Daniel Ruprecht

882 citations
52 papers · 613 · h-index 13

Impact in

Papers in

Daniel Ruprecht

47 papers receiving 577 citations

Peers

Daniel Ruprecht
Comparison fields: 5 of 57
  • Numerical Analysis 151
  • Computational Mechanics 327
  • Hardware and Architecture 114
  • Computational Theory and Mathematics 149
  • Statistical and Nonlinear Physics 64
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Citations per year

Countries citing papers authored by Daniel Ruprecht

Since Specialization
Citations

This map shows the geographic impact of Daniel Ruprecht'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 Ruprecht with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Ruprecht more than expected).

Fields of papers citing papers by Daniel Ruprecht

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Ruprecht. 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 Ruprecht. The network helps show where Daniel Ruprecht may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Ruprecht, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Ruprecht Line = papers co-authored together Daniel Ruprecht links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015105
2 201458
3 201254
4 201844
5 201240
6 201538
7 201426
8 201622
9 201519
10 201417
11 202314
12 200813
13
Numerical simulation of skin transport using Parareal
201513
14 201412
15 201512
16 201812
17 201610
18 20109
19 20178
20 20188

About Daniel Ruprecht

Daniel Ruprecht is a scholar working on Numerical Analysis, Hardware and Architecture, Computational Mechanics, Statistical and Nonlinear Physics and Computational Theory and Mathematics, having authored 52 papers that have together received 613 indexed citations. Recurring topics across this work include Advanced Numerical Methods in Computational Mathematics (18 papers), Parallel Computing and Optimization Techniques (16 papers), Numerical methods for differential equations (16 papers), Computational Fluid Dynamics and Aerodynamics (8 papers), Model Reduction and Neural Networks (7 papers), Matrix Theory and Algorithms (6 papers), Meteorological Phenomena and Simulations (4 papers) and Differential Equations and Numerical Methods (3 papers). The work is most often cited by research in Numerical Analysis (151 citations), Computational Mechanics (327 citations), Hardware and Architecture (114 citations), Computational Theory and Mathematics (149 citations) and Statistical and Nonlinear Physics (64 citations). Daniel Ruprecht has collaborated with scholars based in Germany, Switzerland and United Kingdom. Frequent co-authors include Rolf Krause, Robert Speck, Matthew Emmett, Michael L. Minion, Matthias Bolten, Rupert Klein, P. Gibbon, Andrea Arteaga, Andreas Naumann and Thibaut Lunet. Their work appears in journals such as SIAM Journal on Scientific Computing, Lecture notes in computational science and engineering, Computer Physics Communications, Computers & Fluids and Meteorologische Zeitschrift.

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.

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