Jinpeng Li
- Cognitive Neuroscience top 2%
- Experimental and Cognitive Psychology top 1%
- Artificial Intelligence top 5%
- Human-Computer Interaction top 2%
- Computer Vision and Pattern Recognition top 5%
- Topics
- EEG and Brain-Computer Interfaces (15 papers)Emotion and Mood Recognition (11 papers)Radiomics and Machine Learning in Medical Imaging (8 papers)
In The Last Decade
Jinpeng Li
40 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Cognitive Neuroscience 972
- Experimental and Cognitive Psychology 785
- Artificial Intelligence 362
- Human-Computer Interaction 205
- Computer Vision and Pattern Recognition 197
Countries citing papers authored by Jinpeng Li
This map shows the geographic impact of Jinpeng Li'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 Jinpeng Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jinpeng Li more than expected).
Fields of papers citing papers by Jinpeng Li
This network shows the impact of papers produced by Jinpeng Li. 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 Jinpeng Li. The network helps show where Jinpeng Li may publish in the future.
Co-authorship network of co-authors of Jinpeng Li
This figure shows the co-authorship network connecting the top 25 collaborators of Jinpeng Li. A scholar is included among the top collaborators of Jinpeng Li 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 Jinpeng Li. Jinpeng Li 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 | PGCN: Pyramidal Graph Convolutional Network for EEG Emotion Recognitionbreakdown → | 42 |
| 3 | 8 | |
| 4 | 5 | |
| 5 | 52 | |
| 6 | 7 | |
| 7 | 0 | |
| 8 | 8 | |
| 9 | 1 | |
| 10 | 56 | |
| 11 | 95 | |
| 12 | 10 | |
| 13 | 78 | |
| 14 | MS-MDA: Multisource Marginal Distribution Adaptation for Cross-Subject and Cross-Session EEG Emotion Recognitionbreakdown → | 141 |
| 15 | 11 | |
| 16 | 34 | |
| 17 | 6 | |
| 18 | 9 | |
| 19 | 222 | |
| 20 | Multisource Transfer Learning for Cross-Subject EEG Emotion Recognitionbreakdown → | 283 |
About Jinpeng Li
Jinpeng Li is a scholar working on Experimental and Cognitive Psychology, Human-Computer Interaction and Cognitive Neuroscience, having authored 45 papers that have together received 1.5k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (15 papers), Emotion and Mood Recognition (11 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). The work is most often cited by research in Experimental and Cognitive Psychology (785 citations), Cognitive Neuroscience (972 citations) and Human-Computer Interaction (205 citations). Jinpeng Li has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Huiguang He, Shuang Qiu, Zhaoxiang Zhang, Changde Du, Ming Jin, Yuanyuan Shen, Cheng‐Lin Liu, Ting Cai, Yixin Wang and Zhunan Li. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Access and BMC Bioinformatics.
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.