Daniel Dercks
Impact in
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- Particle physics theoretical and experimental studies
- Dark Matter and Cosmic Phenomena
- Neutrino Physics Research
- Particle Detector Development and Performance
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- Model-Driven Software Engineering Techniques
Papers in
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- Particle physics theoretical and experimental studies 9
- Particle Detector Development and Performance 1
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- Formal Methods in Verification 1
- Co-authors
- Krzysztof Rolbiecki (3 shared papers)Jamie Tattersall (4 shared papers)Torsten Weber (2 shared papers)Nishita Desai (3 shared papers)Jong Soo Kim (2 shared papers)Zeren Simon Wang (2 shared papers)Jonas Wittbrodt (1 shared paper)Georg Ralf Weiglein (1 shared paper)
- Journals
- Physical review. D (2 papers)Computer Physics Communications (1 paper)RWTH Publications (RWTH Aachen) (1 paper)ReIn UW (University of Warsaw) (1 paper)International Conference on High Energy Physics (ICHEP) (2 papers)
- Partner nations
- GermanySouth KoreaSpain
In The Last Decade
Daniel Dercks
9 papers receiving 547 citations
Peers
Comparison fields: 5 of 5
- Nuclear and High Energy Physics 553
- Software 2
- Information Systems and Management 3
- Astronomy and Astrophysics 2
- Artificial Intelligence 2
Countries citing papers authored by Daniel Dercks
This map shows the geographic impact of Daniel Dercks'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 Daniel Dercks with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Dercks more than expected).
Fields of papers citing papers by Daniel Dercks
This network shows the impact of papers produced by Daniel Dercks. 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 Daniel Dercks. The network helps show where Daniel Dercks may publish in the future.
Co-authors
The 23 scholars most cited alongside Daniel Dercks, 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 | 207 | |
| 2 | HiggsBounds-5: Testing Higgs Sectors in the LHC 13 TeV Era | 2020 | 188 |
| 3 | 2019 | 62 | |
| 4 | 2019 | 49 | |
| 5 | 2018 | 28 | |
| 6 | The fate of the Littlest Higgs Model with $T$-parity under 13 TeV LHC Data | 2018 | 12 |
| 7 | SCYNet: Testing supersymmetric models at the LHC with neural networks | 2017 | 5 |
| 8 | 2017 | 1 | |
| 9 | 2019 | 1 | |
| 10 | 2017 | 0 |
About Daniel Dercks
Daniel Dercks is a scholar working on Nuclear and High Energy Physics, Computational Theory and Mathematics, Oncology, Artificial Intelligence and Nuclear Energy and Engineering, having authored 10 papers that have together received 553 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (9 papers), Formal Methods in Verification (1 paper), Cancer Immunotherapy and Biomarkers (1 paper), Artificial Intelligence Applications (1 paper) and Particle Detector Development and Performance (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (553 citations), Software (2 citations), Information Systems and Management (3 citations), Astronomy and Astrophysics (2 citations) and Artificial Intelligence (2 citations). Daniel Dercks has collaborated with scholars based in Germany, South Korea and Spain. Frequent co-authors include Krzysztof Rolbiecki, Jamie Tattersall, Torsten Weber, Nishita Desai, Jong Soo Kim, Zeren Simon Wang, Jonas Wittbrodt, Georg Ralf Weiglein, Tobias Klingl and Philip Bechtle. Their work appears in journals such as Physical review. D, Computer Physics Communications, RWTH Publications (RWTH Aachen), ReIn UW (University of Warsaw) and International Conference on High Energy Physics (ICHEP).
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.