Brian Sutton
Impact in
- Artificial Intelligence top 10%
- Quantum Computing Algorithms and Architecture
- Neural Networks and Reservoir Computing
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- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
Papers in
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- Advanced Memory and Neural Computing 3
- Low-power high-performance VLSI design 2
- Advancements in Semiconductor Devices and Circuit Design 2
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- Quantum Computing Algorithms and Architecture 3
- Neural Networks and Applications 1
- Co-authors
- Supriyo Datta (7 shared papers)Kerem Y. Çamsarı (6 shared papers)Rafatul Faria (5 shared papers)Ahmed Zeeshan Pervaiz (2 shared papers)Behtash Behin‐Aein (1 shared paper)Jay H. Baltisberger (1 shared paper)Anthony Reynolds (1 shared paper)
- Journals
- Physical Review X (1 paper)Journal of Magnetic Resonance (1 paper)Scientific Reports (1 paper)Applied Physics Letters (1 paper)IEEE Access (1 paper)
- Partner nations
- United States
In The Last Decade
Brian Sutton
10 papers receiving 320 citations
Peers
Comparison fields: 5 of 31
- Artificial Intelligence 183
- Electrical and Electronic Engineering 208
- Atomic and Molecular Physics, and Optics 110
- Computational Theory and Mathematics 46
- Computer Networks and Communications 54
Countries citing papers authored by Brian Sutton
This map shows the geographic impact of Brian Sutton'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 Brian Sutton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian Sutton more than expected).
Fields of papers citing papers by Brian Sutton
This network shows the impact of papers produced by Brian Sutton. 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 Brian Sutton. The network helps show where Brian Sutton may publish in the future.
Co-authors
The 7 scholars most cited alongside Brian Sutton, 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 | 2017 | 191 | |
| 2 | 2018 | 48 | |
| 3 | 2020 | 42 | |
| 4 | 2014 | 19 | |
| 5 | 2015 | 18 | |
| 6 | 2007 | 5 | |
| 7 | Stochastic P-bits for Probabilistic Spin Logic | 2016 | 3 |
| 8 | 2010 | 2 | |
| 9 | 2017 | 1 | |
| 10 | 2017 | 1 |
About Brian Sutton
Brian Sutton is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics and Computer Networks and Communications, having authored 10 papers that have together received 330 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (3 papers), Advanced Memory and Neural Computing (3 papers), Quantum and electron transport phenomena (2 papers), Low-power high-performance VLSI design (2 papers), Advancements in Semiconductor Devices and Circuit Design (2 papers), Advanced NMR Techniques and Applications (1 paper), Error Correcting Code Techniques (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Artificial Intelligence (183 citations), Electrical and Electronic Engineering (208 citations), Atomic and Molecular Physics, and Optics (110 citations), Computational Theory and Mathematics (46 citations) and Computer Networks and Communications (54 citations). Brian Sutton has collaborated with scholars based in United States. Frequent co-authors include Supriyo Datta, Kerem Y. Çamsarı, Rafatul Faria, Ahmed Zeeshan Pervaiz, Behtash Behin‐Aein, Jay H. Baltisberger and Anthony Reynolds. Their work appears in journals such as Physical Review X, Journal of Magnetic Resonance, Scientific Reports, Applied Physics Letters and IEEE Access.
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.