Pouya Bashivan
- Cognitive Neuroscience top 5%
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence top 10%
- Biophysics top 5%
- Cellular and Molecular Neuroscience
- Co-authors
- James J. DiCarloKohitij KarRishi RajalinghamElias B. IssaKailyn SchmidtMohammed YeasinGavin M. BidelmanN. Apurva Ratan Murty
- Topics
- Neural dynamics and brain function (11 papers)EEG and Brain-Computer Interfaces (7 papers)Functional Brain Connectivity Studies (5 papers)
- Partner nations
- United StatesCanadaIran
In The Last Decade
Pouya Bashivan
22 papers receiving 641 citations
Peers
Comparison fields: 5 of 80
- Cognitive Neuroscience 509
- Computer Vision and Pattern Recognition 135
- Artificial Intelligence 112
- Biophysics 58
- Cellular and Molecular Neuroscience 41
Countries citing papers authored by Pouya Bashivan
This map shows the geographic impact of Pouya Bashivan'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 Pouya Bashivan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pouya Bashivan more than expected).
Fields of papers citing papers by Pouya Bashivan
This network shows the impact of papers produced by Pouya Bashivan. 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 Pouya Bashivan. The network helps show where Pouya Bashivan may publish in the future.
Co-authorship network of co-authors of Pouya Bashivan
This figure shows the co-authorship network connecting the top 25 collaborators of Pouya Bashivan. A scholar is included among the top collaborators of Pouya Bashivan 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 Pouya Bashivan. Pouya Bashivan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 6 | |
| 7 | 63 | |
| 8 | 206 | |
| 9 | 35 | |
| 10 | 190 | |
| 11 | 1 | |
| 12 | Single units in a deep neural network functionally correspond with neurons in the brain: preliminary results | 4 |
| 13 | 22 | |
| 14 | 4 | |
| 15 | Commonality and singularity in working memory network predicting performance and individual differences | 2 |
| 16 | 20 | |
| 17 | 63 | |
| 18 | 16 | |
| 19 | 6 | |
| 20 | 5 |
About Pouya Bashivan
Pouya Bashivan is a scholar working on Cognitive Neuroscience, Biophysics and Computer Vision and Pattern Recognition, having authored 23 papers that have together received 657 indexed citations. Recurring topics across this work include Neural dynamics and brain function (11 papers), EEG and Brain-Computer Interfaces (7 papers) and Functional Brain Connectivity Studies (5 papers). The work is most often cited by research in Cognitive Neuroscience (509 citations), Biophysics (58 citations) and Computer Vision and Pattern Recognition (135 citations). Pouya Bashivan has collaborated with scholars based in United States, Canada and Iran. Frequent co-authors include James J. DiCarlo, Kohitij Kar, Rishi Rajalingham, Elias B. Issa, Kailyn Schmidt, Mohammed Yeasin, Gavin M. Bidelman, N. Apurva Ratan Murty, Nancy Kanwisher and Alireza Fatehi. Their work appears in journals such as Science, Nature Communications and Journal of 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.