Daniel Münch

1.2k citations
32 papers · 736 indexed · h-index 14

Impact in

Papers in

Daniel Münch

29 papers receiving 727 citations

Peers

Daniel Münch
Comparison fields: 5 of 92
  • Sensory Systems 181
  • Cellular and Molecular Neuroscience 449
  • Insect Science 262
  • Ecology, Evolution, Behavior and Systematics 170
  • Genetics 223
Replace Carlotta Martelli with:
Carlotta Martelli Germany
Anna Maria Liscia Italy
Javier Pérez-Orive Mexico
Vikas Bhandawat United States
Bradley Akitake United States
Abu Farhan Germany
Antonia Strutz Germany
Shimaa A. M. Ebrahim United States
Gautam Reddy United States
Gonzalo Budelli United States
Daniel Münch relative to Carlotta Martelli Germany Carlotta Martelli's profile →
Citations per field
00.5×3.2×
Carlotta Martelli · 1×
Citations per year

Countries citing papers authored by Daniel Münch

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Münch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016159
2 2018104
3 201467
4 201067
5 201340
6 200936
7 201930
8 201030
9 202328
10 202221
11 201718
12 201317
13 201616
14 201015
15
Temporal Separation for Hardware-Based I/O Virtualization for Mixed-Criticality Embedded Real-Time Systems Using PCIe SR-IOV
201412
16 201012
17 201712
18 20157
19 20177
20 20137

About Daniel Münch

Daniel Münch is a scholar working on Sensory Systems, Hardware and Architecture, Cellular and Molecular Neuroscience, Insect Science and Ecology, Evolution, Behavior and Systematics, having authored 32 papers that have together received 736 indexed citations. Recurring topics across this work include Neurobiology and Insect Physiology Research (17 papers), Insect and Arachnid Ecology and Behavior (7 papers), Olfactory and Sensory Function Studies (7 papers), Real-Time Systems Scheduling (7 papers), Embedded Systems Design Techniques (5 papers), Plant and animal studies (4 papers), Radiation Effects in Electronics (4 papers) and Animal Behavior and Reproduction (3 papers). The work is most often cited by research in Sensory Systems (181 citations), Cellular and Molecular Neuroscience (449 citations), Insect Science (262 citations), Ecology, Evolution, Behavior and Systematics (170 citations) and Genetics (223 citations). Daniel Münch has collaborated with scholars based in Germany, Portugal and United Kingdom. Frequent co-authors include C. Giovanni Galizia, Carlos Ribeiro, Martin Strauch, Ana F. Silbering, Gro V. Amdam, Florian Wolschin, Matthias Worgull, Michael Paulitsch, Alexander Kolew and Andreas Herkersdorf. Their work appears in journals such as Microsystem Technologies, Scientific Reports, Chemical Senses, Nature and Nature Communications.

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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