Ilya Sinayskiy
- Artificial Intelligence top 0.5%
- Atomic and Molecular Physics, and Optics top 5%
- Computational Theory and Mathematics top 2%
- Statistical and Nonlinear Physics top 2%
- Electrical and Electronic Engineering
- Co-authors
- Francesco PetruccioneMaria SchuldC. L. LatuneRyan SwekeStéphane AttalChristophe SabotAnban PillayRienk van Grondelle
- Topics
- Quantum Information and Cryptography (46 papers)Quantum Computing Algorithms and Architecture (38 papers)Spectroscopy and Quantum Chemical Studies (12 papers)
- Cited by
- Artificial IntelligenceAtomic and Molecular Physics, and OpticsStatistical and Nonlinear Physics
- Journals
- Physical Review LettersSHILAP Revista de lepidopterologíaScientific Reports
- Partner nations
- South AfricaSouth KoreaUnited Kingdom
In The Last Decade
Ilya Sinayskiy
60 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 119
- Artificial Intelligence 1.5k
- Atomic and Molecular Physics, and Optics 881
- Computational Theory and Mathematics 306
- Statistical and Nonlinear Physics 274
- Electrical and Electronic Engineering 127
Countries citing papers authored by Ilya Sinayskiy
This map shows the geographic impact of Ilya Sinayskiy'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 Ilya Sinayskiy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ilya Sinayskiy more than expected).
Fields of papers citing papers by Ilya Sinayskiy
This network shows the impact of papers produced by Ilya Sinayskiy. 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 Ilya Sinayskiy. The network helps show where Ilya Sinayskiy may publish in the future.
Co-authorship network of co-authors of Ilya Sinayskiy
This figure shows the co-authorship network connecting the top 25 collaborators of Ilya Sinayskiy. A scholar is included among the top collaborators of Ilya Sinayskiy based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ilya Sinayskiy. Ilya Sinayskiy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 14 | |
| 5 | 5 | |
| 6 | 1 | |
| 7 | 11 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 2 | |
| 11 | 5 | |
| 12 | 6 | |
| 13 | 8 | |
| 14 | 5 | |
| 15 | 59 | |
| 16 | 14 | |
| 17 | 146 | |
| 18 | An introduction to quantum machine learning | 254 |
| 19 | 96 | |
| 20 | 36 |
About Ilya Sinayskiy
Ilya Sinayskiy is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Statistical and Nonlinear Physics, having authored 62 papers that have together received 2.0k indexed citations. Recurring topics across this work include Quantum Information and Cryptography (46 papers), Quantum Computing Algorithms and Architecture (38 papers) and Spectroscopy and Quantum Chemical Studies (12 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), Atomic and Molecular Physics, and Optics (881 citations) and Statistical and Nonlinear Physics (274 citations). Ilya Sinayskiy has collaborated with scholars based in South Africa, South Korea and United Kingdom. Frequent co-authors include Francesco Petruccione, Maria Schuld, C. L. Latune, Ryan Sweke, Stéphane Attal, Christophe Sabot, Anban Pillay, Rienk van Grondelle, Samuel Smith and Denis Bernard. Their work appears in journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Scientific Reports.
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.