Yankai Chen
Impact in
- Electrochemistry top 10%
- Electrochemical Analysis and Applications
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
Papers in
-
- Advanced Graph Neural Networks 10
- Domain Adaptation and Few-Shot Learning 3
-
- Recommender Systems and Techniques 10
- Co-authors
- Irwin King (19 shared papers)Yixiang Fang (9 shared papers)Suyan Teng (2 shared papers)Ek Peng Chew (2 shared papers)Loo Hay Lee (2 shared papers)Xiaoning Yang (2 shared papers)Xiaoping Wu (3 shared papers)Fengxiang Tang (2 shared papers)
- Journals
- Journal of Magnetism and Magnetic Materials (2 papers)Physics Letters A (1 paper)ACM Transactions on Information Systems (1 paper)Medical Image Analysis (1 paper)Frontiers in Cell and Developmental Biology (1 paper)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Yankai Chen
50 papers receiving 685 citations
Peers
Comparison fields: 5 of 104
- Electrochemistry 56
- Artificial Intelligence 249
- Information Systems 152
- Management Science and Operations Research 76
- Statistical and Nonlinear Physics 70
Countries citing papers authored by Yankai Chen
This map shows the geographic impact of Yankai Chen'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 Yankai Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yankai Chen more than expected).
Fields of papers citing papers by Yankai Chen
This network shows the impact of papers produced by Yankai Chen. 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 Yankai Chen. The network helps show where Yankai Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Yankai Chen, 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 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 95 | |
| 2 | 2013 | 84 | |
| 3 | 2017 | 71 | |
| 4 | 2022 | 54 | |
| 5 | 2022 | 51 | |
| 6 | 2024 | 35 | |
| 7 | 2022 | 32 | |
| 8 | 2022 | 25 | |
| 9 | 2021 | 21 | |
| 10 | 2007 | 17 | |
| 11 | 2020 | 16 | |
| 12 | 2023 | 15 | |
| 13 | 2023 | 15 | |
| 14 | 2024 | 12 | |
| 15 | 2020 | 12 | |
| 16 | 2023 | 11 | |
| 17 | 2007 | 10 | |
| 18 | 2023 | 10 | |
| 19 | 2021 | 8 | |
| 20 | 2015 | 8 |
About Yankai Chen
Yankai Chen is a scholar working on Artificial Intelligence, Information Systems, Materials Chemistry, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 56 papers that have together received 698 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (10 papers), Recommender Systems and Techniques (10 papers), 2D Materials and Applications (4 papers), Caching and Content Delivery (4 papers), Complex Network Analysis Techniques (4 papers), Medical Image Segmentation Techniques (3 papers), Advanced Memory and Neural Computing (3 papers) and Domain Adaptation and Few-Shot Learning (3 papers). The work is most often cited by research in Electrochemistry (56 citations), Artificial Intelligence (249 citations), Information Systems (152 citations), Management Science and Operations Research (76 citations) and Statistical and Nonlinear Physics (70 citations). Yankai Chen has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Irwin King, Yixiang Fang, Suyan Teng, Ek Peng Chew, Loo Hay Lee, Xiaoning Yang, Xiaoping Wu, Fengxiang Tang, Xiaowei Yu and Luping Chang. Their work appears in journals such as Journal of Magnetism and Magnetic Materials, Physics Letters A, ACM Transactions on Information Systems, Medical Image Analysis and Frontiers in Cell and Developmental Biology.
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.