Heyuan Wang
Impact in
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- Stock Market Forecasting Methods
- Artificial Intelligence top 10%
- Topic Modeling
- Advanced Graph Neural Networks
Papers in
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- Stock Market Forecasting Methods 7
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- Topic Modeling 3
- Co-authors
- Tengjiao Wang (8 shared papers)Zheng Liu (1 shared paper)Xing Xie (1 shared paper)Fangzhao Wu (1 shared paper)Jiayi Zheng (5 shared papers)Yi Li (1 shared paper)Tie Qiu (1 shared paper)Arun Kumar Sangaiah (1 shared paper)
In The Last Decade
Heyuan Wang
19 papers receiving 364 citations
Peers
Comparison fields: 5 of 64
- Management Science and Operations Research 134
- Artificial Intelligence 155
- Finance 48
- Information Systems 100
- Signal Processing 41
Countries citing papers authored by Heyuan Wang
This map shows the geographic impact of Heyuan Wang'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 Heyuan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Heyuan Wang more than expected).
Fields of papers citing papers by Heyuan Wang
This network shows the impact of papers produced by Heyuan Wang. 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 Heyuan Wang. The network helps show where Heyuan Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Heyuan Wang, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 90 | |
| 2 | 2018 | 68 | |
| 3 | 2021 | 49 | |
| 4 | 2020 | 36 | |
| 5 | 2022 | 32 | |
| 6 | 2019 | 14 | |
| 7 | 2022 | 14 | |
| 8 | 2023 | 12 | |
| 9 | 2023 | 12 | |
| 10 | 2024 | 11 | |
| 11 | 2022 | 10 | |
| 12 | 2015 | 7 | |
| 13 | 2025 | 4 | |
| 14 | 2021 | 3 | |
| 15 | 2024 | 3 | |
| 16 | 2024 | 3 | |
| 17 | 2024 | 2 | |
| 18 | 2025 | 2 | |
| 19 | 2025 | 1 | |
| 20 | 2025 | 0 |
About Heyuan Wang
Heyuan Wang is a scholar working on Management Science and Operations Research, Artificial Intelligence, Ocean Engineering, Economics and Econometrics and Mechanical Engineering, having authored 21 papers that have together received 373 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (7 papers), Drilling and Well Engineering (4 papers), Complex Systems and Time Series Analysis (4 papers), Financial Markets and Investment Strategies (3 papers), Multimodal Machine Learning Applications (3 papers), Topic Modeling (3 papers), Time Series Analysis and Forecasting (3 papers) and Hydraulic Fracturing and Reservoir Analysis (3 papers). The work is most often cited by research in Management Science and Operations Research (134 citations), Artificial Intelligence (155 citations), Finance (48 citations), Information Systems (100 citations) and Signal Processing (41 citations). Heyuan Wang has collaborated with scholars based in China, Norway and Türkiye. Frequent co-authors include Tengjiao Wang, Zheng Liu, Xing Xie, Fangzhao Wu, Jiayi Zheng, Yi Li, Tie Qiu, Arun Kumar Sangaiah, Keqiu Li and Huansheng Ning. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Journal of Evidence-Based Medicine, Lithosphere, IEEE Transactions on Industrial Informatics and Physics of Fluids.
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.