Political Science (191 citations), Management Science and Operations Research (41 citations) and Experimental and Cognitive Psychology (27 citations). Bin Pi has collaborated with scholars based in China, Slovenia and Germany. Frequent co-authors include Minyu Feng, Jürgen Kurths, Liang-Jian Deng, M Nekrep Perc, Qin Li, Yuji Zhang, Yuhan Li, Helena Blažun Vošner, Xiaojie Chen and Attila Szolnoki. Their work appears in journals such as Chaos An Interdisciplinary Journal of Nonlinear Science, Applied Mathematics and Computation, Chaos Solitons & Fractals, Physica A Statistical Mechanics and its Applications and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.