Feng Chen
Impact in
- Transportation top 5%
- Human Mobility and Location-Based Analysis
-
- Complex Network Analysis Techniques
Papers in
-
- Anomaly Detection Techniques and Applications 23
- Advanced Graph Neural Networks 9
- Epidemiology 27
- Data-Driven Disease Surveillance 27
- Co-authors
- Chang‐Tien Lu (34 shared papers)Paul E. Smith (1 shared paper)Naren Ramakrishnan (18 shared papers)Liang Zhao (16 shared papers)Jieping Ye (4 shared papers)Qian Sun (2 shared papers)Arnold P. Boedihardjo (9 shared papers)Jing Dai (3 shared papers)
- Journals
- GeoInformatica (8 papers)ACM Transactions on Knowledge Discovery from Data (4 papers)IEEE Transactions on Knowledge and Data Engineering (4 papers)Electronics (2 papers)IEEE Access (2 papers)
- Partner nations
- United StatesChinaNorway
In The Last Decade
Feng Chen
86 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 140
- Transportation 156
- Statistical and Nonlinear Physics 208
- Artificial Intelligence 534
- Signal Processing 152
- Computational Mathematics 7
Countries citing papers authored by Feng Chen
This map shows the geographic impact of Feng Chen'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 Feng Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feng Chen more than expected).
Fields of papers citing papers by Feng Chen
This network shows the impact of papers produced by Feng Chen. 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 Feng Chen. The network helps show where Feng Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Feng Chen, 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 93 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 194 | |
| 2 | 2015 | 94 | |
| 3 | 2008 | 72 | |
| 4 | 2007 | 60 | |
| 5 | 2011 | 52 | |
| 6 | 2015 | 45 | |
| 7 | 2014 | 42 | |
| 8 | 2016 | 37 | |
| 9 | 2017 | 35 | |
| 10 | 2013 | 28 | |
| 11 | 2016 | 28 | |
| 12 | 2010 | 25 | |
| 13 | 2017 | 25 | |
| 14 | 2016 | 21 | |
| 15 | 2023 | 19 | |
| 16 | 2016 | 18 | |
| 17 | 2021 | 17 | |
| 18 | 2013 | 16 | |
| 19 | 2022 | 16 | |
| 20 | 2023 | 16 |
About Feng Chen
Feng Chen is a scholar working on Artificial Intelligence, Epidemiology, Statistical and Nonlinear Physics, Transportation and Signal Processing, having authored 93 papers that have together received 1.3k indexed citations. Recurring topics across this work include Data-Driven Disease Surveillance (27 papers), Complex Network Analysis Techniques (23 papers), Anomaly Detection Techniques and Applications (23 papers), Human Mobility and Location-Based Analysis (17 papers), Geographic Information Systems Studies (9 papers), Advanced Graph Neural Networks (9 papers), Data Management and Algorithms (7 papers) and Advanced Statistical Methods and Models (7 papers). The work is most often cited by research in Transportation (156 citations), Statistical and Nonlinear Physics (208 citations), Artificial Intelligence (534 citations), Signal Processing (152 citations) and Computational Mathematics (7 citations). Feng Chen has collaborated with scholars based in United States, China and Norway. Frequent co-authors include Chang‐Tien Lu, Paul E. Smith, Naren Ramakrishnan, Liang Zhao, Jieping Ye, Qian Sun, Arnold P. Boedihardjo, Jing Dai, Dechang Chen and Yufeng Kou. Their work appears in journals such as GeoInformatica, ACM Transactions on Knowledge Discovery from Data, IEEE Transactions on Knowledge and Data Engineering, Electronics and IEEE Access.
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.