Le Yu
Impact in
- Transportation top 5%
- Transportation Planning and Optimization
- Human Mobility and Location-Based Analysis
- Building and Construction top 5%
- Traffic Prediction and Management Techniques
Papers in
-
- Advanced Graph Neural Networks 8
- Solar Radiation and Photovoltaics 3
- Co-authors
- Leilei Sun (12 shared papers)Bowen Du (9 shared papers)Xiao Hu (3 shared papers)Weifeng Lv (8 shared papers)Liangzhe Han (1 shared paper)David W. Burt (4 shared papers)Xuxiang Ta (1 shared paper)Alan S. McNeilly (2 shared papers)
- Journals
- IEEE Transactions on Knowledge and Data Engineering (4 papers)Current Biology (2 papers)Theoretical and Applied Genetics (2 papers)Knowledge-Based Systems (2 papers)Plant Biotechnology Journal (2 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Le Yu
40 papers receiving 810 citations
Peers
Comparison fields: 5 of 115
- Transportation 115
- Building and Construction 204
- Endocrine and Autonomic Systems 100
- Safety, Risk, Reliability and Quality 56
- Artificial Intelligence 151
Countries citing papers authored by Le Yu
This map shows the geographic impact of Le Yu'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 Le Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Le Yu more than expected).
Fields of papers citing papers by Le Yu
This network shows the impact of papers produced by Le Yu. 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 Le Yu. The network helps show where Le Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside Le Yu, 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 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 144 | |
| 2 | 2022 | 118 | |
| 3 | 2015 | 88 | |
| 4 | 2011 | 88 | |
| 5 | 2010 | 68 | |
| 6 | 2022 | 61 | |
| 7 | 2017 | 34 | |
| 8 | 2022 | 28 | |
| 9 | 2020 | 24 | |
| 10 | 2018 | 15 | |
| 11 | 2022 | 15 | |
| 12 | 2021 | 12 | |
| 13 | 2012 | 12 | |
| 14 | 2015 | 10 | |
| 15 | 2021 | 9 | |
| 16 | 2022 | 9 | |
| 17 | 2023 | 8 | |
| 18 | 2020 | 8 | |
| 19 | 2022 | 7 | |
| 20 | 2023 | 6 |
About Le Yu
Le Yu is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Plant Science, Molecular Biology and Information Systems, having authored 46 papers that have together received 825 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (8 papers), Research in Cotton Cultivation (7 papers), Recommender Systems and Techniques (4 papers), Plant Molecular Biology Research (3 papers), Plant Virus Research Studies (3 papers), Solar Radiation and Photovoltaics (3 papers), Traffic Prediction and Management Techniques (3 papers) and Traffic and Road Safety (2 papers). The work is most often cited by research in Transportation (115 citations), Building and Construction (204 citations), Endocrine and Autonomic Systems (100 citations), Safety, Risk, Reliability and Quality (56 citations) and Artificial Intelligence (151 citations). Le Yu has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Leilei Sun, Bowen Du, Xiao Hu, Weifeng Lv, Liangzhe Han, David W. Burt, Xuxiang Ta, Alan S. McNeilly, J.R. Davis and Andrew Loudon. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Current Biology, Theoretical and Applied Genetics, Knowledge-Based Systems and Plant Biotechnology Journal.
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.