Martin Kumm

49 papers receiving 659 citations

Peers

Martin Kumm
Comparison fields: 5 of 43
  • Hardware and Architecture 191
  • Signal Processing 249
  • Computational Theory and Mathematics 239
  • Electrical and Electronic Engineering 433
  • Computer Vision and Pattern Recognition 113
Replace Anindya Sundar Dhar with:
Anindya Sundar Dhar India
Paulo Flores Portugal
Peter Zipf Germany
Shen‐Fu Hsiao Taiwan
Tsin‐Yuan Chang Taiwan
Yin‐Tsung Hwang Taiwan
Wonyong Sung South Korea
Ki-Il Kum South Korea
M. Torkelson Sweden
P.B. Denyer United Kingdom
Martin Kumm relative to Anindya Sundar Dhar India Anindya Sundar Dhar's profile →
Citations per field
00.5×1.5×2.1×
Anindya Sundar Dhar · 1×
Citations per year

Countries citing papers authored by Martin Kumm

Since Specialization
Citations

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

Fields of papers citing papers by Martin Kumm

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Martin Kumm, 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 Martin Kumm Line = papers co-authored together Martin Kumm links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201574
2 201048
3 201945
4 201236
5 201435
6 201532
7 201228
8 201825
9 201822
10 201320
11 201319
12
Efficient High Speed Compression Trees on Xilinx FPGAs.
201418
13 201318
14 201118
15 201718
16 200717
17 201716
18 201816
19 201915
20 201612

About Martin Kumm

Martin Kumm is a scholar working on Electrical and Electronic Engineering, Computational Theory and Mathematics, Signal Processing, Hardware and Architecture and Biomedical Engineering, having authored 52 papers that have together received 701 indexed citations. Recurring topics across this work include Low-power high-performance VLSI design (23 papers), Numerical Methods and Algorithms (21 papers), Digital Filter Design and Implementation (20 papers), Embedded Systems Design Techniques (11 papers), Analog and Mixed-Signal Circuit Design (10 papers), Parallel Computing and Optimization Techniques (7 papers), Interconnection Networks and Systems (7 papers) and VLSI and FPGA Design Techniques (6 papers). The work is most often cited by research in Hardware and Architecture (191 citations), Signal Processing (249 citations), Computational Theory and Mathematics (239 citations), Electrical and Electronic Engineering (433 citations) and Computer Vision and Pattern Recognition (113 citations). Martin Kumm has collaborated with scholars based in Germany, United States and Sweden. Frequent co-authors include Peter Zipf, Mario Garrido, Oscar Gustafsson, Harald Klingbeil, Uwe Meyer‐Baese, Chip-Hong Chang, Guillermo Botella, M. S. Sanjari, Philip H. W. Leong and David Boland. Their work appears in journals such as IEEE Transactions on Circuits & Systems II Express Briefs, IEEE Transactions on Circuits and Systems I Regular Papers, IEEE Transactions on Computers, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems and IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

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.

Explore authors with similar magnitude of impact