Soroosh Mariooryad
- Experimental and Cognitive Psychology top 5%
- Signal Processing top 5%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Social Psychology
- Co-authors
- Carlos BussoReza LotfianAngeliki MetallinouShrikanth NarayananTam TranDilek Hakkani-TürElizabeth ShribergAnitha Kannan
- Topics
- Emotion and Mood Recognition (10 papers)Speech and Audio Processing (7 papers)Music and Audio Processing (4 papers)
- Cited by
- Experimental and Cognitive PsychologySignal ProcessingComputer Vision and Pattern Recognition
- Journals
- IEEE Transactions on Audio Speech and Language ProcessingSpeech CommunicationIEEE Transactions on Affective Computing
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Soroosh Mariooryad
15 papers receiving 424 citations
Peers
Comparison fields: 5 of 53
- Experimental and Cognitive Psychology 308
- Signal Processing 232
- Artificial Intelligence 199
- Computer Vision and Pattern Recognition 133
- Social Psychology 68
Countries citing papers authored by Soroosh Mariooryad
This map shows the geographic impact of Soroosh Mariooryad'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 Soroosh Mariooryad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Soroosh Mariooryad more than expected).
Fields of papers citing papers by Soroosh Mariooryad
This network shows the impact of papers produced by Soroosh Mariooryad. 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 Soroosh Mariooryad. The network helps show where Soroosh Mariooryad may publish in the future.
Co-authorship network of co-authors of Soroosh Mariooryad
This figure shows the co-authorship network connecting the top 25 collaborators of Soroosh Mariooryad. A scholar is included among the top collaborators of Soroosh Mariooryad 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 Soroosh Mariooryad. Soroosh Mariooryad is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 17 | |
| 3 | 23 | |
| 4 | 45 | |
| 5 | 79 | |
| 6 | 13 | |
| 7 | 16 | |
| 8 | 46 | |
| 9 | 42 | |
| 10 | 16 | |
| 11 | 35 | |
| 12 | 64 | |
| 13 | 35 | |
| 14 | 12 | |
| 15 | 13 |
About Soroosh Mariooryad
Soroosh Mariooryad is a scholar working on Signal Processing, Experimental and Cognitive Psychology and Pharmacy, having authored 15 papers that have together received 467 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (10 papers), Speech and Audio Processing (7 papers) and Music and Audio Processing (4 papers). The work is most often cited by research in Experimental and Cognitive Psychology (308 citations), Signal Processing (232 citations) and Computer Vision and Pattern Recognition (133 citations). Soroosh Mariooryad has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Carlos Busso, Reza Lotfian, Angeliki Metallinou, Shrikanth Narayanan, Tam Tran, Dilek Hakkani-Tür, Elizabeth Shriberg, Anitha Kannan, Matt Shannon and Tom Bagby. Their work appears in journals such as IEEE Transactions on Audio Speech and Language Processing, Speech Communication and IEEE Transactions on Affective Computing.
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.