Dawei Cheng
Impact in
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- Stock Market Forecasting Methods
- Artificial Intelligence top 2%
- Imbalanced Data Classification Techniques
- Advanced Graph Neural Networks
- Topic Modeling
- Anomaly Detection Techniques and Applications
Papers in
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- Advanced Graph Neural Networks 13
- Imbalanced Data Classification Techniques 10
- Topic Modeling 7
- Finance 18
- Banking stability, regulation, efficiency 10
- Financial Markets and Investment Strategies 5
- Co-authors
- Sheng Xiang (13 shared papers)Fangzhou Yang (8 shared papers)Liqing Zhang (17 shared papers)Ying Zhang (11 shared papers)Jin Liu (1 shared paper)Xiaoyang Wang (7 shared papers)Zhibin Niu (13 shared papers)Yi Tu (8 shared papers)
In The Last Decade
Dawei Cheng
64 papers receiving 1.1k citations
Dawei Cheng's Hit Papers
Peers
Comparison fields: 5 of 93
- Management Science and Operations Research 275
- Artificial Intelligence 645
- Accounting 131
- Signal Processing 115
- Finance 93
Countries citing papers authored by Dawei Cheng
This map shows the geographic impact of Dawei Cheng'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 Dawei Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dawei Cheng more than expected).
Fields of papers citing papers by Dawei Cheng
This network shows the impact of papers produced by Dawei Cheng. 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 Dawei Cheng. The network helps show where Dawei Cheng may publish in the future.
Co-authors
The 25 scholars most cited alongside Dawei Cheng, 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 76 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Financial time series forecasting with multi-modality graph neural network Hit paper breakdown → | 2021 | 239 |
| 2 | 2020 | 104 | |
| 3 | 2020 | 75 | |
| 4 | 2020 | 58 | |
| 5 | 2023 | 53 | |
| 6 | 2022 | 47 | |
| 7 | 2019 | 40 | |
| 8 | 2023 | 37 | |
| 9 | 2020 | 35 | |
| 10 | 2022 | 30 | |
| 11 | 2022 | 26 | |
| 12 | 2020 | 23 | |
| 13 | 2020 | 22 | |
| 14 | 2021 | 22 | |
| 15 | 2018 | 19 | |
| 16 | 2019 | 19 | |
| 17 | 2023 | 18 | |
| 18 | 2020 | 17 | |
| 19 | 2020 | 17 | |
| 20 | 2022 | 15 |
About Dawei Cheng
Dawei Cheng is a scholar working on Artificial Intelligence, Finance, Management Science and Operations Research, Accounting and Computer Vision and Pattern Recognition, having authored 76 papers that have together received 1.1k indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (16 papers), Financial Distress and Bankruptcy Prediction (14 papers), Advanced Graph Neural Networks (13 papers), Banking stability, regulation, efficiency (10 papers), Imbalanced Data Classification Techniques (10 papers), Topic Modeling (7 papers), Energy Load and Power Forecasting (6 papers) and Financial Markets and Investment Strategies (5 papers). The work is most often cited by research in Management Science and Operations Research (275 citations), Artificial Intelligence (645 citations), Accounting (131 citations), Signal Processing (115 citations) and Finance (93 citations). Dawei Cheng has collaborated with scholars based in China, Australia and Singapore. Frequent co-authors include Sheng Xiang, Fangzhou Yang, Liqing Zhang, Ying Zhang, Jin Liu, Xiaoyang Wang, Zhibin Niu, Yi Tu, Changjun Jiang and Yifeng Luo. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Neurocomputing, IEEE Transactions on Neural Networks and Learning Systems, Pattern Recognition and The VLDB 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.