Sajad Mousavi
- Cognitive Neuroscience top 5%
- Cardiology and Cardiovascular Medicine top 10%
- Experimental and Cognitive Psychology top 10%
- Physiology
- Biomedical Engineering
- Co-authors
- Fatemeh AfghahU. Rajendra AcharyaJonathan AshdownAlba Gutiérrez‐SacristánAliya G. FeroePaul AvillachIsaac S. KohaneNishant Uppal
- Topics
- Adversarial Robustness in Machine Learning (5 papers)ECG Monitoring and Analysis (4 papers)EEG and Brain-Computer Interfaces (3 papers)
- Cited by
- Cognitive NeuroscienceExperimental and Cognitive PsychologyCardiology and Cardiovascular Medicine
- Partner nations
- United StatesMalaysiaSingapore
In The Last Decade
Sajad Mousavi
14 papers receiving 572 citations
Hit Papers
Peers
Comparison fields: 5 of 71
- Cognitive Neuroscience 425
- Cardiology and Cardiovascular Medicine 182
- Experimental and Cognitive Psychology 113
- Physiology 101
- Biomedical Engineering 84
Countries citing papers authored by Sajad Mousavi
This map shows the geographic impact of Sajad Mousavi'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 Sajad Mousavi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sajad Mousavi more than expected).
Fields of papers citing papers by Sajad Mousavi
This network shows the impact of papers produced by Sajad Mousavi. 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 Sajad Mousavi. The network helps show where Sajad Mousavi may publish in the future.
Co-authorship network of co-authors of Sajad Mousavi
This figure shows the co-authorship network connecting the top 25 collaborators of Sajad Mousavi. A scholar is included among the top collaborators of Sajad Mousavi 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 Sajad Mousavi. Sajad Mousavi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 5 | |
| 11 | 6 | |
| 12 | 31 | |
| 13 | 26 | |
| 14 | 4 | |
| 15 | SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approachbreakdown → | 334 |
| 16 | 116 | |
| 17 | 47 |
About Sajad Mousavi
Sajad Mousavi is a scholar working on Artificial Intelligence, Cardiology and Cardiovascular Medicine and Health Information Management, having authored 17 papers that have together received 587 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (5 papers), ECG Monitoring and Analysis (4 papers) and EEG and Brain-Computer Interfaces (3 papers). The work is most often cited by research in Cognitive Neuroscience (425 citations), Experimental and Cognitive Psychology (113 citations) and Cardiology and Cardiovascular Medicine (182 citations). Sajad Mousavi has collaborated with scholars based in United States, Malaysia and Singapore. Frequent co-authors include Fatemeh Afghah, U. Rajendra Acharya, Jonathan Ashdown, Alba Gutiérrez‐Sacristán, Aliya G. Feroe, Paul Avillach, Isaac S. Kohane, Nishant Uppal, Ashwin Ramesh Babu and Antonio Guillén. Their work appears in journals such as PLoS ONE, Computer Networks and JAMA Pediatrics.
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.