Debadatta Dash
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
- Speech and Audio Processing
Papers in
-
- EEG and Brain-Computer Interfaces 15
- Functional Brain Connectivity Studies 11
- Neural dynamics and brain function 9
- Co-authors
- Paul Ferrari (17 shared papers)Jun Wang (1 shared paper)Jun Wang (5 shared papers)Saleem Malik (3 shared papers)Jun Wang (2 shared papers)Jun Wang (4 shared papers)Joseph A. Maldjian (2 shared papers)Daragh Heitzman (3 shared papers)
- Journals
- eLife (2 papers)Current Biology (1 paper)Frontiers in Psychology (1 paper)Frontiers in Neuroscience (1 paper)IEEE Access (1 paper)
- Partner nations
- United StatesIndiaGermany
In The Last Decade
Debadatta Dash
23 papers receiving 239 citations
Peers
Comparison fields: 5 of 39
- Cognitive Neuroscience 200
- Signal Processing 65
- Cellular and Molecular Neuroscience 31
- Health Informatics 2
- Pharmacy 7
Countries citing papers authored by Debadatta Dash
This map shows the geographic impact of Debadatta Dash'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 Debadatta Dash with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Debadatta Dash more than expected).
Fields of papers citing papers by Debadatta Dash
This network shows the impact of papers produced by Debadatta Dash. 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 Debadatta Dash. The network helps show where Debadatta Dash may publish in the future.
Co-authors
The 25 scholars most cited alongside Debadatta Dash, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 72 | |
| 2 | 2020 | 24 | |
| 3 | 2018 | 18 | |
| 4 | 2020 | 18 | |
| 5 | 2019 | 15 | |
| 6 | 2019 | 14 | |
| 7 | 2018 | 11 | |
| 8 | 2020 | 11 | |
| 9 | 2019 | 10 | |
| 10 | 2018 | 9 | |
| 11 | 2019 | 8 | |
| 12 | 2021 | 8 | |
| 13 | 2020 | 6 | |
| 14 | 2020 | 5 | |
| 15 | 2024 | 5 | |
| 16 | 2018 | 5 | |
| 17 | 2018 | 5 | |
| 18 | 2023 | 2 | |
| 19 | 2024 | 2 | |
| 20 | 2023 | 2 |
About Debadatta Dash
Debadatta Dash is a scholar working on Cognitive Neuroscience, Signal Processing, Electrical and Electronic Engineering, Neurology and Psychiatry and Mental health, having authored 25 papers that have together received 254 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (15 papers), Functional Brain Connectivity Studies (11 papers), Neural dynamics and brain function (9 papers), Advanced Memory and Neural Computing (4 papers), Epilepsy research and treatment (3 papers), Action Observation and Synchronization (2 papers), Atomic and Subatomic Physics Research (2 papers) and Child and Animal Learning Development (2 papers). The work is most often cited by research in Cognitive Neuroscience (200 citations), Signal Processing (65 citations), Cellular and Molecular Neuroscience (31 citations), Health Informatics (2 citations) and Pharmacy (7 citations). Debadatta Dash has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Paul Ferrari, Jun Wang, Jun Wang, Saleem Malik, Jun Wang, Jun Wang, Joseph A. Maldjian, Daragh Heitzman, Elizabeth M. Davenport and Jun Wang. Their work appears in journals such as eLife, Current Biology, Frontiers in Psychology, Frontiers in Neuroscience and IEEE Access.
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.