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.
The Design and Implementation of FFTW3
20053.3k citationsMatteo Frigo, Steven G. Johnsonprofile →
FFTW: an adaptive software architecture for the FFT
20021.1k citationsMatteo Frigo, Steven G. Johnsonprofile →
The implementation of the Cilk-5 multithreaded language
1998786 citationsMatteo Frigo, Charles E. Leiserson et al.profile →
Cache-oblivious algorithms
2003423 citationsMatteo Frigo, Charles E. Leiserson et al.profile →
Parallel sparse matrix-vector and matrix-transpose-vector multiplication using compressed sparse blocks
2009266 citationsAydın Buluç, Jeremy T. Fineman et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Matteo Frigo'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 Matteo Frigo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Frigo more than expected).
This network shows the impact of papers produced by Matteo Frigo. 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 Matteo Frigo. The network helps show where Matteo Frigo may publish in the future.
Co-authorship network of co-authors of Matteo Frigo
This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Frigo.
A scholar is included among the top collaborators of Matteo Frigo 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 Matteo Frigo. Matteo Frigo is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kuszmaul, Bradley C., et al.. (2020). Everyone Loves File. ACM Transactions on Storage. 16(1). 1–29.2 indexed citations
10.
Ferronato, Massimiliano, Matteo Frigo, Carlo Janna, et al.. (2019). Uncertainty Quantification and Reduction Through Data Assimilation Approaches for the Geomechanical Modeling of Hydrocarbon Reservoirs. Research Padua Archive (University of Padua).4 indexed citations
11.
Teatini, Pietro, Massimiliano Ferronato, Andrea Franceschini, et al.. (2019). Gas Storage in Compartmentalized Reservoirs: A Numerical Investigation on Possible “Unexpected” Fault Activation. Research Padua Archive (University of Padua).2 indexed citations
12.
Kuszmaul, Bradley C., et al.. (2019). Everyone Loves File: File Storage Service ({FSS}) in Oracle Cloud Infrastructure. USENIX Annual Technical Conference. 15–32.5 indexed citations
Frigo, Matteo & Steven G. Johnson. (2012). FFTW: Fastest Fourier Transform in the West. Astrophysics Source Code Library.33 indexed citations
15.
Buluç, Aydın, Jeremy T. Fineman, Matteo Frigo, John R. Gilbert, & Charles E. Leiserson. (2009). Parallel sparse matrix-vector and matrix-transpose-vector multiplication using compressed sparse blocks. 233–244.266 indexed citations breakdown →
Frigo, Matteo, Charles E. Leiserson, & Keith H. Randall. (1998). The implementation of the Cilk-5 multithreaded language. 212–223.786 indexed citations breakdown →
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.