Yuan Hu
- Environmental Engineering top 0.5%
- Health, Toxicology and Mutagenesis top 1%
- Automotive Engineering top 2%
- Atmospheric Science top 10%
- Global and Planetary Change top 10%
- Topics
- GNSS positioning and interference (14 papers)Soil Moisture and Remote Sensing (12 papers)Inertial Sensor and Navigation (10 papers)
- Journals
- The Science of The Total EnvironmentEnvironmental PollutionIEEE Transactions on Geoscience and Remote Sensing
- Partner nations
- ChinaGermanyUnited States
In The Last Decade
Yuan Hu
62 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Environmental Engineering 1.1k
- Health, Toxicology and Mutagenesis 706
- Automotive Engineering 346
- Atmospheric Science 265
- Global and Planetary Change 210
Countries citing papers authored by Yuan Hu
This map shows the geographic impact of Yuan Hu'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 Yuan Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuan Hu more than expected).
Fields of papers citing papers by Yuan Hu
This network shows the impact of papers produced by Yuan Hu. 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 Yuan Hu. The network helps show where Yuan Hu may publish in the future.
Co-authorship network of co-authors of Yuan Hu
This figure shows the co-authorship network connecting the top 25 collaborators of Yuan Hu. A scholar is included among the top collaborators of Yuan Hu 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 Yuan Hu. Yuan Hu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 3 | |
| 8 | 2 | |
| 9 | 0 | |
| 10 | 6 | |
| 11 | 1 | |
| 12 | 3 | |
| 13 | 36 | |
| 14 | 15 | |
| 15 | 12 | |
| 16 | 1 | |
| 17 | A novel spatiotemporal convolutional long short-term neural network for air pollution predictionbreakdown → | 317 |
| 18 | 2 | |
| 19 | Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluationbreakdown → | 491 |
| 20 | 241 |
About Yuan Hu
Yuan Hu is a scholar working on Environmental Engineering, Aerospace Engineering and Atmospheric Science, having authored 69 papers that have together received 1.7k indexed citations. Recurring topics across this work include GNSS positioning and interference (14 papers), Soil Moisture and Remote Sensing (12 papers) and Inertial Sensor and Navigation (10 papers). The work is most often cited by research in Environmental Engineering (1.1k citations), Health, Toxicology and Mutagenesis (706 citations) and Automotive Engineering (346 citations). Yuan Hu has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Li Xiang, Ling Peng, Tianhe Chi, Xiaojing Yao, Chengzeng You, Shaolong Cui, Congcong Wen, Jing Shao, Shufu Liu and Wei Liu. Their work appears in journals such as The Science of The Total Environment, Environmental Pollution and IEEE Transactions on Geoscience and Remote Sensing.
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.