Andrew Vold
Impact in
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- Neutrino Physics Research
- Particle physics theoretical and experimental studies
- Astrophysics and Cosmic Phenomena
- Dark Matter and Cosmic Phenomena
- Particle Detector Development and Performance
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- Topic Modeling
Papers in
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- Neutrino Physics Research 4
- Particle physics theoretical and experimental studies 4
- Dark Matter and Cosmic Phenomena 2
- Astrophysics and Cosmic Phenomena 2
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- Topic Modeling 3
- Advanced Text Analysis Techniques 2
- Natural Language Processing Techniques 2
- Text and Document Classification Technologies 1
- Co-authors
- Frank Schilder (2 shared papers)Dezhao Song (1 shared paper)Jack G. Conrad (1 shared paper)Jinane Harmouche (1 shared paper)Frederick Klauschen (1 shared paper)Aaron L. Goldman (1 shared paper)Andreas Meyer‐Lindenberg (1 shared paper)Vincent Barra (1 shared paper)
- Journals
- Physical review. D (2 papers)Physical Review Letters (2 papers)Information Systems (1 paper)Lecture notes in computer science (1 paper)HAL (Le Centre pour la Communication Scientifique Directe) (1 paper)
- Partner nations
- United StatesFranceRussia
In The Last Decade
Andrew Vold
8 papers receiving 409 citations
Peers
Comparison fields: 5 of 36
- Nuclear and High Energy Physics 333
- Artificial Intelligence 58
- Political Science and International Relations 40
- Radiation 13
- Astronomy and Astrophysics 24
Countries citing papers authored by Andrew Vold
This map shows the geographic impact of Andrew Vold'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 Andrew Vold with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Vold more than expected).
Fields of papers citing papers by Andrew Vold
This network shows the impact of papers produced by Andrew Vold. 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 Andrew Vold. The network helps show where Andrew Vold may publish in the future.
Co-authors
The 8 scholars most cited alongside Andrew Vold, 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 | 2018 | 111 | |
| 2 | 2017 | 105 | |
| 3 | 2017 | 70 | |
| 4 | 2021 | 60 | |
| 5 | 2017 | 55 | |
| 6 | 2021 | 11 | |
| 7 | 2021 | 5 | |
| 8 | EVALUATION OF MR-BRAIN-VOLUMETRY METHODS | 2007 | 1 |
About Andrew Vold
Andrew Vold is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Political Science and International Relations, having authored 8 papers that have together received 418 indexed citations. Recurring topics across this work include Neutrino Physics Research (4 papers), Particle physics theoretical and experimental studies (4 papers), Topic Modeling (3 papers), Dark Matter and Cosmic Phenomena (2 papers), Astrophysics and Cosmic Phenomena (2 papers), Advanced Text Analysis Techniques (2 papers), Natural Language Processing Techniques (2 papers) and Text and Document Classification Technologies (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (333 citations), Artificial Intelligence (58 citations), Political Science and International Relations (40 citations), Radiation (13 citations) and Astronomy and Astrophysics (24 citations). Andrew Vold has collaborated with scholars based in United States, France and Russia. Frequent co-authors include Frank Schilder, Dezhao Song, Jack G. Conrad, Jinane Harmouche, Frederick Klauschen, Aaron L. Goldman, Andreas Meyer‐Lindenberg and Vincent Barra. Their work appears in journals such as Physical review. D, Physical Review Letters, Information Systems, Lecture notes in computer science and HAL (Le Centre pour la Communication Scientifique Directe).
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.