Markus Happe

547 citations
24 papers · 436 · h-index 13

Impact in

Papers in

Markus Happe

23 papers receiving 428 citations

Peers

Markus Happe
Comparison fields: 5 of 25
  • Hardware and Architecture 263
  • Artificial Intelligence 80
  • Computer Vision and Pattern Recognition 45
  • Computer Networks and Communications 42
  • Information Systems 42
Replace Tolga Arul with:
Tolga Arul Germany
Cheol-Hoon Lee South Korea
Bettina Schnor Germany
Jaekyu Lee United States
Jon Inouye United States
Sam Davis United States
Maurício Breternitz United States
R. Katti United States
Ilias Giechaskiel United States
Barbara Hohlt United States
Markus Happe relative to Tolga Arul Germany Tolga Arul's profile →
Citations per field
00.5×10×20×30×43.5×
Tolga Arul · 1×
Citations per year

Countries citing papers authored by Markus Happe

Since Specialization
Citations

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

Fields of papers citing papers by Markus Happe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Markus Happe, 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 Happe Line = papers co-authored together Markus Happe links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201391
2 201542
3 201540
4 201139
5 201137
6 201830
7 201226
8 201719
9 201218
10 201417
11 201315
12 201414
13 201313
14 20149
15 20097
16 20094
17 20154
18 20153
19
Hardware/Software Platform for Self-aware Compute Nodes
20122
20 20162

About Markus Happe

Markus Happe is a scholar working on Hardware and Architecture, Computer Networks and Communications, Artificial Intelligence, Information Systems and Signal Processing, having authored 24 papers that have together received 436 indexed citations. Recurring topics across this work include Embedded Systems Design Techniques (15 papers), Software-Defined Networks and 5G (4 papers), VLSI and FPGA Design Techniques (3 papers), Internet Traffic Analysis and Secure E-voting (3 papers), Physical Unclonable Functions (PUFs) and Hardware Security (3 papers), Advanced Software Engineering Methodologies (3 papers), Privacy, Security, and Data Protection (2 papers) and Network Security and Intrusion Detection (2 papers). The work is most often cited by research in Hardware and Architecture (263 citations), Artificial Intelligence (80 citations), Computer Vision and Pattern Recognition (45 citations), Computer Networks and Communications (42 citations) and Information Systems (42 citations). Markus Happe has collaborated with scholars based in Switzerland, Germany and United States. Frequent co-authors include Christian Plessl, Marco Platzner, Enno Lübbers, Vincent Lenders, Andreas Traber, Bernhard Plattner, Laurent Vanbever, Bernhard Ager, Stephan Neuhaus and Yujiao Huang. Their work appears in journals such as IEEE Micro, ACM Transactions on Reconfigurable Technology and Systems, ACM SIGCOMM Computer Communication Review, Lecture notes in computer science and Natural computing series.

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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