M. Rieger

45.8k citations
19 papers · 68 · h-index 5

Impact in

    • Particle physics theoretical and experimental studies
    • Particle Detector Development and Performance
    • High-Energy Particle Collisions Research
    • Quantum Chromodynamics and Particle Interactions
    • Dark Matter and Cosmic Phenomena
    • Scientific Computing and Data Management

Papers in

M. Rieger

11 papers receiving 67 citations

Peers

M. Rieger
Comparison fields: 5 of 21
  • Nuclear and High Energy Physics 49
  • Information Systems and Management 11
  • Artificial Intelligence 26
  • Computer Networks and Communications 13
  • Hardware and Architecture 3
Replace G. Dezoort with:
G. Dezoort United States
M. S. Neubauer United States
P. Harris United States
N. V. Tran United States
P. Musella Portugal
C. Biscarat France
P. Wittich United States
F. Carena Switzerland
G. H. Stark United States
J. Steggemann Germany
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Citations per field
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Citations per year

Countries citing papers authored by M. Rieger

Since Specialization
Citations

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

Fields of papers citing papers by M. Rieger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 201932
2 201712
3 20205
4 20175
5
A development environment for visual physics analysis
20164
6 20143
7 20153
8 20191
9 20211
10 20161
11 20121
12 20200
13 20140
14 20170
15 20240
16 20180
17 20120
18 20210
19 20190

About M. Rieger

M. Rieger is a scholar working on Computer Networks and Communications, Nuclear and High Energy Physics, Information Systems and Management, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 19 papers that have together received 68 indexed citations. Recurring topics across this work include Particle Detector Development and Performance (10 papers), Distributed and Parallel Computing Systems (9 papers), Scientific Computing and Data Management (8 papers), Particle physics theoretical and experimental studies (7 papers), Advanced Data Storage Technologies (5 papers), Computational Physics and Python Applications (4 papers), Data Visualization and Analytics (2 papers) and High-Energy Particle Collisions Research (2 papers). The work is most often cited by research in Nuclear and High Energy Physics (49 citations), Information Systems and Management (11 citations), Artificial Intelligence (26 citations), Computer Networks and Communications (13 citations) and Hardware and Architecture (3 citations). M. Rieger has collaborated with scholars based in Germany, Switzerland and Belgium. Frequent co-authors include M. Erdmann, Elena Geiser, Y. Rath, Christian Gläser, Yannik Rath, D. Noll, J. Steggemann, M. Komm, G. Müller and M. Urban. Their work appears in journals such as Journal of Instrumentation, Nuclear and Particle Physics Proceedings, Journal of Physics Conference Series, RWTH Publications (RWTH Aachen) and Springer theses.

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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