Matthew Fluet

1.0k citations
58 papers · 764 · h-index 19

Impact in

Papers in

Matthew Fluet

56 papers receiving 730 citations

Peers

Matthew Fluet
Comparison fields: 5 of 31
  • Hardware and Architecture 496
  • Computer Networks and Communications 431
  • Artificial Intelligence 495
  • Computational Theory and Mathematics 185
  • Software 45
Replace Roman Leshchinskiy with:
Roman Leshchinskiy Australia
Hans‐Wolfgang Loidl United Kingdom
Richard Kelsey United States
Kathleen Knobe United States
Michał Cierniak United States
Kiminori Matsuzaki Japan
Philippe Clauss France
William Blume United States
Allan M. Schiffman United States
Massimiliano Poletto United States
Matthew Fluet relative to Roman Leshchinskiy Australia Roman Leshchinskiy's profile →
Citations per field
00.5×4.3×
Roman Leshchinskiy · 1×
Citations per year

Countries citing papers authored by Matthew Fluet

Since Specialization
Citations

This map shows the geographic impact of Matthew Fluet'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 Matthew Fluet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Fluet more than expected).

Fields of papers citing papers by Matthew Fluet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew Fluet. 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 Matthew Fluet. The network helps show where Matthew Fluet may publish in the future.

Co-authors

The 18 scholars most cited alongside Matthew Fluet, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Matthew Fluet Line = papers co-authored together Matthew Fluet links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200586
2 201053
3 200749
4 200641
5 200533
6 200832
7 200630
8 200730
9 200825
10 200925
11 200823
12 200123
13 200822
14 200822
15 200621
16 200820
17 200619
18 201019
19 201119
20 200218

About Matthew Fluet

Matthew Fluet is a scholar working on Hardware and Architecture, Artificial Intelligence, Computer Networks and Communications, Computational Theory and Mathematics and Software, having authored 58 papers that have together received 764 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (36 papers), Logic, programming, and type systems (33 papers), Distributed systems and fault tolerance (21 papers), Security and Verification in Computing (13 papers), Distributed and Parallel Computing Systems (10 papers), Interconnection Networks and Systems (8 papers), Formal Methods in Verification (7 papers) and Advanced Data Storage Technologies (6 papers). The work is most often cited by research in Hardware and Architecture (496 citations), Computer Networks and Communications (431 citations), Artificial Intelligence (495 citations), Computational Theory and Mathematics (185 citations) and Software (45 citations). Matthew Fluet has collaborated with scholars based in United States and Germany. Frequent co-authors include Greg Morrisett, John Reppy, Mike Rainey, Amal Ahmed, Umut A. Acar, Riccardo Pucella, K. Donnelly, Lars Bergström, Stephen Weeks and Matthew Le. Their work appears in journals such as ACM SIGPLAN Notices, Journal of Functional Programming, Proceedings of the ACM on Programming Languages, The Electronic Journal of Combinatorics 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.

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