David Gil
Impact in
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- Online Learning and Analytics
Papers in
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- E-Learning and Knowledge Management 6
- Online Learning and Analytics 5
- Co-authors
- Higinio Mora (25 shared papers)Magnus Johnsson (19 shared papers)Jesús Peral (19 shared papers)Antonio Ferrández (11 shared papers)Julian Szymański (9 shared papers)Sergio Luján‐Mora (4 shared papers)Diego Buenaño-Fernández (3 shared papers)Ricardo Sellers Rubio (3 shared papers)
In The Last Decade
David Gil
82 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 155
- Computer Science Applications 159
- Health Information Management 98
- Computer Networks and Communications 435
- Information Systems 384
- Artificial Intelligence 555
Countries citing papers authored by David Gil
This map shows the geographic impact of David Gil'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 David Gil with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Gil more than expected).
Fields of papers citing papers by David Gil
This network shows the impact of papers produced by David Gil. 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 David Gil. The network helps show where David Gil may publish in the future.
Co-authors
The 25 scholars most cited alongside David Gil, 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 87 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 175 | |
| 2 | 2016 | 170 | |
| 3 | 2017 | 143 | |
| 4 | 2019 | 112 | |
| 5 | 2012 | 106 | |
| 6 | Diagnosing Parkinson by using artificial neural networks and support vector machines | 2009 | 103 |
| 7 | 2020 | 82 | |
| 8 | 2005 | 76 | |
| 9 | 2019 | 74 | |
| 10 | 2008 | 69 | |
| 11 | 1982 | 66 | |
| 12 | 2018 | 53 | |
| 13 | 2013 | 52 | |
| 14 | 2015 | 49 | |
| 15 | 2015 | 41 | |
| 16 | 2019 | 39 | |
| 17 | 2019 | 31 | |
| 18 | 2018 | 31 | |
| 19 | 2018 | 27 | |
| 20 | 2015 | 26 |
About David Gil
David Gil is a scholar working on Computer Science Applications, Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition and Information Systems, having authored 87 papers that have together received 2.0k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (13 papers), Context-Aware Activity Recognition Systems (9 papers), Autism Spectrum Disorder Research (6 papers), E-Learning and Knowledge Management (6 papers), Cloud Computing and Resource Management (5 papers), Time Series Analysis and Forecasting (5 papers), Online Learning and Analytics (5 papers) and Data Quality and Management (4 papers). The work is most often cited by research in Computer Science Applications (159 citations), Health Information Management (98 citations), Computer Networks and Communications (435 citations), Information Systems (384 citations) and Artificial Intelligence (555 citations). David Gil has collaborated with scholars based in Spain, Sweden and Poland. Frequent co-authors include Higinio Mora, Magnus Johnsson, Jesús Peral, Antonio Ferrández, Julian Szymański, Sergio Luján‐Mora, Diego Buenaño-Fernández, Ricardo Sellers Rubio, Joaquı́n De Juan and María José Gómez‐Torres. Their work appears in journals such as IEEE Access, Sensors, Sustainability, Expert Systems with Applications and Future Generation Computer Systems.
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.