Enyan Dai
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Adversarial Robustness in Machine Learning
- Explainable Artificial Intelligence (XAI)
- Privacy-Preserving Technologies in Data
- Topic Modeling
- Safety Research top 5%
- Ethics and Social Impacts of AI
Papers in
-
- Advanced Graph Neural Networks 13
- Explainable Artificial Intelligence (XAI) 6
- Privacy-Preserving Technologies in Data 4
- Topic Modeling 4
- Adversarial Robustness in Machine Learning 3
- Co-authors
- Suhang Wang (18 shared papers)Tianxiang Zhao (4 shared papers)Yiwei Sun (2 shared papers)Charų C. Aggarwal (1 shared paper)Yuqing Hu (2 shared papers)Hui Liu (2 shared papers)Jianli Chen (1 shared paper)Wei Jin (1 shared paper)
- Journals
- IEEE Transactions on Software Engineering (1 paper)ACM Transactions on Knowledge Discovery from Data (1 paper)Applied Energy (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)Neurocomputing (1 paper)
- Partner nations
- United StatesHong KongSweden
In The Last Decade
Enyan Dai
20 papers receiving 605 citations
Peers
Comparison fields: 5 of 87
- Artificial Intelligence 416
- Safety Research 95
- Health Informatics 11
- Building and Construction 68
- Computer Vision and Pattern Recognition 90
Countries citing papers authored by Enyan Dai
This map shows the geographic impact of Enyan Dai'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 Enyan Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Enyan Dai more than expected).
Fields of papers citing papers by Enyan Dai
This network shows the impact of papers produced by Enyan Dai. 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 Enyan Dai. The network helps show where Enyan Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Enyan Dai, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 141 | |
| 2 | 2021 | 91 | |
| 3 | 2020 | 69 | |
| 4 | 2021 | 54 | |
| 5 | 2022 | 53 | |
| 6 | 2021 | 41 | |
| 7 | 2020 | 36 | |
| 8 | 2023 | 29 | |
| 9 | 2022 | 23 | |
| 10 | 2024 | 21 | |
| 11 | 2022 | 19 | |
| 12 | 2022 | 8 | |
| 13 | 2023 | 7 | |
| 14 | 2017 | 7 | |
| 15 | 2023 | 5 | |
| 16 | 2022 | 4 | |
| 17 | 2024 | 2 | |
| 18 | 2024 | 2 | |
| 19 | 2020 | 1 | |
| 20 | 2024 | 1 |
About Enyan Dai
Enyan Dai is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Safety Research, Statistical and Nonlinear Physics and Information Systems, having authored 23 papers that have together received 614 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (13 papers), Explainable Artificial Intelligence (XAI) (6 papers), Ethics and Social Impacts of AI (5 papers), Privacy-Preserving Technologies in Data (4 papers), Topic Modeling (4 papers), Adversarial Robustness in Machine Learning (3 papers), Complex Network Analysis Techniques (3 papers) and Building Energy and Comfort Optimization (2 papers). The work is most often cited by research in Artificial Intelligence (416 citations), Safety Research (95 citations), Health Informatics (11 citations), Building and Construction (68 citations) and Computer Vision and Pattern Recognition (90 citations). Enyan Dai has collaborated with scholars based in United States, Hong Kong and Sweden. Frequent co-authors include Suhang Wang, Tianxiang Zhao, Yiwei Sun, Charų C. Aggarwal, Yuqing Hu, Hui Liu, Jianli Chen, Wei Jin, X. D. Zhang and Kai Shu. Their work appears in journals such as IEEE Transactions on Software Engineering, ACM Transactions on Knowledge Discovery from Data, Applied Energy, IEEE Transactions on Knowledge and Data Engineering and Neurocomputing.
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.