Rickard Ewetz

729 citations
76 papers · 486 · h-index 10

Impact in

Papers in

    • Advanced Memory and Neural Computing 34
    • Ferroelectric and Negative Capacitance Devices 30
    • Low-power high-performance VLSI design 19
    • VLSI and FPGA Design Techniques 18
    • Semiconductor materials and devices 14
    • Adversarial Robustness in Machine Learning 7

Rickard Ewetz

67 papers receiving 475 citations

Peers

Rickard Ewetz
Comparison fields: 5 of 39
  • Hardware and Architecture 89
  • Electrical and Electronic Engineering 366
  • Artificial Intelligence 136
  • Computer Vision and Pattern Recognition 72
  • Cellular and Molecular Neuroscience 55
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Citations per field
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Citations per year

Countries citing papers authored by Rickard Ewetz

Since Specialization
Citations

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

Fields of papers citing papers by Rickard Ewetz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 76 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019111
2 201934
3 201932
4 202030
5 202122
6 202216
7 202112
8 201911
9 202211
10 20179
11 20228
12 20157
13 20227
14 20187
15 20237
16 20216
17 20216
18 20166
19 20176
20 20216

About Rickard Ewetz

Rickard Ewetz is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Hardware and Architecture, Computer Networks and Communications and Cellular and Molecular Neuroscience, having authored 76 papers that have together received 486 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (34 papers), Ferroelectric and Negative Capacitance Devices (30 papers), Low-power high-performance VLSI design (19 papers), VLSI and FPGA Design Techniques (18 papers), Semiconductor materials and devices (14 papers), Parallel Computing and Optimization Techniques (10 papers), VLSI and Analog Circuit Testing (8 papers) and Adversarial Robustness in Machine Learning (7 papers). The work is most often cited by research in Hardware and Architecture (89 citations), Electrical and Electronic Engineering (366 citations), Artificial Intelligence (136 citations), Computer Vision and Pattern Recognition (72 citations) and Cellular and Molecular Neuroscience (55 citations). Rickard Ewetz has collaborated with scholars based in United States, Taiwan and Canada. Frequent co-authors include Sumit Kumar Jha, Deliang Fan, Cheng‐Kok Koh, Zhezhi He, Jie Lin, J.S. Yuan, Fan Yao, Amro Awad, Alvaro Velasquez and Susmit Jha. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, ACM Transactions on Design Automation of Electronic Systems, IEEE Micro, IEEE Computer Architecture Letters and Neural Processing Letters.

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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