Manuel Moussallam
- Signal Processing top 5%
- Artificial Intelligence
- Computer Vision and Pattern Recognition top 10%
- Geophysics
- Atmospheric Science
- Co-authors
- Romain HennequinGaetano GiudiceAlessandro AiuppaYves MoussallamClive OppenheimerPhilip R. KyleC. Ian SchipperTalfan Barnie
- Topics
- Music and Audio Processing (7 papers)Speech and Audio Processing (5 papers)Music Technology and Sound Studies (3 papers)
- Journals
- Nature CommunicationsEarth and Planetary Science LettersJournal of Volcanology and Geothermal Research
- Partner nations
- FranceUnited StatesUnited Kingdom
In The Last Decade
Manuel Moussallam
13 papers receiving 316 citations
Peers
Comparison fields: 5 of 73
- Signal Processing 154
- Artificial Intelligence 91
- Computer Vision and Pattern Recognition 81
- Geophysics 69
- Atmospheric Science 49
Countries citing papers authored by Manuel Moussallam
This map shows the geographic impact of Manuel Moussallam'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 Manuel Moussallam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manuel Moussallam more than expected).
Fields of papers citing papers by Manuel Moussallam
This network shows the impact of papers produced by Manuel Moussallam. 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 Manuel Moussallam. The network helps show where Manuel Moussallam may publish in the future.
Co-authorship network of co-authors of Manuel Moussallam
This figure shows the co-authorship network connecting the top 25 collaborators of Manuel Moussallam. A scholar is included among the top collaborators of Manuel Moussallam 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 Manuel Moussallam. Manuel Moussallam 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 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 35 | |
| 7 | 1 | |
| 8 | FastGAE: Fast, Scalable and Effective Graph Autoencoders with Stochastic Subgraph Decoding. | 1 |
| 9 | 8 | |
| 10 | 147 | |
| 11 | 7 | |
| 12 | 31 | |
| 13 | 47 | |
| 14 | 2 | |
| 15 | 43 | |
| 16 | 4 | |
| 17 | 3 |
About Manuel Moussallam
Manuel Moussallam is a scholar working on Signal Processing, Developmental Biology and Computer Vision and Pattern Recognition, having authored 17 papers that have together received 333 indexed citations. Recurring topics across this work include Music and Audio Processing (7 papers), Speech and Audio Processing (5 papers) and Music Technology and Sound Studies (3 papers). The work is most often cited by research in Signal Processing (154 citations), Geophysics (69 citations) and Computer Vision and Pattern Recognition (81 citations). Manuel Moussallam has collaborated with scholars based in France, United States and United Kingdom. Frequent co-authors include Romain Hennequin, Gaetano Giudice, Alessandro Aiuppa, Yves Moussallam, Clive Oppenheimer, Philip R. Kyle, C. Ian Schipper, Talfan Barnie, Markus Schedl and Nial Peters. Their work appears in journals such as Nature Communications, Earth and Planetary Science Letters and Journal of Volcanology and Geothermal Research.
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.