Salvatore Candido
- Molecular Biology top 5%
- Structural Biology top 10%
- Microbiology top 5%
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- Meteorological Phenomena and Simulations 5
- Atmospheric Ozone and Climate 3
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- Reinforcement Learning in Robotics 4
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- Robotic Path Planning Algorithms 3
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- Atmospheric and Environmental Gas Dynamics 3
- Climate variability and models 2
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- Optimization and Search Problems 2
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- Robotic Locomotion and Control 2
- Co-authors
- Roshan RaoAllan dos Santos CostaRobert VerkuilMaryam Fazel-ZarandiAlexander RivesZeming LinZhongkai ZhuNikita Smetanin
- Journals
- Journal of Geophysical Research Atmospheres (2 papers)Quarterly Journal of the Royal Meteorological Society (1 paper)Science (1 paper)
- Partner nations
- United StatesSouth KoreaNetherlands
In The Last Decade
Salvatore Candido
17 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 152
- Molecular Biology 1.6k
- Computational Theory and Mathematics 347
- Structural Biology 18
- Microbiology 71
- Health Informatics 11
Countries citing papers authored by Salvatore Candido
This map shows the geographic impact of Salvatore Candido'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 Salvatore Candido with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Salvatore Candido more than expected).
Fields of papers citing papers by Salvatore Candido
This network shows the impact of papers produced by Salvatore Candido. 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 Salvatore Candido. The network helps show where Salvatore Candido may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Salvatore Candido, 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 | Evolutionary-scale prediction of atomic-level protein structure with a language modelbreakdown → | 2023 | 1968 |
| 2 | 2023 | 90 | |
| 3 | 2022 | 7 | |
| 4 | 2020 | 164 | |
| 5 | 2020 | 10 | |
| 6 | 2019 | 11 | |
| 7 | Lower-Stratosphere Wind Predictions with an Analog Ensemble | 2018 | 1 |
| 8 | 2017 | 25 | |
| 9 | 2012 | 6 | |
| 10 | 2012 | 40 | |
| 11 | 2011 | 17 | |
| 12 | 2011 | 24 | |
| 13 | 2010 | 19 | |
| 14 | 2010 | 9 | |
| 15 | 2009 | 1 | |
| 16 | 2008 | 18 | |
| 17 | 2007 | 19 |
About Salvatore Candido
Salvatore Candido is a scholar working on Atmospheric Science, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 17 papers that have together received 2.4k indexed citations. Recurring topics across this work include Meteorological Phenomena and Simulations (5 papers), Reinforcement Learning in Robotics (4 papers), Robotic Path Planning Algorithms (3 papers), Atmospheric Ozone and Climate (3 papers), Atmospheric and Environmental Gas Dynamics (3 papers), Optimization and Search Problems (2 papers), Climate variability and models (2 papers) and Robotic Locomotion and Control (2 papers). The work is most often cited by research in Molecular Biology (1.6k citations), Computational Theory and Mathematics (347 citations) and Structural Biology (18 citations). Salvatore Candido has collaborated with scholars based in United States, South Korea and Netherlands. Frequent co-authors include Roshan Rao, Allan dos Santos Costa, Robert Verkuil, Maryam Fazel-Zarandi, Alexander Rives, Zeming Lin, Zhongkai Zhu, Nikita Smetanin, Tom Sercu and Halil Akin. Their work appears in journals such as Journal of Geophysical Research Atmospheres, Quarterly Journal of the Royal Meteorological Society, Science, IEEE Transactions on Robotics and Nature.
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.