T. Dorigo
Impact in
- Nuclear and High Energy Physics top 10%
- Particle physics theoretical and experimental studies
- Particle Detector Development and Performance
- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Dark Matter and Cosmic Phenomena
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- Computational Physics and Python Applications
- Gaussian Processes and Bayesian Inference
Papers in
-
- Particle physics theoretical and experimental studies 16
- Particle Detector Development and Performance 9
- High-Energy Particle Collisions Research 4
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- Radiation Detection and Scintillator Technologies 4
- Co-authors
- C. A. GottardoA. Carvalho Antunes De OliveiraM. TosiFlorian GoertzG. StrongJ. KieselerP. VischiaBruno Scarpa
In The Last Decade
T. Dorigo
19 papers receiving 124 citations
Peers
Comparison fields: 5 of 46
- Nuclear and High Energy Physics 87
- Artificial Intelligence 37
- Radiation 8
- History and Philosophy of Science 3
- Statistics and Probability 5
Countries citing papers authored by T. Dorigo
This map shows the geographic impact of T. Dorigo'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 T. Dorigo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Dorigo more than expected).
Fields of papers citing papers by T. Dorigo
This network shows the impact of papers produced by T. Dorigo. 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 T. Dorigo. The network helps show where T. Dorigo may publish in the future.
Co-authorship network
The 25 scholars most cited alongside T. Dorigo, 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 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2025 | 1 | |
| 6 | 2025 | 0 | |
| 7 | 2025 | 0 | |
| 8 | 2024 | 4 | |
| 9 | 2023 | 12 | |
| 10 | 2022 | 1 | |
| 11 | 2022 | 4 | |
| 12 | 2022 | 6 | |
| 13 | 2021 | 6 | |
| 14 | 2020 | 5 | |
| 15 | 2020 | 5 | |
| 16 | 2019 | 24 | |
| 17 | 2017 | 2 | |
| 18 | 2015 | 5 | |
| 19 | 2002 | 2 | |
| 20 | 2001 | 3 |
About T. Dorigo
T. Dorigo is a scholar working on Nuclear and High Energy Physics, Radiation, Information Systems and Management, Artificial Intelligence and Statistics and Probability, having authored 26 papers that have together received 129 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (16 papers), Particle Detector Development and Performance (9 papers), High-Energy Particle Collisions Research (4 papers), Radiation Detection and Scintillator Technologies (4 papers), Gaussian Processes and Bayesian Inference (3 papers), Computational Physics and Python Applications (3 papers), Atomic and Subatomic Physics Research (2 papers) and Advanced Statistical Methods and Models (2 papers). The work is most often cited by research in Nuclear and High Energy Physics (87 citations), Artificial Intelligence (37 citations), Radiation (8 citations), History and Philosophy of Science (3 citations) and Statistics and Probability (5 citations). T. Dorigo has collaborated with scholars based in Italy, Sweden and Germany. Frequent co-authors include C. A. Gottardo, A. Carvalho Antunes De Oliveira, M. Tosi, Florian Goertz, G. Strong, J. Kieseler, P. Vischia, Bruno Scarpa, A. Giammanco and M. Michelotto. Their work appears in journals such as Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, Journal of High Energy Physics, Nuclear Physics B, Computer Physics Communications and Smart Learning Environments.
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.