Pablo Rivas
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 5%
- AI in Service Interactions
- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
Papers in
-
- Adversarial Robustness in Machine Learning 11
- Quantum Computing Algorithms and Architecture 9
- Quantum Information and Cryptography 9
- Topic Modeling 5
-
- Face and Expression Recognition 6
- Co-authors
- Ernesto Sifuentes (3 shared papers)Javier Orduz (7 shared papers)Erich J. Baker (4 shared papers)Rafael González-Landaeta (1 shared paper)Katina Michael (2 shared papers)Roba Abbas (1 shared paper)Theresa Dirndorfer Anderson (1 shared paper)Bryan F. Shaw (3 shared papers)
- Journals
- International Journal of Machine Learning and Cybernetics (2 papers)IEEE Sensors Journal (2 papers)Sensors (1 paper)IEEE Access (1 paper)Alcoholism Clinical and Experimental Research (1 paper)
- Partner nations
- United StatesMexicoCanada
In The Last Decade
Pablo Rivas
65 papers receiving 584 citations
Peers
Comparison fields: 5 of 129
- Health Informatics 56
- Artificial Intelligence 232
- Safety Research 44
- Computer Networks and Communications 99
- Signal Processing 39
Countries citing papers authored by Pablo Rivas
This map shows the geographic impact of Pablo 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 Pablo Rivas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pablo Rivas more than expected).
Fields of papers citing papers by Pablo Rivas
This network shows the impact of papers produced by Pablo 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 Pablo Rivas. The network helps show where Pablo Rivas may publish in the future.
Co-authors
The 25 scholars most cited alongside Pablo 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 68 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 96 | |
| 2 | 2016 | 40 | |
| 3 | 2023 | 39 | |
| 4 | 2013 | 35 | |
| 5 | 2017 | 33 | |
| 6 | 2012 | 29 | |
| 7 | 2013 | 28 | |
| 8 | 2024 | 21 | |
| 9 | 2022 | 20 | |
| 10 | 2014 | 17 | |
| 11 | 2020 | 17 | |
| 12 | 2013 | 17 | |
| 13 | 2019 | 16 | |
| 14 | 2012 | 15 | |
| 15 | 2022 | 12 | |
| 16 | 2019 | 11 | |
| 17 | 2013 | 9 | |
| 18 | 2021 | 9 | |
| 19 | 2014 | 8 | |
| 20 | 2021 | 8 |
About Pablo Rivas
Pablo Rivas is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Safety Research and Computer Networks and Communications, having authored 68 papers that have together received 617 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (11 papers), Quantum Computing Algorithms and Architecture (9 papers), Quantum Information and Cryptography (9 papers), Ethics and Social Impacts of AI (8 papers), Face and Expression Recognition (6 papers), Advanced Malware Detection Techniques (5 papers), Topic Modeling (5 papers) and Atmospheric aerosols and clouds (4 papers). The work is most often cited by research in Health Informatics (56 citations), Artificial Intelligence (232 citations), Safety Research (44 citations), Computer Networks and Communications (99 citations) and Signal Processing (39 citations). Pablo Rivas has collaborated with scholars based in United States, Mexico and Canada. Frequent co-authors include Ernesto Sifuentes, Javier Orduz, Erich J. Baker, Rafael González-Landaeta, Katina Michael, Roba Abbas, Theresa Dirndorfer Anderson, Bryan F. Shaw, Greg Hamerly and Jordan Richard Schoenherr. Their work appears in journals such as International Journal of Machine Learning and Cybernetics, IEEE Sensors Journal, Sensors, IEEE Access and Alcoholism Clinical and Experimental Research.
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.