Jordi Solé‐Casals
- Computational Mathematics top 5%
- Cognitive Neuroscience top 2%
- EEG and Brain-Computer Interfaces 52
- Neural dynamics and brain function 16
- Functional Brain Connectivity Studies 15
- Health Informatics top 2%
- Signal Processing top 2%
- Blind Source Separation Techniques 37
- Speech and Audio Processing 9
- Human-Computer Interaction top 5%
- Gaze Tracking and Assistive Technology 8
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- Machine Fault Diagnosis Techniques 13
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- Neuroscience and Neural Engineering 7
- Co-authors
- Andrzej CichockiZhe SunPere Martí-PuigFeng DuanFrançois VialatteCésar F. CaiafaKarmele López de IpiñaMarcos Faúndez-Zanuy
- Partner nations
- SpainUnited KingdomChina
In The Last Decade
Jordi Solé‐Casals
119 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 147
- Computational Mathematics 41
- Cognitive Neuroscience 852
- Health Informatics 52
- Signal Processing 294
- Human-Computer Interaction 104
Countries citing papers authored by Jordi Solé‐Casals
This map shows the geographic impact of Jordi Solé‐Casals'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 Jordi Solé‐Casals with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jordi Solé‐Casals more than expected).
Fields of papers citing papers by Jordi Solé‐Casals
This network shows the impact of papers produced by Jordi Solé‐Casals. 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 Jordi Solé‐Casals. The network helps show where Jordi Solé‐Casals may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jordi Solé‐Casals, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 8 | |
| 6 | 2024 | 3 | |
| 7 | 2023 | 7 | |
| 8 | 2023 | 8 | |
| 9 | 2023 | 29 | |
| 10 | 2023 | 15 | |
| 11 | 2023 | 36 | |
| 12 | 2023 | 5 | |
| 13 | 2022 | 11 | |
| 14 | 2021 | 1 | |
| 15 | EEG based user recognition using BUMP modelling | 2013 | 17 |
| 16 | 2013 | 4 | |
| 17 | 2012 | 58 | |
| 18 | Bump time-frequency toolbox: a toolbox for time-frequency oscillatory bursts extraction in electrophysiological signals | 2009 | 1 |
| 19 | Nonlinear prediction based on score function | 2002 | 1 |
| 20 | Parametric approach to blind deconvolution of nonlinear channels. | 2000 | 4 |
About Jordi Solé‐Casals
Jordi Solé‐Casals is a scholar working on Computational Mathematics, Signal Processing and Cognitive Neuroscience, having authored 126 papers that have together received 1.8k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (52 papers), Blind Source Separation Techniques (37 papers), Neural dynamics and brain function (16 papers), Functional Brain Connectivity Studies (15 papers), Machine Fault Diagnosis Techniques (13 papers), Speech and Audio Processing (9 papers), Gaze Tracking and Assistive Technology (8 papers) and Neuroscience and Neural Engineering (7 papers). The work is most often cited by research in Computational Mathematics (41 citations), Cognitive Neuroscience (852 citations) and Health Informatics (52 citations). Jordi Solé‐Casals has collaborated with scholars based in Spain, United Kingdom and China. Frequent co-authors include Andrzej Cichocki, Zhe Sun, Pere Martí-Puig, Feng Duan, François Vialatte, César F. Caiafa, Karmele López de Ipiña, Marcos Faúndez-Zanuy, Carlos M. Travieso and J. Cusidó. Their work appears in journals such as PLoS ONE, Scientific Reports and IEEE Access.
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.