Nima Bigdely-Shamlo
- Cognitive Neuroscience top 1%
- Signal Processing top 2%
- Cellular and Molecular Neuroscience top 5%
- Experimental and Cognitive Psychology top 5%
- Cardiology and Cardiovascular Medicine top 10%
- Co-authors
- Tim MullenChristian KotheScott MakeigKay A. RobbinsAndrey VankovArnaud DelormeZeynep Akalin AcarKenneth Kreutz-Delgado
- Topics
- EEG and Brain-Computer Interfaces (21 papers)Neural dynamics and brain function (16 papers)Functional Brain Connectivity Studies (10 papers)
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
Nima Bigdely-Shamlo
25 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 107
- Cognitive Neuroscience 2.0k
- Signal Processing 298
- Cellular and Molecular Neuroscience 280
- Experimental and Cognitive Psychology 247
- Cardiology and Cardiovascular Medicine 176
Countries citing papers authored by Nima Bigdely-Shamlo
This map shows the geographic impact of Nima Bigdely-Shamlo'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 Nima Bigdely-Shamlo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nima Bigdely-Shamlo more than expected).
Fields of papers citing papers by Nima Bigdely-Shamlo
This network shows the impact of papers produced by Nima Bigdely-Shamlo. 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 Nima Bigdely-Shamlo. The network helps show where Nima Bigdely-Shamlo may publish in the future.
Co-authorship network of co-authors of Nima Bigdely-Shamlo
This figure shows the co-authorship network connecting the top 25 collaborators of Nima Bigdely-Shamlo. A scholar is included among the top collaborators of Nima Bigdely-Shamlo 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 Nima Bigdely-Shamlo. Nima Bigdely-Shamlo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | 19 | |
| 3 | 8 | |
| 4 | 61 | |
| 5 | 9 | |
| 6 | 22 | |
| 7 | 22 | |
| 8 | The PREP pipeline: standardized preprocessing for large-scale EEG analysisbreakdown → | 782 |
| 9 | 36 | |
| 10 | 64 | |
| 11 | 2 | |
| 12 | 69 | |
| 13 | 17 | |
| 14 | 6 | |
| 15 | 61 | |
| 16 | 20 | |
| 17 | 111 | |
| 18 | 17 | |
| 19 | First demonstration of an EEG-based emotion BCI | 1 |
| 20 | 141 |
About Nima Bigdely-Shamlo
Nima Bigdely-Shamlo is a scholar working on Cognitive Neuroscience, Signal Processing and Human-Computer Interaction, having authored 26 papers that have together received 2.3k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (21 papers), Neural dynamics and brain function (16 papers) and Functional Brain Connectivity Studies (10 papers). The work is most often cited by research in Cognitive Neuroscience (2.0k citations), Human-Computer Interaction (173 citations) and Signal Processing (298 citations). Nima Bigdely-Shamlo has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Tim Mullen, Christian Kothe, Scott Makeig, Kay A. Robbins, Andrey Vankov, Arnaud Delorme, Zeynep Akalin Acar, Kenneth Kreutz-Delgado, Daniel P. Ferris and Joseph T. Gwin. Their work appears in journals such as NeuroImage, Proceedings of the IEEE and Frontiers in Neuroscience.
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.