Jiexia Ye
Impact in
- Transportation top 2%
- Transportation Planning and Optimization
- Human Mobility and Location-Based Analysis
- Building and Construction top 5%
- Traffic Prediction and Management Techniques
Papers in
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- Traffic Prediction and Management Techniques 8
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- Human Mobility and Location-Based Analysis 6
- Transportation Planning and Optimization 5
- Co-authors
- Chengzhong Xu (11 shared papers)Juanjuan Zhao (9 shared papers)Kejiang Ye (6 shared papers)Xitong Gao (2 shared papers)Yuhang Zhang (2 shared papers)Jun Zhang (1 shared paper)Fan Zhang (1 shared paper)Minxian Xu (1 shared paper)
- Journals
- IEEE Transactions on Intelligent Transportation Systems (4 papers)IEEE Transactions on Big Data (1 paper)Neural Computing and Applications (1 paper)Concurrency and Computation Practice and Experience (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
In The Last Decade
Jiexia Ye
11 papers receiving 292 citations
Peers
Comparison fields: 5 of 35
- Transportation 204
- Building and Construction 242
- Signal Processing 42
- Control and Systems Engineering 69
- Automotive Engineering 21
Countries citing papers authored by Jiexia Ye
This map shows the geographic impact of Jiexia Ye'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 Jiexia Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiexia Ye more than expected).
Fields of papers citing papers by Jiexia Ye
This network shows the impact of papers produced by Jiexia Ye. 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 Jiexia Ye. The network helps show where Jiexia Ye may publish in the future.
Co-authors
The 13 scholars most cited alongside Jiexia Ye, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 199 | |
| 2 | 2020 | 35 | |
| 3 | 2022 | 15 | |
| 4 | 2022 | 14 | |
| 5 | 2022 | 10 | |
| 6 | 2021 | 10 | |
| 7 | 2024 | 5 | |
| 8 | 2019 | 4 | |
| 9 | 2020 | 3 | |
| 10 | Multi-View Graph Convolutional Networks for Relationship-Driven Stock Prediction. | 2020 | 2 |
| 11 | 2021 | 2 | |
| 12 | 2026 | 0 |
About Jiexia Ye
Jiexia Ye is a scholar working on Building and Construction, Transportation, Artificial Intelligence, Management Science and Operations Research and Management Information Systems, having authored 12 papers that have together received 299 indexed citations. Recurring topics across this work include Traffic Prediction and Management Techniques (8 papers), Human Mobility and Location-Based Analysis (6 papers), Transportation Planning and Optimization (5 papers), Advanced Graph Neural Networks (2 papers), Imbalanced Data Classification Techniques (1 paper), Railway Systems and Energy Efficiency (1 paper), FinTech, Crowdfunding, Digital Finance (1 paper) and Machine Learning in Healthcare (1 paper). The work is most often cited by research in Transportation (204 citations), Building and Construction (242 citations), Signal Processing (42 citations), Control and Systems Engineering (69 citations) and Automotive Engineering (21 citations). Jiexia Ye has collaborated with scholars based in Macao and China. Frequent co-authors include Chengzhong Xu, Juanjuan Zhao, Kejiang Ye, Xitong Gao, Yuhang Zhang, Jun Zhang, Fan Zhang, Minxian Xu, Ming Chen and Yang Wang. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Big Data, Neural Computing and Applications, Concurrency and Computation Practice and Experience and Proceedings of the AAAI Conference on Artificial Intelligence.
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.