Benoît Garbinato

1.4k citations
106 papers · 949 · h-index 17

Impact in

Papers in

Benoît Garbinato

102 papers receiving 874 citations

Peers

Benoît Garbinato
Comparison fields: 5 of 44
  • Computer Networks and Communications 596
  • Transportation 53
  • Artificial Intelligence 220
  • Signal Processing 41
  • Information Systems 93
Replace Starsky H.Y. Wong with:
Starsky H.Y. Wong United States
Jian Xu China
Mathy Vanhoef Belgium
Minghua Ma China
Moritz Steiner United States
Marvin McNett United States
Elena Pagani Italy
Ying Cai United States
Valtteri Niemi Finland
Gergely Ács Hungary
Benoît Garbinato relative to Starsky H.Y. Wong United States Starsky H.Y. Wong's profile →
Citations per field
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Citations per year

Countries citing papers authored by Benoît Garbinato

Since Specialization
Citations

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

Fields of papers citing papers by Benoît Garbinato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Benoît Garbinato, 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 Benoît Garbinato Line = papers co-authored together Benoît Garbinato links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 106 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200960
2 199957
3 200248
4 200546
5 200243
6 199535
7 199834
8 202332
9 201928
10
Using the strategy design pattern to compose reliable distributed protocols
199726
11 199719
12 200218
13 200318
14 200818
15 200918
16 201818
17 201317
18 200916
19 201716
20 201415

About Benoît Garbinato

Benoît Garbinato is a scholar working on Computer Networks and Communications, Transportation, Signal Processing, Artificial Intelligence and Information Systems, having authored 106 papers that have together received 949 indexed citations. Recurring topics across this work include Distributed systems and fault tolerance (38 papers), Mobile Ad Hoc Networks (17 papers), Peer-to-Peer Network Technologies (10 papers), Data Management and Algorithms (9 papers), Human Mobility and Location-Based Analysis (9 papers), Privacy-Preserving Technologies in Data (7 papers), Opportunistic and Delay-Tolerant Networks (6 papers) and Mobile and Web Applications (5 papers). The work is most often cited by research in Computer Networks and Communications (596 citations), Transportation (53 citations), Artificial Intelligence (220 citations), Signal Processing (41 citations) and Information Systems (93 citations). Benoît Garbinato has collaborated with scholars based in Switzerland, United States and Canada. Frequent co-authors include Rachid Guerraoui, Adrian Holzer, Pascal A. Felber, Patrick Th. Eugster, Hugo Miranda, Fernando Pedone, André Schiper, John D. Kelleher, Marco Tomassini and Parisa Jalili Marandi. Their work appears in journals such as Computer Networks, ACM Computing Surveys, Lecture notes in computer science, IEEE Transactions on Learning Technologies and ACM SIGPLAN Notices.

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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