Nadime Francis

25 total papers · 679 total citations
7 papers, 298 citations indexed

About

Nadime Francis is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Nadime Francis has authored 7 papers receiving a total of 298 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 4 papers in Computer Networks and Communications and 4 papers in Artificial Intelligence. Recurrent topics in Nadime Francis's work include Graph Theory and Algorithms (6 papers), Advanced Database Systems and Queries (4 papers) and Algorithms and Data Compression (2 papers). Nadime Francis is often cited by papers focused on Graph Theory and Algorithms (6 papers), Advanced Database Systems and Queries (4 papers) and Algorithms and Data Compression (2 papers). Nadime Francis collaborates with scholars based in France, United Kingdom and United States. Nadime Francis's co-authors include Victor Marsault, Leonid Libkin, Tobias Lindaaker, Stefan Plantikow, Petra Selmer, Alastair Green, Paolo Guagliardo, Filip Murlak, Mingxi Wu and Oskar van Rest and has published in prestigious journals such as Theory of Computing Systems, Logical Methods in Computer Science and Edinburgh Research Explorer (University of Edinburgh).

In The Last Decade

Nadime Francis

5 papers receiving 287 citations

Hit Papers

Cypher 2018 2026 2020 2023 2018 50 100 150 200 250

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Nadime Francis 146 126 124 78 57 7 298
Victor Marsault 151 1.0× 134 1.1× 127 1.0× 74 0.9× 60 1.1× 8 311
Alastair Green 151 1.0× 142 1.1× 134 1.1× 77 1.0× 62 1.1× 4 315
Minh-Duc Pham 145 1.0× 170 1.3× 108 0.9× 88 1.1× 58 1.0× 5 255
Wangchao Le 152 1.0× 94 0.7× 179 1.4× 152 1.9× 93 1.6× 11 300
Mateusz Pawlik 147 1.0× 59 0.5× 78 0.6× 60 0.8× 150 2.6× 8 303
Andrew Lamb 104 0.7× 99 0.8× 223 1.8× 120 1.5× 99 1.7× 8 308
Oskar van Rest 104 0.7× 162 1.3× 137 1.1× 89 1.1× 34 0.6× 5 224
Andreas Wierse 112 0.8× 142 1.1× 37 0.3× 72 0.9× 84 1.5× 6 343
Ruslan Dautov 117 0.8× 63 0.5× 133 1.1× 35 0.4× 114 2.0× 12 351
Christopher R. Aberger 115 0.8× 137 1.1× 126 1.0× 86 1.1× 43 0.8× 6 233

Countries citing papers authored by Nadime Francis

Since Specialization
Citations

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

Fields of papers citing papers by Nadime Francis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nadime Francis

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

All Works

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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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