Manuel Eggimann

456 citations
16 papers · 273 · h-index 10

Impact in

Papers in

    • Advanced Memory and Neural Computing 5
    • Semiconductor materials and devices 3
    • CCD and CMOS Imaging Sensors 3
    • Advancements in Semiconductor Devices and Circuit Design 3
    • Low-power high-performance VLSI design 2
    • Advanced Sensor and Energy Harvesting Materials 2

Manuel Eggimann

16 papers receiving 260 citations

Peers

Manuel Eggimann
Comparison fields: 5 of 57
  • Human-Computer Interaction 44
  • Hardware and Architecture 40
  • Electrical and Electronic Engineering 148
  • Computer Vision and Pattern Recognition 50
  • Signal Processing 14
Replace Injoon Hong with:
Injoon Hong South Korea
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Ryotaro Taniguchi Japan
Ka-Fai Un Macao
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Luke Everson United States
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Citations per field
00.5×10×14.7×
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Citations per year

Countries citing papers authored by Manuel Eggimann

Since Specialization
Citations

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

Fields of papers citing papers by Manuel Eggimann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 202165
2 202158
3 202321
4 202120
5 201919
6 202116
7 201912
8 201911
9 202410
10 201510
11 20248
12 20236
13 20216
14 20234
15 20224
16 20253

About Manuel Eggimann

Manuel Eggimann is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Computer Vision and Pattern Recognition, Physiology and Human-Computer Interaction, having authored 16 papers that have together received 273 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (5 papers), Body Composition Measurement Techniques (3 papers), Semiconductor materials and devices (3 papers), CCD and CMOS Imaging Sensors (3 papers), Advancements in Semiconductor Devices and Circuit Design (3 papers), Advanced Sensor and Energy Harvesting Materials (2 papers), Hand Gesture Recognition Systems (2 papers) and Low-power high-performance VLSI design (2 papers). The work is most often cited by research in Human-Computer Interaction (44 citations), Hardware and Architecture (40 citations), Electrical and Electronic Engineering (148 citations), Computer Vision and Pattern Recognition (50 citations) and Signal Processing (14 citations). Manuel Eggimann has collaborated with scholars based in Switzerland, Italy and United States. Frequent co-authors include Luca Benini, Michele Magno, Philipp Mayer, Stefan Mach, Davide Rossi, Alfio Di Mauro, Abbas Rahimi, Antonio Pullini, Francesco Conti and Marco Guermandi. Their work appears in journals such as IEEE Journal of Solid-State Circuits, IEEE Sensors Journal, Sustainable Computing Informatics and Systems, IEEE Internet of Things Journal and IEEE Transactions on Circuits and Systems I Regular Papers.

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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