Michael Albright
Impact in
- Nuclear and High Energy Physics top 10%
- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Particle physics theoretical and experimental studies
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- Digital Media Forensic Detection
- Generative Adversarial Networks and Image Synthesis
- Face recognition and analysis
Papers in
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- Digital Media Forensic Detection 4
- Generative Adversarial Networks and Image Synthesis 4
- Advanced Image Processing Techniques 2
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- Quantum Chromodynamics and Particle Interactions 3
- High-Energy Particle Collisions Research 3
- Particle physics theoretical and experimental studies 2
- Co-authors
- Scott McCloskey (4 shared papers)Clint Young (2 shared papers)J. I. Kapusta (2 shared papers)Joseph I. Kapusta (1 shared paper)Arslan Basharat (1 shared paper)Eric M. Smith (1 shared paper)
- Journals
- Physical review. C (1 paper)2022 26th International Conference on Pattern Recognition (ICPR) (1 paper)arXiv (Cornell University) (1 paper)Physical Review C (2 papers)
- Partner nations
- United States
In The Last Decade
Michael Albright
7 papers receiving 294 citations
Peers
Comparison fields: 5 of 33
- Nuclear and High Energy Physics 167
- Computer Vision and Pattern Recognition 122
- Astronomy and Astrophysics 58
- Applied Mathematics 13
- Artificial Intelligence 35
Countries citing papers authored by Michael Albright
This map shows the geographic impact of Michael Albright'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 Michael Albright with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Albright more than expected).
Fields of papers citing papers by Michael Albright
This network shows the impact of papers produced by Michael Albright. 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 Michael Albright. The network helps show where Michael Albright may publish in the future.
Co-authors
The 6 scholars most cited alongside Michael Albright, 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 | 2019 | 123 | |
| 2 | 2014 | 74 | |
| 3 | 2016 | 54 | |
| 4 | 2015 | 48 | |
| 5 | Source Generator Attribution via Inversion | 2019 | 4 |
| 6 | 2022 | 1 | |
| 7 | 2021 | 1 | |
| 8 | 2019 | 1 |
About Michael Albright
Michael Albright is a scholar working on Computer Vision and Pattern Recognition, Nuclear and High Energy Physics, Astronomy and Astrophysics, Artificial Intelligence and Biophysics, having authored 8 papers that have together received 306 indexed citations. Recurring topics across this work include Digital Media Forensic Detection (4 papers), Generative Adversarial Networks and Image Synthesis (4 papers), Quantum Chromodynamics and Particle Interactions (3 papers), High-Energy Particle Collisions Research (3 papers), Advanced Image Processing Techniques (2 papers), Particle physics theoretical and experimental studies (2 papers), Cell Image Analysis Techniques (1 paper) and Pulsars and Gravitational Waves Research (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (167 citations), Computer Vision and Pattern Recognition (122 citations), Astronomy and Astrophysics (58 citations), Applied Mathematics (13 citations) and Artificial Intelligence (35 citations). Michael Albright has collaborated with scholars based in United States. Frequent co-authors include Scott McCloskey, Clint Young, J. I. Kapusta, Joseph I. Kapusta, Arslan Basharat and Eric M. Smith. Their work appears in journals such as Physical review. C, 2022 26th International Conference on Pattern Recognition (ICPR), arXiv (Cornell University) and Physical Review C.
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.