Jin Fan
- Artificial Intelligence top 10%
- Building and Construction top 5%
- Atmospheric Science top 10%
- Health, Toxicology and Mutagenesis top 5%
- Environmental Engineering top 10%
- Co-authors
- Jia WuHao TianYujie HuHuifeng WuZhu FuShigong WangQing WuHua Zhang
- Topics
- Air Quality and Health Impacts (12 papers)Time Series Analysis and Forecasting (10 papers)Energy Efficient Wireless Sensor Networks (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaThe Science of The Total EnvironmentAtmospheric Environment
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Jin Fan
64 papers receiving 784 citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Artificial Intelligence 175
- Building and Construction 164
- Atmospheric Science 163
- Health, Toxicology and Mutagenesis 151
- Environmental Engineering 119
Countries citing papers authored by Jin Fan
This map shows the geographic impact of Jin 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 Jin Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin Fan more than expected).
Fields of papers citing papers by Jin Fan
This network shows the impact of papers produced by Jin 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 Jin Fan. The network helps show where Jin Fan may publish in the future.
Co-authorship network of co-authors of Jin Fan
This figure shows the co-authorship network connecting the top 25 collaborators of Jin Fan. A scholar is included among the top collaborators of Jin Fan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jin Fan. Jin Fan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 38 | |
| 8 | 12 | |
| 9 | 7 | |
| 10 | A Decomposition Dynamic graph convolutional recurrent network for traffic forecastingbreakdown → | 115 |
| 11 | 17 | |
| 12 | 1 | |
| 13 | 4 | |
| 14 | 21 | |
| 15 | 26 | |
| 16 | 30 | |
| 17 | 8 | |
| 18 | 7 | |
| 19 | 3 | |
| 20 | [Characteristics and sources of soluble ions in aerosols from Glacier No. 1 at the headwater of Urumqi River, Tianshan Mountains, China]. | 2 |
About Jin Fan
Jin Fan is a scholar working on Computational Mathematics, Signal Processing and Health, Toxicology and Mutagenesis, having authored 72 papers that have together received 807 indexed citations. Recurring topics across this work include Air Quality and Health Impacts (12 papers), Time Series Analysis and Forecasting (10 papers) and Energy Efficient Wireless Sensor Networks (8 papers). The work is most often cited by research in Transportation (114 citations), Building and Construction (164 citations) and Health, Toxicology and Mutagenesis (151 citations). Jin Fan has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Jia Wu, Hao Tian, Yujie Hu, Huifeng Wu, Zhu Fu, Shigong Wang, Qing Wu, Hua Zhang, Jiang Jian and Tom H. Luan. Their work appears in journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Atmospheric Environment.
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.