Jonas Dias

633 citations
26 papers · 399 · h-index 12

Impact in

Papers in

Jonas Dias

26 papers receiving 378 citations

Peers

Jonas Dias
Comparison fields: 5 of 34
  • Information Systems and Management 336
  • Computer Networks and Communications 322
  • Information Systems 245
  • Biophysics 13
  • Management Information Systems 12
Replace Zoltán Farkas with:
Zoltán Farkas Hungary
Gábor Gombás Hungary
Shalil Majithia United Kingdom
Upulee Kanewala United States
Yangfan Cui United States
Michael Wan United States
Tak‐Lon Wu United States
Yingwei Cui United States
Anat Eyal Israel
Dominic Battré Germany
Jonas Dias relative to Zoltán Farkas Hungary Zoltán Farkas's profile →
Citations per field
00.5×4.3×
Zoltán Farkas · 1×
Citations per year

Countries citing papers authored by Jonas Dias

Since Specialization
Citations

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

Fields of papers citing papers by Jonas Dias

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Jonas Dias, 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 Jonas Dias Line = papers co-authored together Jonas Dias links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201170
2 201441
3 201340
4 201337
5 201326
6 201119
7 201116
8 201416
9 201314
10 201314
11 201414
12 201113
13 201211
14 201211
15 20129
16 20138
17 20188
18 20167
19 20125
20 20135

About Jonas Dias

Jonas Dias is a scholar working on Information Systems and Management, Computer Networks and Communications, Information Systems, Molecular Biology and Computer Vision and Pattern Recognition, having authored 26 papers that have together received 399 indexed citations. Recurring topics across this work include Scientific Computing and Data Management (24 papers), Distributed and Parallel Computing Systems (17 papers), Advanced Data Storage Technologies (8 papers), Research Data Management Practices (6 papers), Cloud Computing and Resource Management (5 papers), Genomics and Phylogenetic Studies (3 papers), Genetics, Bioinformatics, and Biomedical Research (2 papers) and Cell Image Analysis Techniques (1 paper). The work is most often cited by research in Information Systems and Management (336 citations), Computer Networks and Communications (322 citations), Information Systems (245 citations), Biophysics (13 citations) and Management Information Systems (12 citations). Jonas Dias has collaborated with scholars based in Brazil, France and Russia. Frequent co-authors include Marta Mattoso, Daniel de Oliveira, Eduardo Ogasawara, Kary Ocaña, Fábio Porto, Patrick Valduriez, Vítor Silva, Álvaro L. G. A. Coutinho, Fernanda Baião and Fernando A. Rochinha. Their work appears in journals such as Future Generation Computer Systems, International Journal for Uncertainty Quantification, Computational Geosciences, Proceedings of the VLDB Endowment and Concurrency and Computation Practice and Experience.

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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