M. Pettee
Impact in
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- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Particle Detector Development and Performance
- Quantum Chromodynamics and Particle Interactions
- Astrophysics and Cosmic Phenomena
- Neutrino Physics Research
Papers in
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- Particle physics theoretical and experimental studies 4
- Neutrino Physics Research 1
- Particle Detector Development and Performance 1
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- Advanced Vision and Imaging 1
- Video Surveillance and Tracking Methods 1
- Co-authors
- Benjamin Nachman (4 shared papers)V. M. Mikuni (2 shared papers)David Shih (2 shared papers)Gregor Kasieczka (1 shared paper)Liam Parker (2 shared papers)Michael Eickenberg (2 shared papers)Alberto Bietti (2 shared papers)Géraud Krawezik (2 shared papers)
- Journals
- Monthly Notices of the Royal Astronomical Society (2 papers)Physical review. D (2 papers)Journal of High Energy Physics (1 paper)Journal of Instrumentation (1 paper)HAL (Le Centre pour la Communication Scientifique Directe) (1 paper)
- Partner nations
- United StatesCanadaFrance
In The Last Decade
M. Pettee
6 papers receiving 103 citations
Peers
Comparison fields: 5 of 41
- Nuclear and High Energy Physics 59
- Instrumentation 5
- Artificial Intelligence 34
- Health Informatics 1
- Astronomy and Astrophysics 12
Countries citing papers authored by M. Pettee
This map shows the geographic impact of M. Pettee'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 M. Pettee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Pettee more than expected).
Fields of papers citing papers by M. Pettee
This network shows the impact of papers produced by M. Pettee. 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 M. Pettee. The network helps show where M. Pettee may publish in the future.
Co-authors
The 19 scholars most cited alongside M. Pettee, 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 | 2023 | 48 | |
| 2 | 2024 | 27 | |
| 3 | 2023 | 16 | |
| 4 | 2024 | 10 | |
| 5 | 2023 | 6 | |
| 6 | 2023 | 5 | |
| 7 | 2024 | 0 |
About M. Pettee
M. Pettee is a scholar working on Nuclear and High Energy Physics, Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology and Astronomy and Astrophysics, having authored 7 papers that have together received 112 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (4 papers), Computational Physics and Python Applications (2 papers), Advanced Vision and Imaging (1 paper), Neutrino Physics Research (1 paper), Fractal and DNA sequence analysis (1 paper), Video Surveillance and Tracking Methods (1 paper), Gaussian Processes and Bayesian Inference (1 paper) and Particle Detector Development and Performance (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (59 citations), Instrumentation (5 citations), Artificial Intelligence (34 citations), Health Informatics (1 citation) and Astronomy and Astrophysics (12 citations). M. Pettee has collaborated with scholars based in United States, Canada and France. Frequent co-authors include Benjamin Nachman, V. M. Mikuni, David Shih, Gregor Kasieczka, Liam Parker, Michael Eickenberg, Alberto Bietti, Géraud Krawezik, Michael T. McCabe and Siavash Golkar. Their work appears in journals such as Monthly Notices of the Royal Astronomical Society, Physical review. D, Journal of High Energy Physics, Journal of Instrumentation 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.