Ursula Laa
Impact in
- Nuclear and High Energy Physics top 10%
- Particle physics theoretical and experimental studies
- Dark Matter and Cosmic Phenomena
- Black Holes and Theoretical Physics
- Neutrino Physics Research
- Particle Detector Development and Performance
- Quantum Chromodynamics and Particle Interactions
- Astronomy and Astrophysics top 10%
- Cosmology and Gravitation Theories
Papers in
-
- Particle physics theoretical and experimental studies 9
- Particle Detector Development and Performance 6
- Dark Matter and Cosmic Phenomena 3
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- Data Analysis with R 4
- Computational Physics and Python Applications 3
- Advanced Clustering Algorithms Research 1
- Co-authors
- Sabine Kraml (5 shared papers)G. Bélanger (2 shared papers)Jonathan Da Silva (2 shared papers)A. Pukhov (2 shared papers)Jérémy Bernon (1 shared paper)F. Boudjema (1 shared paper)Daniele Barducci (1 shared paper)André Lessa (3 shared papers)
In The Last Decade
Ursula Laa
18 papers receiving 266 citations
Peers
Comparison fields: 5 of 26
- Nuclear and High Energy Physics 252
- Astronomy and Astrophysics 136
- Computational Mathematics 1
- Artificial Intelligence 40
- Tourism, Leisure and Hospitality Management 1
Countries citing papers authored by Ursula Laa
This map shows the geographic impact of Ursula Laa'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 Ursula Laa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ursula Laa more than expected).
Fields of papers citing papers by Ursula Laa
This network shows the impact of papers produced by Ursula Laa. 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 Ursula Laa. The network helps show where Ursula Laa may publish in the future.
Co-authors
The 25 scholars most cited alongside Ursula Laa, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 103 | |
| 2 | 2019 | 44 | |
| 3 | 2018 | 43 | |
| 4 | 2017 | 23 | |
| 5 | 2015 | 16 | |
| 6 | 2018 | 13 | |
| 7 | 2019 | 10 | |
| 8 | 2018 | 4 | |
| 9 | 2024 | 2 | |
| 10 | 2017 | 2 | |
| 11 | 2021 | 2 | |
| 12 | 2022 | 2 | |
| 13 | 2021 | 2 | |
| 14 | 2024 | 1 | |
| 15 | 2025 | 1 | |
| 16 | 2023 | 1 | |
| 17 | 2019 | 1 | |
| 18 | 2024 | 1 | |
| 19 | 2025 | 0 |
About Ursula Laa
Ursula Laa is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition and Global and Planetary Change, having authored 19 papers that have together received 271 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (9 papers), Particle Detector Development and Performance (6 papers), Data Analysis with R (4 papers), Computational Physics and Python Applications (3 papers), Dark Matter and Cosmic Phenomena (3 papers), Distributed and Parallel Computing Systems (3 papers), Data Visualization and Analytics (2 papers) and Advanced Clustering Algorithms Research (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (252 citations), Astronomy and Astrophysics (136 citations), Computational Mathematics (1 citation), Artificial Intelligence (40 citations) and Tourism, Leisure and Hospitality Management (1 citation). Ursula Laa has collaborated with scholars based in Austria, Australia and France. Frequent co-authors include Sabine Kraml, G. Bélanger, Jonathan Da Silva, A. Pukhov, Jérémy Bernon, F. Boudjema, Daniele Barducci, André Lessa, W. Waltenberger and F. Ambrogi. Their work appears in journals such as The European Physical Journal C, Computer Physics Communications, Journal of Computational and Graphical Statistics, The R Journal and Wiley Interdisciplinary Reviews Computational Statistics.
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.