Matej Pivoluska
- Artificial Intelligence top 5%
- Atomic and Molecular Physics, and Optics top 10%
- Computer Vision and Pattern Recognition
- Computational Theory and Mathematics
- Electrical and Electronic Engineering
- Co-authors
- Martin PleschMarcus HuberMehul MalikJan BoudaNicolai FriisWill McCutcheonMartin BohmannSebastian Philipp Neumann
- Topics
- Quantum Information and Cryptography (21 papers)Quantum Mechanics and Applications (17 papers)Quantum Computing Algorithms and Architecture (14 papers)
In The Last Decade
Matej Pivoluska
23 papers receiving 344 citations
Peers
Comparison fields: 5 of 33
- Artificial Intelligence 317
- Atomic and Molecular Physics, and Optics 272
- Computer Vision and Pattern Recognition 34
- Computational Theory and Mathematics 33
- Electrical and Electronic Engineering 31
Countries citing papers authored by Matej Pivoluska
This map shows the geographic impact of Matej Pivoluska'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 Matej Pivoluska with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matej Pivoluska more than expected).
Fields of papers citing papers by Matej Pivoluska
This network shows the impact of papers produced by Matej Pivoluska. 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 Matej Pivoluska. The network helps show where Matej Pivoluska may publish in the future.
Co-authorship network of co-authors of Matej Pivoluska
This figure shows the co-authorship network connecting the top 25 collaborators of Matej Pivoluska. A scholar is included among the top collaborators of Matej Pivoluska 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 Matej Pivoluska. Matej Pivoluska 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 | 1 | |
| 3 | 2 | |
| 4 | 13 | |
| 5 | 28 | |
| 6 | 9 | |
| 7 | 17 | |
| 8 | 13 | |
| 9 | 8 | |
| 10 | 11 | |
| 11 | 36 | |
| 12 | 40 | |
| 13 | 58 | |
| 14 | 36 | |
| 15 | Two measurements are sufficient for certifying high-dimensional entanglement | 1 |
| 16 | 2 | |
| 17 | Device Independent Random Number Generation | 4 |
| 18 | 8 | |
| 19 | 2 | |
| 20 | 40 |
About Matej Pivoluska
Matej Pivoluska is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Computational Theory and Mathematics, having authored 24 papers that have together received 352 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (21 papers), Quantum Mechanics and Applications (17 papers) and Quantum Computing Algorithms and Architecture (14 papers). The work is most often cited by research in Acoustics and Ultrasonics (12 citations), Artificial Intelligence (317 citations) and Atomic and Molecular Physics, and Optics (272 citations). Matej Pivoluska has collaborated with scholars based in Slovakia, Czechia and Austria. Frequent co-authors include Martin Plesch, Marcus Huber, Mehul Malik, Jan Bouda, Nicolai Friis, Will McCutcheon, Martin Bohmann, Sebastian Philipp Neumann, Rupert Ursin and Natalia Herrera Valencia. Their work appears in journals such as Physical Review Letters, 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.