Raoul Heese
- Artificial Intelligence top 5%
- Control and Systems Engineering top 10%
- Electrical and Electronic Engineering
- Mechanical Engineering
- Statistical and Nonlinear Physics top 10%
- Co-authors
- Christian BauckhageBogdan GeorgievSven GiesselbachSebastian MayerBirgit KirschKatharina BeckhRajkumar RamamurthyJannis Schuecker
- Topics
- Quantum Computing Algorithms and Architecture (8 papers)Quantum Information and Cryptography (7 papers)Quantum Mechanics and Applications (4 papers)
- Partner nations
- GermanyFinlandUnited Kingdom
In The Last Decade
Raoul Heese
19 papers receiving 562 citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Artificial Intelligence 239
- Control and Systems Engineering 94
- Electrical and Electronic Engineering 63
- Mechanical Engineering 57
- Statistical and Nonlinear Physics 49
Countries citing papers authored by Raoul Heese
This map shows the geographic impact of Raoul Heese'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 Raoul Heese with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raoul Heese more than expected).
Fields of papers citing papers by Raoul Heese
This network shows the impact of papers produced by Raoul Heese. 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 Raoul Heese. The network helps show where Raoul Heese may publish in the future.
Co-authorship network of co-authors of Raoul Heese
This figure shows the co-authorship network connecting the top 25 collaborators of Raoul Heese. A scholar is included among the top collaborators of Raoul Heese 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 Raoul Heese. Raoul Heese 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 | 1 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 28 | |
| 8 | 8 | |
| 9 | 6 | |
| 10 | 1 | |
| 11 | 4 | |
| 12 | 4 | |
| 13 | 8 | |
| 14 | 16 | |
| 15 | Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systemsbreakdown → | 469 |
| 16 | 13 | |
| 17 | 1 | |
| 18 | 17 | |
| 19 | 3 | |
| 20 | 3 |
About Raoul Heese
Raoul Heese is a scholar working on Filtration and Separation, Computational Theory and Mathematics and Artificial Intelligence, having authored 20 papers that have together received 589 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (8 papers), Quantum Information and Cryptography (7 papers) and Quantum Mechanics and Applications (4 papers). The work is most often cited by research in Artificial Intelligence (239 citations), Health Informatics (10 citations) and Control and Systems Engineering (94 citations). Raoul Heese has collaborated with scholars based in Germany, Finland and United Kingdom. Frequent co-authors include Christian Bauckhage, Bogdan Georgiev, Sven Giesselbach, Sebastian Mayer, Birgit Kirsch, Katharina Beckh, Rajkumar Ramamurthy, Jannis Schuecker, Michał Walczak and Laura von Rueden. Their work appears in journals such as PLoS ONE, Scientific Reports and European Journal of Operational Research.
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.