Fabio Checconi

1.1k citations
38 papers · 693 indexed · h-index 16
Topics
Parallel Computing and Optimization Techniques (17 papers)Real-Time Systems Scheduling (14 papers)Interconnection Networks and Systems (10 papers)

In The Last Decade

Fabio Checconi

36 papers receiving 650 citations

Peers

Fabio Checconi
Comparison fields: 5 of 71
  • Computer Networks and Communications 389
  • Hardware and Architecture 288
  • Information Systems 180
  • Computer Vision and Pattern Recognition 153
  • Artificial Intelligence 145
Replace Maciej Besta with:
Maciej Besta Switzerland
Lifeng Nai United States
Daehoon Kim South Korea
Harsha Vardhan Simhadri United States
Andrew Putnam United States
Nachiket Kapre Singapore
Youshan Miao China
Jesper Larsson Träff Austria
Dan Alistarh Austria
A. Ferreira France
Fabio Checconi relative to Maciej Besta Switzerland Maciej Besta's profile →
Citations per field
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Citations per year

Countries citing papers authored by Fabio Checconi

Since Specialization
Citations

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

Fields of papers citing papers by Fabio Checconi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fabio Checconi

This figure shows the co-authorship network connecting the top 25 collaborators of Fabio Checconi. A scholar is included among the top collaborators of Fabio Checconi 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 Fabio Checconi. Fabio Checconi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 1
4 35
5 3
6 3
7 88
8 12
9 58
10 32
11 10
12 34
13 21
14
Effective Real-Time Computing on Linux
2
15 2
16 19
17 41
18 37
19 5
20 6

About Fabio Checconi

Fabio Checconi is a scholar working on Computational Mathematics, Hardware and Architecture and Computer Networks and Communications, having authored 38 papers that have together received 693 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (17 papers), Real-Time Systems Scheduling (14 papers) and Interconnection Networks and Systems (10 papers). The work is most often cited by research in Hardware and Architecture (288 citations), Computer Networks and Communications (389 citations) and Information Systems (180 citations). Fabio Checconi has collaborated with scholars based in United States, Italy and Germany. Frequent co-authors include Fabrizio Petrini, Xinyu Que, Tommaso Cucinotta, Dario Faggioli, Paolo Valente, John A. Gunnels, Yogish Sabharwal, Giuseppe Lipari, Venkatesan T. Chakaravarthy and Marko Bertogna. Their work appears in journals such as Computer, IEEE Transactions on Computers and IEEE/ACM Transactions on Networking.

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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