Yuanfei Dai
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
- Anomaly Detection Techniques and Applications
Papers in
-
- Advanced Graph Neural Networks 6
- Topic Modeling 4
- Domain Adaptation and Few-Shot Learning 3
-
- Generative Adversarial Networks and Image Synthesis 3
- Co-authors
- Wenzhong Guo (8 shared papers)Shiping Wang (7 shared papers)Naixue Xiong (2 shared papers)Shunxin Xiao (1 shared paper)Carsten Eickhoff (3 shared papers)Xing Chen (4 shared papers)Renjie Lin (3 shared papers)Xiaodong Miao (1 shared paper)
- Journals
- Knowledge-Based Systems (3 papers)Electronics (2 papers)IEEE Access (2 papers)Briefings in Bioinformatics (1 paper)IEEE/ACM Transactions on Computational Biology and Bioinformatics (1 paper)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Yuanfei Dai
18 papers receiving 424 citations
Peers
Comparison fields: 5 of 75
- Artificial Intelligence 283
- Computer Vision and Pattern Recognition 82
- Statistical and Nonlinear Physics 43
- Computational Theory and Mathematics 48
- Information Systems 58
Countries citing papers authored by Yuanfei Dai
This map shows the geographic impact of Yuanfei 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 Yuanfei Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuanfei Dai more than expected).
Fields of papers citing papers by Yuanfei Dai
This network shows the impact of papers produced by Yuanfei 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 Yuanfei Dai. The network helps show where Yuanfei Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Yuanfei 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
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 153 | |
| 2 | 2021 | 101 | |
| 3 | 2020 | 57 | |
| 4 | 2019 | 39 | |
| 5 | 2020 | 26 | |
| 6 | 2023 | 18 | |
| 7 | 2018 | 11 | |
| 8 | 2019 | 6 | |
| 9 | 2019 | 6 | |
| 10 | 2023 | 4 | |
| 11 | 2017 | 3 | |
| 12 | 2023 | 2 | |
| 13 | Wasserstein Adversarial Autoencoders for Knowledge Graph Embedding based Drug-Drug Interaction Prediction. | 2020 | 2 |
| 14 | 2025 | 1 | |
| 15 | 2024 | 1 | |
| 16 | 2024 | 1 | |
| 17 | 2025 | 1 | |
| 18 | 2018 | 1 | |
| 19 | 2025 | 0 | |
| 20 | 2026 | 0 |
About Yuanfei Dai
Yuanfei Dai is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Computer Networks and Communications and Surgery, having authored 20 papers that have together received 433 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (6 papers), Topic Modeling (4 papers), Generative Adversarial Networks and Image Synthesis (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Computational Drug Discovery Methods (2 papers), Network Security and Intrusion Detection (2 papers), Biomedical Text Mining and Ontologies (2 papers) and Software System Performance and Reliability (1 paper). The work is most often cited by research in Artificial Intelligence (283 citations), Computer Vision and Pattern Recognition (82 citations), Statistical and Nonlinear Physics (43 citations), Computational Theory and Mathematics (48 citations) and Information Systems (58 citations). Yuanfei Dai has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Wenzhong Guo, Shiping Wang, Naixue Xiong, Shunxin Xiao, Carsten Eickhoff, Xing Chen, Renjie Lin, Xiaodong Miao, Tianjing Wang and Li Fang. Their work appears in journals such as Knowledge-Based Systems, Electronics, IEEE Access, Briefings in Bioinformatics and IEEE/ACM Transactions on Computational Biology and Bioinformatics.
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.