Markus Neher

51 papers receiving 560 citations

Peers

Markus Neher
Comparison fields: 5 of 85
  • Theoretical Computer Science 16
  • Numerical Analysis 64
  • Reproductive Medicine 76
  • Computational Theory and Mathematics 166
  • Biotechnology 82
Replace Takeyuki Tamura with:
Takeyuki Tamura Japan
Bl. Sendov Bulgaria
Sarika Jain India
Onur Sumer Canada
Shouhua Wang China
Fabian Fröhlich Germany
Cangzhi Jia China
Daming Zhu China
Tzu-Yi Chen United States
Marcus Oswald Germany
Markus Neher relative to Takeyuki Tamura Japan Takeyuki Tamura's profile →
Citations per field
00.5×10×15×21.3×
Takeyuki Tamura · 1×
Citations per year

Countries citing papers authored by Markus Neher

Since Specialization
Citations

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

Fields of papers citing papers by Markus Neher

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Markus Neher, 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 Markus Neher Line = papers co-authored together Markus Neher links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996181
2 200794
3 200183
4 200638
5 200537
6 200724
7 199913
8 200112
9 202310
10 200910
11 20039
12 19949
13 20019
14 20038
15 20047
16 20066
17 19754
18 19934
19 20013
20 20063

About Markus Neher

Markus Neher is a scholar working on Computational Theory and Mathematics, Computational Mechanics, Mechanical Engineering, Numerical Analysis and Signal Processing, having authored 56 papers that have together received 598 indexed citations. Recurring topics across this work include Numerical Methods and Algorithms (14 papers), Physics and Engineering Research Articles (10 papers), Engineering and Materials Science Studies (9 papers), Numerical methods for differential equations (7 papers), Polynomial and algebraic computation (7 papers), Digital Filter Design and Implementation (6 papers), Advanced Mathematical Modeling in Engineering (3 papers) and Model Reduction and Neural Networks (3 papers). The work is most often cited by research in Theoretical Computer Science (16 citations), Numerical Analysis (64 citations), Reproductive Medicine (76 citations), Computational Theory and Mathematics (166 citations) and Biotechnology (82 citations). Markus Neher has collaborated with scholars based in Germany, United States and France. Frequent co-authors include Kenneth R. Jackson, Nedialko S. Nedialkov, J. E. Fry, Michael Fromm, Yuhang Wan, Charles Armstrong, Guanqiong Ye, Martin Sillem, B. Runnebaum and S. Prifti. Their work appears in journals such as Applied Mathematics and Computation, Computing, ACM Transactions on Mathematical Software, BIT Numerical Mathematics and European Journal of Obstetrics & Gynecology and Reproductive Biology.

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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