Ming Jin
Impact in
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- Emotion and Mood Recognition
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces
- Functional Brain Connectivity Studies
- Neural dynamics and brain function
Papers in
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- EEG and Brain-Computer Interfaces 6
- Functional Brain Connectivity Studies 2
-
- Emotion and Mood Recognition 6
- Mental Health Research Topics 1
- Co-authors
- Jinpeng Li (6 shared papers)Zhunan Li (4 shared papers)Huiguang He (3 shared papers)Cunhang Fan (2 shared papers)Hao Chen (2 shared papers)Ting Cai (2 shared papers)Changde Du (1 shared paper)Suprateek Kundu (2 shared papers)
- Journals
- NeuroImage (1 paper)Frontiers in Neuroscience (1 paper)IEEE Journal of Biomedical and Health Informatics (1 paper)Brain Connectivity (1 paper)IEEE Transactions on Multimedia (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Ming Jin
10 papers receiving 379 citations
Ming Jin's Hit Papers
Peers
Comparison fields: 5 of 60
- Experimental and Cognitive Psychology 253
- Cognitive Neuroscience 283
- Human-Computer Interaction 55
- Computer Vision and Pattern Recognition 57
- Artificial Intelligence 66
Countries citing papers authored by Ming Jin
This map shows the geographic impact of Ming Jin'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 Ming Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Jin more than expected).
Fields of papers citing papers by Ming Jin
This network shows the impact of papers produced by Ming Jin. 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 Ming Jin. The network helps show where Ming Jin may publish in the future.
Co-authors
The 23 scholars most cited alongside Ming Jin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | MS-MDA: Multisource Marginal Distribution Adaptation for Cross-Subject and Cross-Session EEG Emotion Recognition Hit paper breakdown → | 2021 | 141 |
| 2 | 2022 | 95 | |
| 3 | PGCN: Pyramidal Graph Convolutional Network for EEG Emotion Recognition Hit paper breakdown → | 2024 | 42 |
| 4 | 2021 | 22 | |
| 5 | 2020 | 20 | |
| 6 | 2018 | 17 | |
| 7 | 2021 | 15 | |
| 8 | 2020 | 12 | |
| 9 | 2021 | 10 | |
| 10 | 2023 | 7 | |
| 11 | 2025 | 0 | |
| 12 | 2025 | 0 |
About Ming Jin
Ming Jin is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology, Radiology, Nuclear Medicine and Imaging, Human-Computer Interaction and Cardiology and Cardiovascular Medicine, having authored 12 papers that have together received 381 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (6 papers), Emotion and Mood Recognition (6 papers), Gaze Tracking and Assistive Technology (3 papers), Advanced Neuroimaging Techniques and Applications (2 papers), Functional Brain Connectivity Studies (2 papers), ECG Monitoring and Analysis (2 papers), Surface Roughness and Optical Measurements (1 paper) and Mental Health Research Topics (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (253 citations), Cognitive Neuroscience (283 citations), Human-Computer Interaction (55 citations), Computer Vision and Pattern Recognition (57 citations) and Artificial Intelligence (66 citations). Ming Jin has collaborated with scholars based in China and United States. Frequent co-authors include Jinpeng Li, Zhunan Li, Huiguang He, Cunhang Fan, Hao Chen, Ting Cai, Changde Du, Suprateek Kundu, Hao Chen and Ying Guo. Their work appears in journals such as NeuroImage, Frontiers in Neuroscience, IEEE Journal of Biomedical and Health Informatics, Brain Connectivity and IEEE Transactions on Multimedia.
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.