Omar Eldash
- Hardware and Architecture top 5%
- VLSI and Analog Circuit Testing 7
- Embedded Systems Design Techniques 6
- Artificial Intelligence top 10%
- Neural Networks and Applications 6
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- Advanced Neural Network Applications 8
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- Advanced Memory and Neural Computing 9
- CCD and CMOS Imaging Sensors 8
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- Neuroscience and Neural Engineering 5
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- Interconnection Networks and Systems 4
- Co-authors
- Magdy BayoumiKasem KhalilAshok KumarBappaditya DeyCatherine E. GravesJim IgnowskiLei ZhaoPaolo Faraboschi
- Journals
- IEEE Transactions on Very Large Scale Integration (VLSI) Systems (1 paper)IEEE Transactions on Circuits & Systems II Express Briefs (1 paper)IEEE Transactions on Circuits and Systems I Regular Papers (1 paper)
- Partner nations
- United StatesBelgiumIsrael
In The Last Decade
Omar Eldash
23 papers receiving 395 citations
Peers
Comparison fields: 5 of 71
- Hardware and Architecture 82
- Artificial Intelligence 146
- Computer Vision and Pattern Recognition 85
- Electrical and Electronic Engineering 206
- Software 9
Countries citing papers authored by Omar Eldash
This map shows the geographic impact of Omar Eldash'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 Omar Eldash with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Omar Eldash more than expected).
Fields of papers citing papers by Omar Eldash
This network shows the impact of papers produced by Omar Eldash. 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 Omar Eldash. The network helps show where Omar Eldash may publish in the future.
Co-authorship network
The 14 scholars most cited alongside Omar Eldash, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 1 | |
| 6 | 2022 | 49 | |
| 7 | 2021 | 3 | |
| 8 | 2020 | 6 | |
| 9 | 2020 | 81 | |
| 10 | 2020 | 5 | |
| 11 | 2020 | 36 | |
| 12 | 2019 | 11 | |
| 13 | 2019 | 63 | |
| 14 | 2019 | 9 | |
| 15 | 2019 | 2 | |
| 16 | 2018 | 34 | |
| 17 | 2018 | 10 | |
| 18 | 2017 | 11 | |
| 19 | 2017 | 1 | |
| 20 | 2017 | 13 |
About Omar Eldash
Omar Eldash is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 26 papers that have together received 405 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (9 papers), CCD and CMOS Imaging Sensors (8 papers), Advanced Neural Network Applications (8 papers), VLSI and Analog Circuit Testing (7 papers), Neural Networks and Applications (6 papers), Embedded Systems Design Techniques (6 papers), Neuroscience and Neural Engineering (5 papers) and Interconnection Networks and Systems (4 papers). The work is most often cited by research in Hardware and Architecture (82 citations), Artificial Intelligence (146 citations) and Computer Vision and Pattern Recognition (85 citations). Omar Eldash has collaborated with scholars based in United States, Belgium and Israel. Frequent co-authors include Magdy Bayoumi, Kasem Khalil, Ashok Kumar, Bappaditya Dey, Ashok Kumar, Catherine E. Graves, Jim Ignowski, Lei Zhao, Paolo Faraboschi and Ron M. Roth. Their work appears in journals such as IEEE Transactions on Very Large Scale Integration (VLSI) Systems, IEEE Transactions on Circuits & Systems II Express Briefs, IEEE Transactions on Circuits and Systems I Regular Papers, IEEE Transactions on Biomedical Circuits and Systems and SHILAP Revista de lepidopterología.
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.