Enea Ceolini
Impact in
- Signal Processing top 5%
- Speech and Audio Processing
- Music and Audio Processing
- Health Informatics top 5%
Papers in
-
- Speech and Audio Processing 12
- Music and Audio Processing 8
-
- EEG and Brain-Computer Interfaces 5
- Neural dynamics and brain function 4
- Co-authors
- Marco Ancona (3 shared papers)Markus Groß (3 shared papers)Cengiz Öztireli (3 shared papers)Shih‐Chii Liu (15 shared papers)Tobi Delbrück (2 shared papers)Daniel Neil (3 shared papers)Daniel D.E. Wong (4 shared papers)Nima Mesgarani (2 shared papers)
- Journals
- iScience (3 papers)Frontiers in Neuroscience (2 papers)IEEE Signal Processing Magazine (1 paper)NeuroImage (1 paper)npj Digital Medicine (1 paper)
- Partner nations
- SwitzerlandNetherlandsFrance
In The Last Decade
Enea Ceolini
27 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 108
- Signal Processing 255
- Health Informatics 28
- Cognitive Neuroscience 268
- Artificial Intelligence 464
- Computer Vision and Pattern Recognition 161
Countries citing papers authored by Enea Ceolini
This map shows the geographic impact of Enea Ceolini'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 Enea Ceolini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Enea Ceolini more than expected).
Fields of papers citing papers by Enea Ceolini
This network shows the impact of papers produced by Enea Ceolini. 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 Enea Ceolini. The network helps show where Enea Ceolini may publish in the future.
Co-authors
The 25 scholars most cited alongside Enea Ceolini, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 180 | |
| 2 | 2019 | 155 | |
| 3 | 2020 | 136 | |
| 4 | 2018 | 110 | |
| 5 | 2018 | 92 | |
| 6 | 2019 | 87 | |
| 7 | 2020 | 57 | |
| 8 | 2019 | 55 | |
| 9 | 2017 | 47 | |
| 10 | 2018 | 16 | |
| 11 | 2018 | 15 | |
| 12 | 2019 | 13 | |
| 13 | 2021 | 12 | |
| 14 | 2017 | 12 | |
| 15 | 2019 | 10 | |
| 16 | 2022 | 9 | |
| 17 | 2022 | 8 | |
| 18 | 2020 | 7 | |
| 19 | 2025 | 7 | |
| 20 | 2019 | 6 |
About Enea Ceolini
Enea Ceolini is a scholar working on Signal Processing, Cognitive Neuroscience, Artificial Intelligence, Computational Mechanics and Electrical and Electronic Engineering, having authored 28 papers that have together received 1.1k indexed citations. Recurring topics across this work include Speech and Audio Processing (12 papers), Music and Audio Processing (8 papers), Speech Recognition and Synthesis (5 papers), EEG and Brain-Computer Interfaces (5 papers), Advanced Adaptive Filtering Techniques (4 papers), Neural dynamics and brain function (4 papers), Explainable Artificial Intelligence (XAI) (3 papers) and Adversarial Robustness in Machine Learning (3 papers). The work is most often cited by research in Signal Processing (255 citations), Health Informatics (28 citations), Cognitive Neuroscience (268 citations), Artificial Intelligence (464 citations) and Computer Vision and Pattern Recognition (161 citations). Enea Ceolini has collaborated with scholars based in Switzerland, Netherlands and France. Frequent co-authors include Marco Ancona, Markus Groß, Cengiz Öztireli, Shih‐Chii Liu, Tobi Delbrück, Daniel Neil, Daniel D.E. Wong, Nima Mesgarani, Elisa Donati and Jens Hjortkjær. Their work appears in journals such as iScience, Frontiers in Neuroscience, IEEE Signal Processing Magazine, NeuroImage and npj Digital Medicine.
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.