Shirui Pan
- Artificial Intelligence top 0.05%
- Advanced Graph Neural Networks 126
- Topic Modeling 50
- Domain Adaptation and Few-Shot Learning 30
- Anomaly Detection Techniques and Applications 22
- Text and Document Classification Technologies 19
- Transportation top 0.2%
- Building and Construction top 0.1%
- Statistical and Nonlinear Physics top 0.2%
- Complex Network Analysis Techniques 50
- Signal Processing top 0.2%
- Time Series Analysis and Forecasting 17
-
- Recommender Systems and Techniques 43
- Co-authors
- Chengqi ZhangGuodong LongJing JiangZonghan WuPhilip S. YuXingquan ZhuShaoxiong JiErik Cambria
- Journals
- IEEE Transactions on Neural Networks and Learning Systems (15 papers)IEEE Transactions on Knowledge and Data Engineering (13 papers)Pattern Recognition (12 papers)
- Partner nations
- AustraliaChinaUnited States
In The Last Decade
Shirui Pan
277 papers receiving 12.5k citations
Hit Papers
Peers
Comparison fields: 5 of 185
- Artificial Intelligence 7.5k
- Transportation 1.4k
- Building and Construction 2.0k
- Statistical and Nonlinear Physics 1.7k
- Signal Processing 1.4k
Countries citing papers authored by Shirui Pan
This map shows the geographic impact of Shirui Pan'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 Shirui Pan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shirui Pan more than expected).
Fields of papers citing papers by Shirui Pan
This network shows the impact of papers produced by Shirui Pan. 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 Shirui Pan. The network helps show where Shirui Pan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shirui Pan, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 9 | |
| 5 | 2024 | 8 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 33 | |
| 9 | 2024 | 4 | |
| 10 | 2024 | 16 | |
| 11 | 2024 | 9 | |
| 12 | 2024 | 29 | |
| 13 | 2024 | 8 | |
| 14 | 2023 | 3 | |
| 15 | 2023 | 12 | |
| 16 | 2023 | 9 | |
| 17 | 2023 | 18 | |
| 18 | 2023 | 55 | |
| 19 | 2022 | 2 | |
| 20 | Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement | 2020 | 16 |
About Shirui Pan
Shirui Pan is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Information Systems and Signal Processing, having authored 303 papers that have together received 12.8k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (126 papers), Topic Modeling (50 papers), Complex Network Analysis Techniques (50 papers), Recommender Systems and Techniques (43 papers), Domain Adaptation and Few-Shot Learning (30 papers), Anomaly Detection Techniques and Applications (22 papers), Text and Document Classification Technologies (19 papers) and Time Series Analysis and Forecasting (17 papers). The work is most often cited by research in Artificial Intelligence (7.5k citations), Transportation (1.4k citations), Building and Construction (2.0k citations), Statistical and Nonlinear Physics (1.7k citations) and Signal Processing (1.4k citations). Shirui Pan has collaborated with scholars based in Australia, China and United States. Frequent co-authors include Chengqi Zhang, Guodong Long, Jing Jiang, Zonghan Wu, Philip S. Yu, Xingquan Zhu, Shaoxiong Ji, Erik Cambria, Jia Wu and Pekka Marttinen. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering, Pattern Recognition, IEEE Transactions on Cybernetics and Neural Networks.
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.