Sheng‐Fu Liang
- Cognitive Neuroscience top 1%
- Experimental and Cognitive Psychology top 1%
- Biomedical Engineering top 5%
- Cellular and Molecular Neuroscience top 5%
- Cardiology and Cardiovascular Medicine top 5%
- Co-authors
- Chin‐Teng LinTzyy‐Ping JungLi‐Wei KoRuei-Cheng WuChih‐En KuoYung-Hung WangTeng‐Yi HuangWen-Hung Chao
- Topics
- EEG and Brain-Computer Interfaces (52 papers)Neuroscience and Neural Engineering (17 papers)Blind Source Separation Techniques (16 papers)
- Partner nations
- TaiwanUnited StatesIndia
In The Last Decade
Sheng‐Fu Liang
101 papers receiving 3.0k citations
Peers
Comparison fields: 5 of 130
- Cognitive Neuroscience 1.9k
- Experimental and Cognitive Psychology 769
- Biomedical Engineering 602
- Cellular and Molecular Neuroscience 547
- Cardiology and Cardiovascular Medicine 467
Countries citing papers authored by Sheng‐Fu Liang
This map shows the geographic impact of Sheng‐Fu Liang'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 Sheng‐Fu Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sheng‐Fu Liang more than expected).
Fields of papers citing papers by Sheng‐Fu Liang
This network shows the impact of papers produced by Sheng‐Fu Liang. 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 Sheng‐Fu Liang. The network helps show where Sheng‐Fu Liang may publish in the future.
Co-authorship network of co-authors of Sheng‐Fu Liang
This figure shows the co-authorship network connecting the top 25 collaborators of Sheng‐Fu Liang. A scholar is included among the top collaborators of Sheng‐Fu Liang 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 Sheng‐Fu Liang. Sheng‐Fu Liang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 107 | |
| 8 | 7 | |
| 9 | 4 | |
| 10 | 20 | |
| 11 | 143 | |
| 12 | 2 | |
| 13 | 54 | |
| 14 | 3 | |
| 15 | Machine Learning with Automatic Feature Selection for Multi-class Protein Fold Classification * | 2 |
| 16 | 6 | |
| 17 | Modeling and analysis of acoustic musical strings using kelly-lochbaum lattice networks | 3 |
| 18 | Recurrent Neural-Network-Based Physical Model for the Chin and Other Plucked-String Instruments | 4 |
| 19 | 10 | |
| 20 | A Generalized Model-Based Analysis/Synthesis Method for Plucked-String Instruments by Using Recurrent Neural Networks | 1 |
About Sheng‐Fu Liang
Sheng‐Fu Liang is a scholar working on Cognitive Neuroscience, Signal Processing and Human-Computer Interaction, having authored 106 papers that have together received 3.2k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (52 papers), Neuroscience and Neural Engineering (17 papers) and Blind Source Separation Techniques (16 papers). The work is most often cited by research in Cognitive Neuroscience (1.9k citations), Human-Computer Interaction (377 citations) and Experimental and Cognitive Psychology (769 citations). Sheng‐Fu Liang has collaborated with scholars based in Taiwan, United States and India. Frequent co-authors include Chin‐Teng Lin, Tzyy‐Ping Jung, Li‐Wei Ko, Ruei-Cheng Wu, Chih‐En Kuo, Yung-Hung Wang, Teng‐Yi Huang, Wen-Hung Chao, Yujie Chen and Yuhan Hu. Their work appears in journals such as NeuroImage, The Journal of Physiology and Proceedings of the IEEE.
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.