Runlong Yu
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Topic Modeling
- Privacy-Preserving Technologies in Data
- Intelligent Tutoring Systems and Adaptive Learning
Papers in
-
- Advanced Graph Neural Networks 3
- Topic Modeling 3
-
- Recommender Systems and Techniques 11
- Co-authors
- Enhong Chen (13 shared papers)Qi Liu (10 shared papers)Zaixi Zhang (1 shared paper)Mingyue Cheng (4 shared papers)Likang Wu (2 shared papers)Hengshu Zhu (3 shared papers)Hui Xiong (3 shared papers)Chao Wang (1 shared paper)
- Journals
- IEEE Transactions on Knowledge and Data Engineering (3 papers)Expert Systems with Applications (1 paper)Big Data Mining and Analytics (1 paper)Plant Biology (1 paper)Communications of the ACM (1 paper)
- Partner nations
- ChinaUnited StatesNetherlands
In The Last Decade
Runlong Yu
24 papers receiving 272 citations
Peers
Comparison fields: 5 of 61
- Information Systems 140
- Artificial Intelligence 156
- Management Science and Operations Research 44
- Computational Mathematics 2
- Computer Science Applications 19
Countries citing papers authored by Runlong Yu
This map shows the geographic impact of Runlong Yu'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 Runlong Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Runlong Yu more than expected).
Fields of papers citing papers by Runlong Yu
This network shows the impact of papers produced by Runlong Yu. 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 Runlong Yu. The network helps show where Runlong Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside Runlong Yu, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 43 | |
| 2 | 2018 | 38 | |
| 3 | 2019 | 26 | |
| 4 | 2020 | 24 | |
| 5 | 2022 | 15 | |
| 6 | 2021 | 14 | |
| 7 | 2022 | 14 | |
| 8 | 2021 | 14 | |
| 9 | 2021 | 13 | |
| 10 | 2022 | 12 | |
| 11 | 2019 | 10 | |
| 12 | 2022 | 8 | |
| 13 | 2019 | 8 | |
| 14 | 2023 | 7 | |
| 15 | 2025 | 6 | |
| 16 | 2024 | 6 | |
| 17 | 2025 | 4 | |
| 18 | 2024 | 3 | |
| 19 | 2022 | 3 | |
| 20 | 2024 | 2 |
About Runlong Yu
Runlong Yu is a scholar working on Artificial Intelligence, Information Systems, Management Science and Operations Research, Statistical and Nonlinear Physics and Signal Processing, having authored 32 papers that have together received 276 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (11 papers), Hydrological Forecasting Using AI (3 papers), Advanced Graph Neural Networks (3 papers), Topic Modeling (3 papers), Complex Network Analysis Techniques (3 papers), Machine Learning in Materials Science (3 papers), Intellectual Property and Patents (2 papers) and Mental Health via Writing (2 papers). The work is most often cited by research in Information Systems (140 citations), Artificial Intelligence (156 citations), Management Science and Operations Research (44 citations), Computational Mathematics (2 citations) and Computer Science Applications (19 citations). Runlong Yu has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Enhong Chen, Qi Liu, Zaixi Zhang, Mingyue Cheng, Likang Wu, Hengshu Zhu, Hui Xiong, Chao Wang, Yunzhou Zhang and Qi Liu. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Expert Systems with Applications, Big Data Mining and Analytics, Plant Biology and Communications of the ACM.
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.