Daniel GroBe

441 citations
18 papers · 287 · h-index 11

Impact in

Papers in

Daniel GroBe

18 papers receiving 280 citations

Peers

Daniel GroBe
Comparison fields: 5 of 49
  • Hardware and Architecture 106
  • Computational Theory and Mathematics 150
  • Software 32
  • Electrical and Electronic Engineering 137
  • Artificial Intelligence 63
Replace Alok Jain with:
Alok Jain India
Tetsuo Yokoyama Japan
В. В. Кравец United States
Mayler G. A. Martins Brazil
V. Pitchumani United States
Hyung Ki Lee South Korea
Shuyu Guo China
Jinian Bian China
Shin’ichi Wakabayashi Japan
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Citations per field
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Citations per year

Countries citing papers authored by Daniel GroBe

Since Specialization
Citations

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

Fields of papers citing papers by Daniel GroBe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Daniel GroBe, 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 GroBe Line = papers co-authored together Daniel GroBe links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 200052
2 201636
3 200632
4 202124
5 201822
6 201817
7 200817
8 200715
9 201815
10 202111
11 201810
12 20068
13 20168
14 20197
15 20187
16 20213
17 20182
18 20191

About Daniel GroBe

Daniel GroBe is a scholar working on Computational Theory and Mathematics, Electrical and Electronic Engineering, Hardware and Architecture, Artificial Intelligence and Software, having authored 18 papers that have together received 287 indexed citations. Recurring topics across this work include Formal Methods in Verification (8 papers), Quantum-Dot Cellular Automata (5 papers), VLSI and Analog Circuit Testing (4 papers), Low-power high-performance VLSI design (4 papers), Embedded Systems Design Techniques (3 papers), Advanced Memory and Neural Computing (3 papers), Quantum Computing Algorithms and Architecture (3 papers) and Radiation Effects in Electronics (3 papers). The work is most often cited by research in Hardware and Architecture (106 citations), Computational Theory and Mathematics (150 citations), Software (32 citations), Electrical and Electronic Engineering (137 citations) and Artificial Intelligence (63 citations). Daniel GroBe has collaborated with scholars based in Germany, Austria and Switzerland. Frequent co-authors include Rolf Drechsler, Ulrich Rothe, Alexander W. Eckert, Ulrich Kühne, Alireza Mahzoon, Robert Wille, Mathias Soeken, Hoang M. Le, Marcel Walter and Vladimir Herdt. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Biomaterials, Design, Automation, and Test in Europe, Infoscience (Ecole Polytechnique Fédérale de Lausanne) and 2008 Design, Automation and Test in Europe.

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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