Jorge A. Navas
- Artificial Intelligence
- Software top 5%
- Information Systems top 10%
- Hardware and Architecture top 10%
- Computer Networks and Communications
- Co-authors
- Joxan JaffarVijayaraghavan MuraliManuel V. HermenegildoMario Méndez-LojoArie GurfinkelMooly SagivNina NarodytskaNadav Amit
- Topics
- Logic, programming, and type systems (10 papers)Formal Methods in Verification (9 papers)Software Testing and Debugging Techniques (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaCommunications of the ACMTheoretical Computer Science
- Partner nations
- United StatesAustraliaSingapore
In The Last Decade
Jorge A. Navas
15 papers receiving 130 citations
Peers
Comparison fields: 5 of 13
- Artificial Intelligence 64
- Software 56
- Information Systems 51
- Hardware and Architecture 41
- Computer Networks and Communications 39
Countries citing papers authored by Jorge A. Navas
This map shows the geographic impact of Jorge A. Navas'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 Jorge A. Navas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jorge A. Navas more than expected).
Fields of papers citing papers by Jorge A. Navas
This network shows the impact of papers produced by Jorge A. Navas. 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 Jorge A. Navas. The network helps show where Jorge A. Navas may publish in the future.
Co-authorship network of co-authors of Jorge A. Navas
This figure shows the co-authorship network connecting the top 25 collaborators of Jorge A. Navas. A scholar is included among the top collaborators of Jorge A. Navas 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 Jorge A. Navas. Jorge A. Navas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 48 | |
| 5 | 1 | |
| 6 | 10 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 9 | |
| 10 | 30 | |
| 11 | 12 | |
| 12 | Customizable resource usage analysis for java bytecode | 2 |
| 13 | Safe upper-bounds inference of energy consumption for java bytecode applications | 7 |
| 14 | A generic, context sensitive analysis framework for object oriented programs | 1 |
| 15 | 7 | |
| 16 | An efficient, parametric fixpoint algorithm forincremental analysis of java bytecode | 0 |
| 17 | Las cestas autonómicas | 0 |
About Jorge A. Navas
Jorge A. Navas is a scholar working on Software, Computational Theory and Mathematics and Hardware and Architecture, having authored 17 papers that have together received 136 indexed citations. Recurring topics across this work include Logic, programming, and type systems (10 papers), Formal Methods in Verification (9 papers) and Software Testing and Debugging Techniques (6 papers). The work is most often cited by research in Software (56 citations), Hardware and Architecture (41 citations) and Information Systems (51 citations). Jorge A. Navas has collaborated with scholars based in United States, Australia and Singapore. Frequent co-authors include Joxan Jaffar, Vijayaraghavan Murali, Manuel V. Hermenegildo, Mario Méndez-Lojo, Arie Gurfinkel, Mooly Sagiv, Nina Narodytska, Nadav Amit, Noam Rinetzky and Leonid Ryzhyk. Their work appears in journals such as SHILAP Revista de lepidopterología, Communications of the ACM and Theoretical Computer Science.
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.