Alberto Rivas
Impact in
- Software top 10%
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- Online Learning and Analytics
Papers in
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- AI-based Problem Solving and Planning 7
- Logic, Reasoning, and Knowledge 5
- Machine Learning and Algorithms 2
- Advanced Software Engineering Methodologies 2
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- Formal Methods in Verification 10
- Co-authors
- Sheila A. McIlraith (12 shared papers)Pablo Chamoso (10 shared papers)Alfonso González‐Briones (6 shared papers)Juan M. Corchado (5 shared papers)Christian Muise (6 shared papers)Jorge A. Baier (5 shared papers)Javier Prieto (1 shared paper)Guillermo Hernández (1 shared paper)
- Journals
- Electronics (2 papers)Sensors (2 papers)Logic Journal of IGPL (1 paper)Neurocomputing (1 paper)PLoS ONE (1 paper)
- Partner nations
- CanadaSpainUnited States
In The Last Decade
Alberto Rivas
24 papers receiving 538 citations
Peers
Comparison fields: 5 of 84
- Software 50
- Computer Science Applications 66
- Artificial Intelligence 295
- Computational Theory and Mathematics 144
- Computer Vision and Pattern Recognition 94
Countries citing papers authored by Alberto Rivas
This map shows the geographic impact of Alberto Rivas'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 Alberto Rivas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alberto Rivas more than expected).
Fields of papers citing papers by Alberto Rivas
This network shows the impact of papers produced by Alberto Rivas. 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 Alberto Rivas. The network helps show where Alberto Rivas may publish in the future.
Co-authors
The 25 scholars most cited alongside Alberto Rivas, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 102 | |
| 2 | 2019 | 79 | |
| 3 | 2020 | 78 | |
| 4 | 2017 | 44 | |
| 5 | 2017 | 41 | |
| 6 | 2019 | 36 | |
| 7 | 2018 | 34 | |
| 8 | 2018 | 19 | |
| 9 | 2019 | 16 | |
| 10 | 2016 | 15 | |
| 11 | 2019 | 15 | |
| 12 | 2021 | 13 | |
| 13 | 2019 | 11 | |
| 14 | 2019 | 11 | |
| 15 | 2018 | 8 | |
| 16 | 2018 | 8 | |
| 17 | 2021 | 8 | |
| 18 | 2018 | 6 | |
| 19 | Strong-Cyclic Planning when Fairness is Not a Valid Assumption. | 2016 | 6 |
| 20 | 2017 | 3 |
About Alberto Rivas
Alberto Rivas is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Software, Information Systems and Sociology and Political Science, having authored 26 papers that have together received 561 indexed citations. Recurring topics across this work include Formal Methods in Verification (10 papers), AI-based Problem Solving and Planning (7 papers), Logic, Reasoning, and Knowledge (5 papers), Model-Driven Software Engineering Techniques (3 papers), Digital Marketing and Social Media (3 papers), Software Testing and Debugging Techniques (3 papers), Machine Learning and Algorithms (2 papers) and Advanced Software Engineering Methodologies (2 papers). The work is most often cited by research in Software (50 citations), Computer Science Applications (66 citations), Artificial Intelligence (295 citations), Computational Theory and Mathematics (144 citations) and Computer Vision and Pattern Recognition (94 citations). Alberto Rivas has collaborated with scholars based in Canada, Spain and United States. Frequent co-authors include Sheila A. McIlraith, Pablo Chamoso, Alfonso González‐Briones, Juan M. Corchado, Christian Muise, Jorge A. Baier, Javier Prieto, Guillermo Hernández, Rodrigo Toro Icarte and Richard Valenzano. Their work appears in journals such as Electronics, Sensors, Logic Journal of IGPL, Neurocomputing and PLoS ONE.
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.