Lingfei Wu
- Artificial Intelligence top 1%
- Topic Modeling 40
- Advanced Graph Neural Networks 27
- Natural Language Processing Techniques 22
- Anomaly Detection Techniques and Applications 7
- Information Systems top 1%
- Recommender Systems and Techniques 8
- Web Data Mining and Analysis 8
- Software Engineering Research 7
- Signal Processing top 5%
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- Multimodal Machine Learning Applications 7
- Software top 10%
- Co-authors
- Heng JiYing LinFei HuangJian PeiFangli XuTengfei MaLiang ZhaoYu Chen
- Journals
- IEEE Transactions on Neural Networks and Learning Systems (5 papers)IEEE Transactions on Knowledge and Data Engineering (3 papers)SIAM Journal on Scientific Computing (2 papers)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Lingfei Wu
98 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 134
- Artificial Intelligence 1.3k
- Information Systems 464
- Signal Processing 206
- Computer Vision and Pattern Recognition 290
- Software 47
Countries citing papers authored by Lingfei Wu
This map shows the geographic impact of Lingfei Wu'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 Lingfei Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lingfei Wu more than expected).
Fields of papers citing papers by Lingfei Wu
This network shows the impact of papers produced by Lingfei Wu. 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 Lingfei Wu. The network helps show where Lingfei Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Lingfei Wu, 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 | 2024 | 1 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 53 | |
| 5 | 2023 | 4 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 10 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 1 | |
| 10 | 2023 | 23 | |
| 11 | 2023 | 4 | |
| 12 | 2021 | 13 | |
| 13 | 2021 | 9 | |
| 14 | 2020 | 31 | |
| 15 | A Joint Neural Model for Information Extraction with Global Featuresbreakdown → | 2020 | 225 |
| 16 | Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation | 2020 | 24 |
| 17 | 2019 | 8 | |
| 18 | 2018 | 50 | |
| 19 | 2018 | 43 | |
| 20 | 2016 | 18 |
About Lingfei Wu
Lingfei Wu is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Signal Processing and Information Systems and Management, having authored 104 papers that have together received 1.9k indexed citations. Recurring topics across this work include Topic Modeling (40 papers), Advanced Graph Neural Networks (27 papers), Natural Language Processing Techniques (22 papers), Recommender Systems and Techniques (8 papers), Web Data Mining and Analysis (8 papers), Software Engineering Research (7 papers), Multimodal Machine Learning Applications (7 papers) and Anomaly Detection Techniques and Applications (7 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Information Systems (464 citations), Signal Processing (206 citations), Computer Vision and Pattern Recognition (290 citations) and Software (47 citations). Lingfei Wu has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Heng Ji, Ying Lin, Fei Huang, Jian Pei, Fangli Xu, Tengfei Ma, Liang Zhao, Yu Chen, Shouling Ji and Xiaojie Guo. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering, SIAM Journal on Scientific Computing, IEEE Transactions on Big Data and IEEE Transactions on Pattern Analysis and Machine 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.