Peter Zaspel
Impact in
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- Computational Drug Discovery Methods
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- Parallel Computing and Optimization Techniques
Papers in
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- Computational Drug Discovery Methods 8
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- Machine Learning in Materials Science 9
- Co-authors
- Michael Griebel (4 shared papers)Bing Huang (1 shared paper)Helmut Harbrecht (1 shared paper)O. Anatole von Lilienfeld (1 shared paper)Vivin Vinod (7 shared papers)Ulrich Kleinekathöfer (4 shared papers)Sayan Maity (1 shared paper)Vincent Heuveline (1 shared paper)
- Journals
- Machine Learning Science and Technology (3 papers)Journal of Chemical Theory and Computation (3 papers)Journal of Computational Chemistry (1 paper)Computing and Visualization in Science (1 paper)Scientific Data (1 paper)
- Partner nations
- GermanySwitzerland
In The Last Decade
Peter Zaspel
14 papers receiving 232 citations
Peers
Comparison fields: 5 of 54
- Computational Theory and Mathematics 86
- Hardware and Architecture 26
- Computational Mechanics 68
- Physical and Theoretical Chemistry 24
- Computer Graphics and Computer-Aided Design 9
Countries citing papers authored by Peter Zaspel
This map shows the geographic impact of Peter Zaspel'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 Peter Zaspel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Zaspel more than expected).
Fields of papers citing papers by Peter Zaspel
This network shows the impact of papers produced by Peter Zaspel. 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 Peter Zaspel. The network helps show where Peter Zaspel may publish in the future.
Co-authors
The 11 scholars most cited alongside Peter Zaspel, 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 | 2018 | 86 | |
| 2 | 2010 | 48 | |
| 3 | 2012 | 41 | |
| 4 | 2011 | 21 | |
| 5 | 2023 | 16 | |
| 6 | 2024 | 9 | |
| 7 | 2018 | 5 | |
| 8 | 2025 | 4 | |
| 9 | 2024 | 3 | |
| 10 | 2025 | 2 | |
| 11 | 2011 | 2 | |
| 12 | 2025 | 1 | |
| 13 | 2022 | 1 | |
| 14 | 2017 | 1 | |
| 15 | 2025 | 0 | |
| 16 | 2025 | 0 |
About Peter Zaspel
Peter Zaspel is a scholar working on Computational Theory and Mathematics, Materials Chemistry, Physical and Theoretical Chemistry, Atomic and Molecular Physics, and Optics and Computational Mechanics, having authored 16 papers that have together received 240 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (9 papers), Computational Drug Discovery Methods (8 papers), Various Chemistry Research Topics (4 papers), Advanced Numerical Methods in Computational Mathematics (2 papers), Advanced Chemical Physics Studies (2 papers), Protein Structure and Dynamics (2 papers), Computational Fluid Dynamics and Aerodynamics (2 papers) and Scientific Research and Discoveries (1 paper). The work is most often cited by research in Computational Theory and Mathematics (86 citations), Hardware and Architecture (26 citations), Computational Mechanics (68 citations), Physical and Theoretical Chemistry (24 citations) and Computer Graphics and Computer-Aided Design (9 citations). Peter Zaspel has collaborated with scholars based in Germany and Switzerland. Frequent co-authors include Michael Griebel, Bing Huang, Helmut Harbrecht, O. Anatole von Lilienfeld, Vivin Vinod, Ulrich Kleinekathöfer, Sayan Maity, Vincent Heuveline, Clayton Webster and M. Schick. Their work appears in journals such as Machine Learning Science and Technology, Journal of Chemical Theory and Computation, Journal of Computational Chemistry, Computing and Visualization in Science and Scientific Data.
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.