Yankai Chen
- Artificial Intelligence top 5%
- Information Systems top 5%
- Electrical and Electronic Engineering
- Materials Chemistry
- Management Science and Operations Research top 10%
- Co-authors
- Irwin KingYixiang FangSuyan TengLoo Hay LeeEk Peng ChewXiaoning YangXiaoping WuFengxiang Tang
- Topics
- Recommender Systems and Techniques (10 papers)Advanced Graph Neural Networks (9 papers)Medical Image Segmentation Techniques (4 papers)
- Journals
- The Journal of Physical Chemistry BEuropean Journal of Operational ResearchJournal of Membrane Science
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Yankai Chen
48 papers receiving 635 citations
Peers
Comparison fields: 5 of 100
- Artificial Intelligence 231
- Information Systems 140
- Electrical and Electronic Engineering 106
- Materials Chemistry 77
- Management Science and Operations Research 73
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-authorship network of co-authors of Yankai Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Yankai Chen. A scholar is included among the top collaborators of Yankai Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yankai Chen. Yankai Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 14 | |
| 13 | 1 | |
| 14 | 0 | |
| 15 | 6 | |
| 16 | 1 | |
| 17 | 5 | |
| 18 | Determination of 6 eugenol residues in aquatic products by ultra-high performance liquid chromatography- tandem mass spectrometry. | 1 |
| 19 | 4 | |
| 20 | BMAS 2007 | 2 |
About Yankai Chen
Yankai Chen is a scholar working on Information Systems, Artificial Intelligence and Electrochemistry, having authored 55 papers that have together received 649 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (10 papers), Advanced Graph Neural Networks (9 papers) and Medical Image Segmentation Techniques (4 papers). The work is most often cited by research in Electrochemistry (56 citations), Artificial Intelligence (231 citations) and Information Systems (140 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, Loo Hay Lee, Ek Peng Chew, Xiaoning Yang, Xiaoping Wu, Fengxiang Tang, Xiaowei Yu and Siqiang Luo. Their work appears in journals such as The Journal of Physical Chemistry B, European Journal of Operational Research and Journal of Membrane Science.
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.