Leonardo Novo
- Artificial Intelligence top 5%
- Quantum Information and Cryptography 14
- Quantum Computing Algorithms and Architecture 12
- Neural Networks and Reservoir Computing 4
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- Quantum-Dot Cellular Automata 5
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- Quantum Mechanics and Applications 4
- Quantum and electron transport phenomena 3
- Atomic and Subatomic Physics Research 1
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- Optical Network Technologies 1
- Co-authors
- Shantanav ChakrabortyYasser OmarAndris AmbainisJérémie RolandOtfried GühneTobias MoroderFabio SciarrinoCarlos A. H. Fernandes
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsAtomic and Molecular Physics, and Optics
- Partner nations
- PortugalBelgiumUnited States
In The Last Decade
Leonardo Novo
15 papers receiving 334 citations
Peers
Comparison fields: 5 of 29
- Artificial Intelligence 318
- Computational Theory and Mathematics 87
- Atomic and Molecular Physics, and Optics 167
- Statistical and Nonlinear Physics 23
- Acoustics and Ultrasonics 1
Countries citing papers authored by Leonardo Novo
This map shows the geographic impact of Leonardo Novo'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 Leonardo Novo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leonardo Novo more than expected).
Fields of papers citing papers by Leonardo Novo
This network shows the impact of papers produced by Leonardo Novo. 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 Leonardo Novo. The network helps show where Leonardo Novo may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Leonardo Novo, 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 | 2024 | 15 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 11 | |
| 6 | 2022 | 40 | |
| 7 | 2021 | 8 | |
| 8 | 2021 | 2 | |
| 9 | 2020 | 15 | |
| 10 | 2020 | 25 | |
| 11 | 2018 | 9 | |
| 12 | 2017 | 34 | |
| 13 | 2017 | 18 | |
| 14 | 2017 | 8 | |
| 15 | 2016 | 117 | |
| 16 | 2013 | 40 |
About Leonardo Novo
Leonardo Novo is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Instrumentation, having authored 16 papers that have together received 344 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (14 papers), Quantum Computing Algorithms and Architecture (12 papers), Quantum-Dot Cellular Automata (5 papers), Neural Networks and Reservoir Computing (4 papers), Quantum Mechanics and Applications (4 papers), Quantum and electron transport phenomena (3 papers), Atomic and Subatomic Physics Research (1 paper) and Optical Network Technologies (1 paper). The work is most often cited by research in Artificial Intelligence (318 citations), Computational Theory and Mathematics (87 citations) and Atomic and Molecular Physics, and Optics (167 citations). Leonardo Novo has collaborated with scholars based in Portugal, Belgium and United States. Frequent co-authors include Shantanav Chakraborty, Yasser Omar, Andris Ambainis, Jérémie Roland, Otfried Gühne, Tobias Moroder, Fabio Sciarrino, Carlos A. H. Fernandes, Sofia Ribeiro and Ernesto F. Galvão. Their work appears in journals such as Physical Review Letters, Nature Photonics 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.