Shovan Barma
Impact in
- Cognitive Neuroscience top 10%
- EEG and Brain-Computer Interfaces
- Functional Brain Connectivity Studies
- Neural dynamics and brain function
- Signal Processing top 10%
- Blind Source Separation Techniques
Papers in
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- EEG and Brain-Computer Interfaces 20
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- Blind Source Separation Techniques 11
- Co-authors
- Samarendra Dandapat (11 shared papers)Bo‐Wei Chen (3 shared papers)Jhing-Fa Wang (5 shared papers)Sio Hang Pun (6 shared papers)Mang I Vai (4 shared papers)Peng Un Mak (5 shared papers)Jiawen Li (4 shared papers)Feng Jiang (1 shared paper)
In The Last Decade
Shovan Barma
44 papers receiving 398 citations
Peers
Comparison fields: 5 of 87
- Cognitive Neuroscience 206
- Signal Processing 77
- Experimental and Cognitive Psychology 94
- Human-Computer Interaction 25
- Cardiology and Cardiovascular Medicine 70
Countries citing papers authored by Shovan Barma
This map shows the geographic impact of Shovan Barma'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 Shovan Barma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shovan Barma more than expected).
Fields of papers citing papers by Shovan Barma
This network shows the impact of papers produced by Shovan Barma. 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 Shovan Barma. The network helps show where Shovan Barma may publish in the future.
Co-authors
The 24 scholars most cited alongside Shovan Barma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 46 | |
| 2 | 2015 | 31 | |
| 3 | 2021 | 28 | |
| 4 | 2020 | 28 | |
| 5 | 2022 | 23 | |
| 6 | 2014 | 22 | |
| 7 | 2015 | 21 | |
| 8 | 2020 | 19 | |
| 9 | 2022 | 18 | |
| 10 | 2015 | 17 | |
| 11 | 2019 | 17 | |
| 12 | 2020 | 16 | |
| 13 | 2021 | 13 | |
| 14 | 2019 | 11 | |
| 15 | 2022 | 10 | |
| 16 | 2021 | 7 | |
| 17 | 2023 | 5 | |
| 18 | 2017 | 5 | |
| 19 | 2015 | 5 | |
| 20 | 2008 | 5 |
About Shovan Barma
Shovan Barma is a scholar working on Cognitive Neuroscience, Signal Processing, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Cardiology and Cardiovascular Medicine, having authored 48 papers that have together received 407 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (20 papers), Blind Source Separation Techniques (11 papers), Emotion and Mood Recognition (8 papers), Phonocardiography and Auscultation Techniques (5 papers), Machine Fault Diagnosis Techniques (4 papers), Smart Agriculture and AI (4 papers), ECG Monitoring and Analysis (4 papers) and Epilepsy research and treatment (4 papers). The work is most often cited by research in Cognitive Neuroscience (206 citations), Signal Processing (77 citations), Experimental and Cognitive Psychology (94 citations), Human-Computer Interaction (25 citations) and Cardiology and Cardiovascular Medicine (70 citations). Shovan Barma has collaborated with scholars based in India, Taiwan and China. Frequent co-authors include Samarendra Dandapat, Bo‐Wei Chen, Jhing-Fa Wang, Sio Hang Pun, Mang I Vai, Peng Un Mak, Jiawen Li, Feng Jiang, Anne James and Kashif Iqbal. Their work appears in journals such as IEEE Transactions on Instrumentation and Measurement, Biomedical Signal Processing and Control, IEEE Journal of Biomedical and Health Informatics, IEEE Access and IEEE/ACM Transactions on Computational Biology and 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.