Rafael C. Núñez
- Modeling and Simulation top 5%
- Artificial Intelligence
- Infectious Diseases
- Computational Mechanics
- Signal Processing
- Co-authors
- John P. NolanKamal PremaratneJ.G. GonzalezManohar N. MurthiGonzalo R. ArceMichał JastrzębskiJasmina Panovska‐GriffithsJamie A. Cohen
- Topics
- Bayesian Modeling and Causal Inference (3 papers)Logic, Reasoning, and Knowledge (3 papers)Parallel Computing and Optimization Techniques (3 papers)
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaIEEE Transactions on Signal Processing
- Partner nations
- United StatesAustraliaDenmark
In The Last Decade
Rafael C. Núñez
11 papers receiving 154 citations
Peers
Comparison fields: 5 of 63
- Modeling and Simulation 46
- Artificial Intelligence 36
- Infectious Diseases 35
- Computational Mechanics 18
- Signal Processing 17
Countries citing papers authored by Rafael C. Núñez
This map shows the geographic impact of Rafael C. Núñez'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 Rafael C. Núñez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rafael C. Núñez more than expected).
Fields of papers citing papers by Rafael C. Núñez
This network shows the impact of papers produced by Rafael C. Núñez. 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 Rafael C. Núñez. The network helps show where Rafael C. Núñez may publish in the future.
Co-authorship network of co-authors of Rafael C. Núñez
This figure shows the co-authorship network connecting the top 25 collaborators of Rafael C. Núñez. A scholar is included among the top collaborators of Rafael C. Núñez 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 Rafael C. Núñez. Rafael C. Núñez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 73 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | Efficient computation of DS-based uncertain logic operations and its application to hard and soft data fusion | 5 |
| 5 | Dynamics of belief theoretic agent opinions under bounded confidence | 3 |
| 6 | DS-based uncertain implication rules for inference and fusion applications | 9 |
| 7 | Hard and soft data fusion for joint tracking and classification/intent-detection | 7 |
| 8 | Modeling uncertainty in first-order logic: A dempster-shafer theoretic approach | 7 |
| 9 | 6 | |
| 10 | 14 | |
| 11 | 23 | |
| 12 | 2 |
About Rafael C. Núñez
Rafael C. Núñez is a scholar working on Hardware and Architecture, Modeling and Simulation and Computational Theory and Mathematics, having authored 12 papers that have together received 155 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (3 papers), Logic, Reasoning, and Knowledge (3 papers) and Parallel Computing and Optimization Techniques (3 papers). The work is most often cited by research in Modeling and Simulation (46 citations), Hardware and Architecture (13 citations) and Infectious Diseases (35 citations). Rafael C. Núñez has collaborated with scholars based in United States, Australia and Denmark. Frequent co-authors include John P. Nolan, Kamal Premaratne, J.G. Gonzalez, Manohar N. Murthi, Gonzalo R. Arce, Michał Jastrzębski, Jasmina Panovska‐Griffiths, Jamie A. Cohen, Michael Famulare and Jeffrey S. Duchin. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and IEEE Transactions on Signal Processing.
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.