M. Campbell
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- Particle physics theoretical and experimental studies 6
- Particle Detector Development and Performance 5
- Dark Matter and Cosmic Phenomena 2
- High-Energy Particle Collisions Research 1
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- Computational Physics and Python Applications 2
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- Speech and Audio Processing 1
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- Physics of Superconductivity and Magnetism 1
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- Distributed and Parallel Computing Systems 1
- Co-authors
- B. DenbyF. BedeschiFabrizio NestiC. Edward BowersNeil ChrissC. Grosso-PilcherG. RedlingerM. J. Shochet
- Journals
- Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment (4 papers)IEEE Transactions on Nuclear Science (2 papers)International Conference on Acoustics, Speech, and Signal Processing (1 paper)
- Partner nations
- United StatesItalyIsrael
In The Last Decade
M. Campbell
6 papers receiving 44 citations
Peers
Comparison fields: 5 of 23
- Nuclear and High Energy Physics 32
- Radiation 5
- Artificial Intelligence 16
- Hardware and Architecture 2
- Signal Processing 3
Countries citing papers authored by M. Campbell
This map shows the geographic impact of M. Campbell'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. Campbell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Campbell more than expected).
Fields of papers citing papers by M. Campbell
This network shows the impact of papers produced by M. Campbell. 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. Campbell. The network helps show where M. Campbell may publish in the future.
Co-authorship network
The 25 scholars most cited alongside M. Campbell, 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 | 2015 | 0 | |
| 2 | 2015 | 1 | |
| 3 | 2002 | 0 | |
| 4 | 1995 | 7 | |
| 5 | 1990 | 17 | |
| 6 | 1988 | 4 | |
| 7 | 1988 | 17 | |
| 8 | 1985 | 1 |
About M. Campbell
M. Campbell is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence and Signal Processing, having authored 8 papers that have together received 47 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (6 papers), Particle Detector Development and Performance (5 papers), Computational Physics and Python Applications (2 papers), Dark Matter and Cosmic Phenomena (2 papers), Physics of Superconductivity and Magnetism (1 paper), Distributed and Parallel Computing Systems (1 paper), High-Energy Particle Collisions Research (1 paper) and Speech and Audio Processing (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (32 citations), Radiation (5 citations) and Artificial Intelligence (16 citations). M. Campbell has collaborated with scholars based in United States, Italy and Israel. Frequent co-authors include B. Denby, F. Bedeschi, Fabrizio Nesti, C. Edward Bowers, Neil Chriss, C. Grosso-Pilcher, G. Redlinger, M. J. Shochet, K. Burkett and W. Badgett. Their work appears in journals such as Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, IEEE Transactions on Nuclear Science and International Conference on Acoustics, Speech, and Signal Processing.
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.