Sofiène Jerbi
Impact in
- Artificial Intelligence top 5%
- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Neural Networks and Reservoir Computing
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- Quantum Mechanics and Applications
- Quantum many-body systems
- Quantum and electron transport phenomena
Papers in
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- Quantum Computing Algorithms and Architecture 9
- Quantum Information and Cryptography 9
- Neural Networks and Reservoir Computing 3
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- Quantum Mechanics and Applications 3
- Quantum many-body systems 2
- Quantum and electron transport phenomena 1
- Co-authors
- Vedran Dunjko (5 shared papers)Andrea Skolik (1 shared paper)Hans J. Briegel (6 shared papers)Hendrik Poulsen Nautrup (5 shared papers)Jonas M. Kübler (1 shared paper)Thomas Bäck (1 shared paper)Raban Iten (1 shared paper)Henrik Wilming (1 shared paper)
- Journals
- Quantum (3 papers)Nature Communications (2 papers)EPJ Quantum Technology (1 paper)Machine Learning Science and Technology (1 paper)Physical review. A (1 paper)
- Partner nations
- AustriaGermanyNetherlands
In The Last Decade
Sofiène Jerbi
10 papers receiving 278 citations
Sofiène Jerbi's Hit Papers
Peers
Comparison fields: 5 of 40
- Artificial Intelligence 255
- Atomic and Molecular Physics, and Optics 71
- Computational Theory and Mathematics 34
- Acoustics and Ultrasonics 1
- Hardware and Architecture 6
Countries citing papers authored by Sofiène Jerbi
This map shows the geographic impact of Sofiène Jerbi'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 Sofiène Jerbi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sofiène Jerbi more than expected).
Fields of papers citing papers by Sofiène Jerbi
This network shows the impact of papers produced by Sofiène Jerbi. 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 Sofiène Jerbi. The network helps show where Sofiène Jerbi may publish in the future.
Co-authors
The 19 scholars most cited alongside Sofiène Jerbi, 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 | Quantum machine learning beyond kernel methods Hit paper breakdown → | 2023 | 111 |
| 2 | 2022 | 108 | |
| 3 | 2024 | 33 | |
| 4 | 2022 | 10 | |
| 5 | 2024 | 7 | |
| 6 | 2021 | 7 | |
| 7 | 2024 | 5 | |
| 8 | 2025 | 4 | |
| 9 | 2020 | 2 | |
| 10 | 2024 | 2 | |
| 11 | 2025 | 0 |
About Sofiène Jerbi
Sofiène Jerbi is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering, Computational Theory and Mathematics and Management Science and Operations Research, having authored 11 papers that have together received 289 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (9 papers), Quantum Information and Cryptography (9 papers), Neural Networks and Reservoir Computing (3 papers), Quantum Mechanics and Applications (3 papers), Quantum many-body systems (2 papers), Quantum and electron transport phenomena (1 paper), Computability, Logic, AI Algorithms (1 paper) and Low-power high-performance VLSI design (1 paper). The work is most often cited by research in Artificial Intelligence (255 citations), Atomic and Molecular Physics, and Optics (71 citations), Computational Theory and Mathematics (34 citations), Acoustics and Ultrasonics (1 citation) and Hardware and Architecture (6 citations). Sofiène Jerbi has collaborated with scholars based in Austria, Germany and Netherlands. Frequent co-authors include Vedran Dunjko, Andrea Skolik, Hans J. Briegel, Hendrik Poulsen Nautrup, Jonas M. Kübler, Thomas Bäck, Raban Iten, Henrik Wilming, Felix Motzoi and Elies Gil-Fuster. Their work appears in journals such as Quantum, Nature Communications, EPJ Quantum Technology, Machine Learning Science and Technology and Physical review. A.
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.