Alexander Krauß
- Artificial Intelligence
- Economics and Econometrics
- Statistics, Probability and Uncertainty top 5%
- Computational Theory and Mathematics top 10%
- Sociology and Political Science
- Co-authors
- Tobias NipkowUwe PetersOliver BraganzaMarta Sales‐PardoCarl HoeferAna BoveMatthieu SozeauMatteo Colombo
- Topics
- scientometrics and bibliometrics research (8 papers)Logic, programming, and type systems (7 papers)Formal Methods in Verification (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- United KingdomSpainUnited States
In The Last Decade
Alexander Krauß
31 papers receiving 303 citations
Peers
Comparison fields: 5 of 113
- Artificial Intelligence 85
- Economics and Econometrics 55
- Statistics, Probability and Uncertainty 51
- Computational Theory and Mathematics 51
- Sociology and Political Science 46
Countries citing papers authored by Alexander Krauß
This map shows the geographic impact of Alexander Krauß'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 Alexander Krauß with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Krauß more than expected).
Fields of papers citing papers by Alexander Krauß
This network shows the impact of papers produced by Alexander Krauß. 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 Alexander Krauß. The network helps show where Alexander Krauß may publish in the future.
Co-authorship network of co-authors of Alexander Krauß
This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Krauß. A scholar is included among the top collaborators of Alexander Krauß 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 Alexander Krauß. Alexander Krauß is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 7 | |
| 5 | 6 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 8 | |
| 9 | 7 | |
| 10 | 20 | |
| 11 | 4 | |
| 12 | 3 | |
| 13 | 18 | |
| 14 | 27 | |
| 15 | 2 | |
| 16 | 3 | |
| 17 | Regular Sets and Expressions. | 2 |
| 18 | 6 | |
| 19 | 13 | |
| 20 | 0 |
About Alexander Krauß
Alexander Krauß is a scholar working on Statistics, Probability and Uncertainty, History and Philosophy of Science and Business and International Management, having authored 34 papers that have together received 325 indexed citations. Recurring topics across this work include scientometrics and bibliometrics research (8 papers), Logic, programming, and type systems (7 papers) and Formal Methods in Verification (6 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (51 citations), Safety Research (29 citations) and Computational Theory and Mathematics (51 citations). Alexander Krauß has collaborated with scholars based in United Kingdom, Spain and United States. Frequent co-authors include Tobias Nipkow, Uwe Peters, Oliver Braganza, Marta Sales‐Pardo, Carl Hoefer, Ana Bove, Matthieu Sozeau, Matteo Colombo, Carol Graham and Jasmin Christian Blanchette. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.