Ming Jin
Impact in
-
- Emotion and Mood Recognition
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces
- Functional Brain Connectivity Studies
- Neural dynamics and brain function
Papers in
-
- Emotion and Mood Recognition 6
- Mental Health Research Topics 2
-
- EEG and Brain-Computer Interfaces 6
- Functional Brain Connectivity Studies 3
- Co-authors
- Jinpeng Li (6 shared papers)Huiguang He (3 shared papers)Zhunan Li (4 shared papers)Cunhang Fan (2 shared papers)Ting Cai (2 shared papers)Hao Chen (2 shared papers)Enwei Zhu (1 shared paper)Changde Du (1 shared paper)
- Journals
- NeuroImage (2 papers)Frontiers in Neuroscience (1 paper)IEEE Journal of Biomedical and Health Informatics (1 paper)Brain Connectivity (1 paper)IEEE photonics journal (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Ming Jin
12 papers receiving 487 citations
Ming Jin's Hit Papers
Peers
Comparison fields: 5 of 60
- Experimental and Cognitive Psychology 319
- Cognitive Neuroscience 313
- Human-Computer Interaction 61
- Computer Vision and Pattern Recognition 58
- Neurology 17
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 25 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 | 163 |
| 2 | 2022 | 117 | |
| 3 | PGCN: Pyramidal Graph Convolutional Network for EEG Emotion Recognition Hit paper breakdown → | 2024 | 76 |
| 4 | 2021 | 28 | |
| 5 | 2018 | 21 | |
| 6 | 2020 | 20 | |
| 7 | 2021 | 19 | |
| 8 | 2025 | 13 | |
| 9 | 2023 | 12 | |
| 10 | 2021 | 12 | |
| 11 | 2020 | 12 | |
| 12 | 2021 | 1 | |
| 13 | 2024 | 0 |
About Ming Jin
Ming Jin is a scholar working on Experimental and Cognitive Psychology, Cognitive Neuroscience, Human-Computer Interaction, Signal Processing and Cardiology and Cardiovascular Medicine, having authored 13 papers that have together received 494 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (6 papers), EEG and Brain-Computer Interfaces (6 papers), Gaze Tracking and Assistive Technology (3 papers), Functional Brain Connectivity Studies (3 papers), Mental Health Research Topics (2 papers), ECG Monitoring and Analysis (2 papers), Advanced Neuroimaging Techniques and Applications (2 papers) and Advanced Malware Detection Techniques (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (319 citations), Cognitive Neuroscience (313 citations), Human-Computer Interaction (61 citations), Computer Vision and Pattern Recognition (58 citations) and Neurology (17 citations). Ming Jin has collaborated with scholars based in China and United States. Frequent co-authors include Jinpeng Li, Huiguang He, Zhunan Li, Cunhang Fan, Ting Cai, Hao Chen, Enwei Zhu, Changde Du, Suprateek Kundu and Hao Chen. Their work appears in journals such as NeuroImage, Frontiers in Neuroscience, IEEE Journal of Biomedical and Health Informatics, Brain Connectivity and IEEE photonics journal.
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.