Changjun Fan
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
Papers in
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- Advanced Graph Neural Networks 12
- Topic Modeling 4
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- Complex Network Analysis Techniques 12
- Opinion Dynamics and Social Influence 5
- Co-authors
- Yizhou Sun (4 shared papers)Li Zeng (6 shared papers)Yang‐Yu Liu (2 shared papers)Muhao Chen (3 shared papers)Guangquan Cheng (3 shared papers)Yan Zhang (1 shared paper)Cunchao Zhu (1 shared paper)Zhong Liu (9 shared papers)
- Journals
- International Journal of Machine Learning and Cybernetics (2 papers)Physica A Statistical Mechanics and its Applications (2 papers)Chinese Science Bulletin (Chinese Version) (2 papers)The Innovation (2 papers)Knowledge-Based Systems (1 paper)
- Partner nations
- ChinaUnited StatesSweden
In The Last Decade
Changjun Fan
35 papers receiving 745 citations
Changjun Fan's Hit Papers
Peers
Comparison fields: 5 of 105
- Statistical and Nonlinear Physics 238
- Artificial Intelligence 332
- Management Science and Operations Research 62
- Environmental Chemistry 49
- Computer Networks and Communications 108
Countries citing papers authored by Changjun Fan
This map shows the geographic impact of Changjun Fan'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 Changjun Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Changjun Fan more than expected).
Fields of papers citing papers by Changjun Fan
This network shows the impact of papers produced by Changjun Fan. 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 Changjun Fan. The network helps show where Changjun Fan may publish in the future.
Co-authors
The 25 scholars most cited alongside Changjun Fan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Finding key players in complex networks through deep reinforcement learning Hit paper breakdown → | 2020 | 243 |
| 2 | 2021 | 153 | |
| 3 | 2019 | 54 | |
| 4 | 2019 | 41 | |
| 5 | 2018 | 29 | |
| 6 | 2015 | 28 | |
| 7 | 2016 | 25 | |
| 8 | 2014 | 24 | |
| 9 | 2020 | 20 | |
| 10 | 2020 | 17 | |
| 11 | 2023 | 15 | |
| 12 | 2021 | 14 | |
| 13 | 2021 | 14 | |
| 14 | 2020 | 13 | |
| 15 | 2016 | 12 | |
| 16 | 2022 | 8 | |
| 17 | 2020 | 7 | |
| 18 | 2022 | 6 | |
| 19 | 2024 | 5 | |
| 20 | 2013 | 4 |
About Changjun Fan
Changjun Fan is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Management Science and Operations Research, Electrical and Electronic Engineering and Computational Theory and Mathematics, having authored 38 papers that have together received 755 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (12 papers), Advanced Graph Neural Networks (12 papers), Organic Light-Emitting Diodes Research (6 papers), Opinion Dynamics and Social Influence (5 papers), Organic Electronics and Photovoltaics (5 papers), Topic Modeling (4 papers), Data Quality and Management (3 papers) and Conducting polymers and applications (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (238 citations), Artificial Intelligence (332 citations), Management Science and Operations Research (62 citations), Environmental Chemistry (49 citations) and Computer Networks and Communications (108 citations). Changjun Fan has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Yizhou Sun, Li Zeng, Yang‐Yu Liu, Muhao Chen, Guangquan Cheng, Yan Zhang, Cunchao Zhu, Zhong Liu, Yong Cai and Guangliang Liu. Their work appears in journals such as International Journal of Machine Learning and Cybernetics, Physica A Statistical Mechanics and its Applications, Chinese Science Bulletin (Chinese Version), The Innovation and Knowledge-Based Systems.
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.