Fengyu Cong
- Cognitive Neuroscience top 1%
- Signal Processing top 1%
- Experimental and Cognitive Psychology top 2%
- Computational Mathematics top 0.2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Co-authors
- Tapani RistaniemiPiia AstikainenQiu‐Hua LinXiao‐Feng GongChi ZhangLi‐Dan KuangKlaus MathiakFan Li
- Topics
- EEG and Brain-Computer Interfaces (75 papers)Blind Source Separation Techniques (65 papers)Functional Brain Connectivity Studies (53 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONENeuroImage
- Partner nations
- ChinaFinlandUnited States
In The Last Decade
Fengyu Cong
188 papers receiving 2.8k citations
Hit Papers
Peers
Comparison fields: 5 of 162
- Cognitive Neuroscience 1.7k
- Signal Processing 606
- Experimental and Cognitive Psychology 407
- Computational Mathematics 347
- Radiology, Nuclear Medicine and Imaging 346
Countries citing papers authored by Fengyu Cong
This map shows the geographic impact of Fengyu Cong'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 Fengyu Cong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fengyu Cong more than expected).
Fields of papers citing papers by Fengyu Cong
This network shows the impact of papers produced by Fengyu Cong. 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 Fengyu Cong. The network helps show where Fengyu Cong may publish in the future.
Co-authorship network of co-authors of Fengyu Cong
This figure shows the co-authorship network connecting the top 25 collaborators of Fengyu Cong. A scholar is included among the top collaborators of Fengyu Cong 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 Fengyu Cong. Fengyu Cong 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 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 4 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 13 | |
| 12 | 16 | |
| 13 | 3 | |
| 14 | 18 | |
| 15 | 21 | |
| 16 | 76 | |
| 17 | 0 | |
| 18 | 31 | |
| 19 | Fast and effective model order selection method to determine the number of sources in a linear transformation model | 17 |
| 20 | How many single trials' EEG recordings are enough to extract children's brain activity of mismatch negativity by independent component analysis? | 1 |
About Fengyu Cong
Fengyu Cong is a scholar working on Computational Mathematics, Cognitive Neuroscience and Signal Processing, having authored 208 papers that have together received 2.8k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (75 papers), Blind Source Separation Techniques (65 papers) and Functional Brain Connectivity Studies (53 papers). The work is most often cited by research in Computational Mathematics (347 citations), Cognitive Neuroscience (1.7k citations) and Signal Processing (606 citations). Fengyu Cong has collaborated with scholars based in China, Finland and United States. Frequent co-authors include Tapani Ristaniemi, Piia Astikainen, Qiu‐Hua Lin, Xiao‐Feng Gong, Chi Zhang, Li‐Dan Kuang, Klaus Mathiak, Fan Li, Zheng Chang and Heikki Lyytinen. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and NeuroImage.
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.