Carlos Escolano
- Cognitive Neuroscience top 5%
- Artificial Intelligence top 10%
- Cellular and Molecular Neuroscience
- Transportation top 10%
- Psychiatry and Mental health
- Co-authors
- Javier MínguezMarta R. Costa‐jussàJosé A. R. FonollosaJavier Garcı́a-CampayoMayte Navarro-GilMarco CongedoLuis MontesanoAldo Arranz-López
- Topics
- Natural Language Processing Techniques (20 papers)Topic Modeling (18 papers)EEG and Brain-Computer Interfaces (15 papers)
- Journals
- SHILAP Revista de lepidopterologíaSustainabilityFrontiers in Neuroscience
- Partner nations
- SpainUnited StatesUnited Kingdom
In The Last Decade
Carlos Escolano
57 papers receiving 632 citations
Peers
Comparison fields: 5 of 93
- Cognitive Neuroscience 307
- Artificial Intelligence 187
- Cellular and Molecular Neuroscience 73
- Transportation 63
- Psychiatry and Mental health 62
Countries citing papers authored by Carlos Escolano
This map shows the geographic impact of Carlos Escolano'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 Carlos Escolano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carlos Escolano more than expected).
Fields of papers citing papers by Carlos Escolano
This network shows the impact of papers produced by Carlos Escolano. 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 Carlos Escolano. The network helps show where Carlos Escolano may publish in the future.
Co-authorship network of co-authors of Carlos Escolano
This figure shows the co-authorship network connecting the top 25 collaborators of Carlos Escolano. A scholar is included among the top collaborators of Carlos Escolano 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 Carlos Escolano. Carlos Escolano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 7 | |
| 4 | 0 | |
| 5 | 10 | |
| 6 | 11 | |
| 7 | Multilingual machine translation: Closing the gap between shared and language-specific encoder-decoders | 20 |
| 8 | 16 | |
| 9 | 1 | |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 14 | |
| 13 | Medida y valoración de la accesibilidad viaria en España: revisión de casos | 0 |
| 14 | 6 | |
| 15 | Ubicación de franquicias y grandes cadenas comerciales después de la gran recesión: El caso de la ciudad de Zaragoza | 1 |
| 16 | 51 | |
| 17 | 37 | |
| 18 | 9 | |
| 19 | 4 | |
| 20 | 107 |
About Carlos Escolano
Carlos Escolano is a scholar working on Urban Studies, Transportation and Development, having authored 67 papers that have together received 675 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (20 papers), Topic Modeling (18 papers) and EEG and Brain-Computer Interfaces (15 papers). The work is most often cited by research in Cognitive Neuroscience (307 citations), Transportation (63 citations) and Artificial Intelligence (187 citations). Carlos Escolano has collaborated with scholars based in Spain, United States and United Kingdom. Frequent co-authors include Javier Mínguez, Marta R. Costa‐jussà, José A. R. Fonollosa, Javier Garcı́a-Campayo, Mayte Navarro-Gil, Marco Congedo, Luis Montesano, Aldo Arranz-López, Julio A. Soria-Lara and Dirk De Ridder. Their work appears in journals such as SHILAP Revista de lepidopterología, Sustainability and Frontiers in Neuroscience.
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.