Salvatore Candido
- Molecular Biology top 5%
- Computational Theory and Mathematics top 2%
- Materials Chemistry
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Co-authors
- Roshan RaoAllan dos Santos CostaRobert VerkuilMaryam Fazel-ZarandiAlexander RivesZeming LinZhongkai ZhuNikita Smetanin
- Topics
- Meteorological Phenomena and Simulations (5 papers)Reinforcement Learning in Robotics (4 papers)Robotic Path Planning Algorithms (3 papers)
- 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
- Materials Chemistry 264
- Artificial Intelligence 187
- Radiology, Nuclear Medicine and Imaging 143
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 of co-authors of Salvatore Candido
This figure shows the co-authorship network connecting the top 25 collaborators of Salvatore Candido. A scholar is included among the top collaborators of Salvatore Candido 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 Salvatore Candido. Salvatore Candido is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Evolutionary-scale prediction of atomic-level protein structure with a language modelbreakdown → | 1968 |
| 2 | 90 | |
| 3 | 7 | |
| 4 | 164 | |
| 5 | 10 | |
| 6 | 11 | |
| 7 | Lower-Stratosphere Wind Predictions with an Analog Ensemble | 1 |
| 8 | 25 | |
| 9 | 6 | |
| 10 | 40 | |
| 11 | 17 | |
| 12 | 24 | |
| 13 | 19 | |
| 14 | 9 | |
| 15 | 1 | |
| 16 | 18 | |
| 17 | 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) and Robotic Path Planning Algorithms (3 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 Nature, Science and Geophysical Research Letters.
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.