Bryan Singer

1.1k total citations · 1 hit paper
9 papers, 695 citations indexed

About

Bryan Singer is a scholar working on Computational Theory and Mathematics, Signal Processing and Hardware and Architecture. According to data from OpenAlex, Bryan Singer has authored 9 papers receiving a total of 695 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computational Theory and Mathematics, 6 papers in Signal Processing and 4 papers in Hardware and Architecture. Recurrent topics in Bryan Singer's work include Numerical Methods and Algorithms (7 papers), Digital Filter Design and Implementation (6 papers) and Parallel Computing and Optimization Techniques (3 papers). Bryan Singer is often cited by papers focused on Numerical Methods and Algorithms (7 papers), Digital Filter Design and Implementation (6 papers) and Parallel Computing and Optimization Techniques (3 papers). Bryan Singer collaborates with scholars based in United States and Czechia. Bryan Singer's co-authors include Manuela Veloso, David Padua, José M. F. Moura, Jeremy Johnson, Markus Püschel, A. Gacic, Yevgen Voronenko, Robert W. Johnson, Franz Franchetti and Robert W. Johnson and has published in prestigious journals such as Proceedings of the IEEE, IEEE Transactions on Signal Processing and Journal of Machine Learning Research.

In The Last Decade

Bryan Singer

9 papers receiving 650 citations

Hit Papers

SPIRAL: Code Generation for DSP Transforms 2005 2026 2012 2019 2005 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. SPIRAL: Code Generation for DSP Transforms
    2005 513 citations Markus Püschel, José M. F. Moura et al. Proceedings of the IEEE profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bryan Singer United States 6 548 277 191 162 102 9 695
A. Gacic United States 6 418 0.8× 251 0.9× 143 0.7× 135 0.8× 65 0.6× 9 703
Harry A. G. Wijshoff Netherlands 17 558 1.0× 459 1.7× 149 0.8× 165 1.0× 22 0.2× 67 794
Ayal Zaks Israel 14 701 1.3× 474 1.7× 151 0.8× 241 1.5× 41 0.4× 37 911
Giuseppe Di Guglielmo United States 16 429 0.8× 208 0.8× 116 0.6× 154 1.0× 57 0.6× 70 726
Alastair Reid United States 15 446 0.8× 345 1.2× 148 0.8× 315 1.9× 63 0.6× 29 755
Hal Wasserman United States 8 312 0.6× 260 0.9× 180 0.9× 370 2.3× 35 0.3× 12 838
William Jalby France 16 1.0k 1.9× 868 3.1× 161 0.8× 151 0.9× 31 0.3× 60 1.2k
Robert L. Bocchino United States 14 588 1.1× 609 2.2× 65 0.3× 264 1.6× 35 0.3× 31 863
Larry Carter United States 17 509 0.9× 480 1.7× 81 0.4× 201 1.2× 21 0.2× 48 741
Milind Girkar United States 17 850 1.6× 679 2.5× 56 0.3× 102 0.6× 61 0.6× 40 985

Countries citing papers authored by Bryan Singer

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Bryan Singer

This figure shows the co-authorship network connecting the top 25 collaborators of Bryan Singer. A scholar is included among the top collaborators of Bryan Singer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bryan Singer. Bryan Singer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Püschel, Markus, José M. F. Moura, Jeremy Johnson, et al.. (2005). SPIRAL: Code Generation for DSP Transforms. Proceedings of the IEEE. 93(2). 232–275. 513 indexed citations breakdown →
2.
Püschel, Markus, José M. F. Moura, Bryan Singer, et al.. (2004). Spiral: A Generator for Platform-Adapted Libraries of Signal Processing Alogorithms. The International Journal of High Performance Computing Applications. 18(1). 21–45. 112 indexed citations
3.
Singer, Bryan & Manuela Veloso. (2003). Learning to construct fast signal processing implementations. Journal of Machine Learning Research. 3. 887–919. 17 indexed citations
4.
Singer, Bryan & Manuela Veloso. (2002). Automating the modeling and optimization of the performance of signal transforms. IEEE Transactions on Signal Processing. 50(8). 2003–2014. 8 indexed citations
5.
Singer, Bryan & Manuela Veloso. (2001). Learning to Generate Fast Signal Processing Implementations. International Conference on Machine Learning. 529–536. 3 indexed citations
6.
Singer, Bryan & Manuela Veloso. (2001). Stochastic search for signal processing algorithm optimization. 22–22. 21 indexed citations
7.
Singer, Bryan, et al.. (2001). X-Men. 73–73. 1 indexed citations
8.
Singer, Bryan & Manuela Veloso. (2000). Learning to Predict Performance from Formula Modeling and Training Data. International Conference on Machine Learning. 887–894. 19 indexed citations
9.
Singer, Bryan & Manuela Veloso. (2000). Automated Formula Generation and Performance Learning for the FFT. Defense Technical Information Center (DTIC). 1 indexed citations

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.

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2026