Stefan Kunis

35 papers receiving 775 citations

Peers

Stefan Kunis
Comparison fields: 5 of 78
  • Numerical Analysis 90
  • Computational Mathematics 9
  • Applied Mathematics 145
  • Computational Mechanics 281
  • Signal Processing 111
Replace June‐Yub Lee with:
June‐Yub Lee South Korea
Albert Fannjiang United States
Anne Gelb United States
Vladislav Voroninski United States
Jens Keiner Germany
Gerd Teschke Germany
Ronny Ramlau Austria
Shingyu Leung Hong Kong
Vicente Vidal Spain
Lucas Monzón United States
Stefan Kunis relative to June‐Yub Lee South Korea June‐Yub Lee's profile →
Citations per field
00.5×2.8×
June‐Yub Lee · 1×
Citations per year

Countries citing papers authored by Stefan Kunis

Since Specialization
Citations

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

Fields of papers citing papers by Stefan Kunis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 22 scholars most cited alongside Stefan Kunis, 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 Stefan Kunis Line = papers co-authored together Stefan Kunis links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20230
3 20231
4 202314
5 20211
6 20195
7 20174
8 20128
9 201121
10 201016
11 200921
12 200957
13 20085
14 20086
15 200727
16 200732
17 2007104
18 200739
19 200626
20 200382

About Stefan Kunis

Stefan Kunis is a scholar working on Computational Mathematics, Applied Mathematics, Numerical Analysis, Computational Mechanics and Signal Processing, having authored 40 papers that have together received 843 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (11 papers), Image and Signal Denoising Methods (9 papers), Electromagnetic Scattering and Analysis (6 papers), Mathematical Approximation and Integration (6 papers), Mathematical Analysis and Transform Methods (6 papers), Digital Filter Design and Implementation (6 papers), Advanced Numerical Analysis Techniques (5 papers) and Advanced MRI Techniques and Applications (4 papers). The work is most often cited by research in Numerical Analysis (90 citations), Computational Mathematics (9 citations), Applied Mathematics (145 citations), Computational Mechanics (281 citations) and Signal Processing (111 citations). Stefan Kunis has collaborated with scholars based in Germany, Austria and Czechia. Frequent co-authors include Daniel Potts, Jens Keiner, Holger Rauhut, Mario Bebendorf, Tobias Knopp, Manuel Gräf, Yiqiu Dong, Michael Döhler, Sabine A. E. Heider and Jörg D. Hardege. Their work appears in journals such as Applied and Computational Harmonic Analysis, SIAM Journal on Numerical Analysis, Journal of Fourier Analysis and Applications, Advances in Computational Mathematics and ACM Transactions on Mathematical Software.

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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