Feng Ji
- Artificial Intelligence top 10%
- Statistical and Nonlinear Physics top 5%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications
- Electrical and Electronic Engineering
- Co-authors
- Wee Peng TayCheng DengBangjun WangLingling AnLav R. VarshneyJie ZhengKejia XieXinbo Gao
- Topics
- Complex Network Analysis Techniques (21 papers)Advanced Graph Neural Networks (19 papers)Topic Modeling (8 papers)
- Cited by
- Statistical and Nonlinear PhysicsComputer Vision and Pattern RecognitionComputational Mathematics
- Partner nations
- ChinaSingaporeUnited States
In The Last Decade
Feng Ji
69 papers receiving 490 citations
Peers
Comparison fields: 5 of 103
- Artificial Intelligence 142
- Statistical and Nonlinear Physics 134
- Computer Vision and Pattern Recognition 126
- Computer Networks and Communications 52
- Electrical and Electronic Engineering 52
Countries citing papers authored by Feng Ji
This map shows the geographic impact of Feng Ji'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 Feng Ji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feng Ji more than expected).
Fields of papers citing papers by Feng Ji
This network shows the impact of papers produced by Feng Ji. 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 Feng Ji. The network helps show where Feng Ji may publish in the future.
Co-authorship network of co-authors of Feng Ji
This figure shows the co-authorship network connecting the top 25 collaborators of Feng Ji. A scholar is included among the top collaborators of Feng Ji 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 Feng Ji. Feng Ji is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 11 | |
| 9 | 4 | |
| 10 | 6 | |
| 11 | 12 | |
| 12 | 25 | |
| 13 | 8 | |
| 14 | 37 | |
| 15 | Joint Segmentation and Tagging with Coupled Sequences Labeling | 5 |
| 16 | Applications of Fuzzy Lifting Wavelet Packet Transform in MFL Signal Processing | 3 |
| 17 | Detecting Hedge Cues and their Scopes with Average Perceptron | 2 |
| 18 | 7 | |
| 19 | 1 | |
| 20 | 2 |
About Feng Ji
Feng Ji is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 74 papers that have together received 514 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (21 papers), Advanced Graph Neural Networks (19 papers) and Topic Modeling (8 papers). The work is most often cited by research in Statistical and Nonlinear Physics (134 citations), Computer Vision and Pattern Recognition (126 citations) and Computational Mathematics (3 citations). Feng Ji has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Wee Peng Tay, Cheng Deng, Bangjun Wang, Lingling An, Lav R. Varshney, Jie Zheng, Kejia Xie, Xinbo Gao, Da-Ren He and Dacheng Tao. Their work appears in journals such as Scientific Reports, IEEE Transactions on Signal Processing and IEEE Access.
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.