Bryan Singer
Impact in
- Hardware and Architecture top 1%
- Parallel Computing and Optimization Techniques
- Embedded Systems Design Techniques
- Computational Mathematics top 10%
Papers in
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- Numerical Methods and Algorithms 8
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- Parallel Computing and Optimization Techniques 4
- Embedded Systems Design Techniques 1
- VLSI and Analog Circuit Testing 1
- Co-authors
- Manuela Veloso (9 shared papers)Markus Püschel (3 shared papers)José M. F. Moura (3 shared papers)Jeremy Russell Johnson (2 shared papers)David Padua (2 shared papers)Yevgen Voronenko (1 shared paper)Robert William Johnson (1 shared paper)Franz Franchetti (1 shared paper)
- Journals
- IEEE Transactions on Signal Processing (1 paper)Journal of Machine Learning Research (1 paper)Proceedings of the IEEE (1 paper)The International Journal of High Performance Computing Applications (1 paper)Lecture notes in computer science (1 paper)
- Partner nations
- United StatesCzechia
In The Last Decade
Bryan Singer
9 papers receiving 793 citations
Bryan Singer's Hit Papers
Peers
Comparison fields: 5 of 47
- Hardware and Architecture 649
- Computational Mathematics 9
- Computational Theory and Mathematics 242
- Computer Networks and Communications 323
- Signal Processing 126
Countries citing papers authored by Bryan Singer
This map shows the geographic impact of Bryan Singer'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 Bryan Singer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bryan Singer more than expected).
Fields of papers citing papers by Bryan Singer
This network shows the impact of papers produced by Bryan Singer. 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 Bryan Singer. The network helps show where Bryan Singer may publish in the future.
Co-authors
The 10 scholars most cited alongside Bryan Singer, 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 | SPIRAL: Code Generation for DSP Transforms Hit paper breakdown → | 2005 | 601 |
| 2 | 2004 | 132 | |
| 3 | Learning to Predict Performance from Formula Modeling and Training Data | 2000 | 28 |
| 4 | 2001 | 22 | |
| 5 | 2001 | 22 | |
| 6 | Learning to construct fast signal processing implementations | 2003 | 18 |
| 7 | 2002 | 8 | |
| 8 | Learning to Generate Fast Signal Processing Implementations | 2001 | 3 |
| 9 | Automated Formula Generation and Performance Learning for the FFT | 2000 | 1 |
About Bryan Singer
Bryan Singer is a scholar working on Computational Theory and Mathematics, Hardware and Architecture, Signal Processing, Computational Mechanics and Information Systems, having authored 9 papers that have together received 835 indexed citations. Recurring topics across this work include Numerical Methods and Algorithms (8 papers), Digital Filter Design and Implementation (6 papers), Parallel Computing and Optimization Techniques (4 papers), Software Engineering Research (1 paper), Evolutionary Algorithms and Applications (1 paper), Embedded Systems Design Techniques (1 paper), Analog and Mixed-Signal Circuit Design (1 paper) and VLSI and Analog Circuit Testing (1 paper). The work is most often cited by research in Hardware and Architecture (649 citations), Computational Mathematics (9 citations), Computational Theory and Mathematics (242 citations), Computer Networks and Communications (323 citations) and Signal Processing (126 citations). Bryan Singer has collaborated with scholars based in United States and Czechia. Frequent co-authors include Manuela Veloso, Markus Püschel, José M. F. Moura, Jeremy Russell Johnson, David Padua, Yevgen Voronenko, Robert William Johnson, Franz Franchetti, A. Gacic and Robert W. Johnson. Their work appears in journals such as IEEE Transactions on Signal Processing, Journal of Machine Learning Research, Proceedings of the IEEE, The International Journal of High Performance Computing Applications and Lecture notes in computer science.
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.