D. Dubois

9 total papers · 644 total citations
4 papers, 305 citations indexed

About

D. Dubois is a scholar working on Computer Networks and Communications, Hardware and Architecture and Artificial Intelligence. According to data from OpenAlex, D. Dubois has authored 4 papers receiving a total of 305 indexed citations (citations by other indexed papers that have themselves been cited), including 1 paper in Computer Networks and Communications, 1 paper in Hardware and Architecture and 1 paper in Artificial Intelligence. Recurrent topics in D. Dubois's work include Bayesian Modeling and Causal Inference (1 paper), Multi-Criteria Decision Making (1 paper) and Interconnection Networks and Systems (1 paper). D. Dubois is often cited by papers focused on Bayesian Modeling and Causal Inference (1 paper), Multi-Criteria Decision Making (1 paper) and Interconnection Networks and Systems (1 paper). D. Dubois collaborates with scholars based in United States. D. Dubois's co-authors include Henri Prade, Jérôme Lang, E. Chojnacki, Sébastien Destercke and Wu-chun Feng and has published in prestigious journals such as HAL (Le Centre pour la Communication Scientifique Directe) and Computing and Informatics / Computers and Artificial Intelligence.

In The Last Decade

D. Dubois

4 papers receiving 285 citations

Author Peers

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

Author						Papers	Cites
D. Dubois	280	105	47	35	31	4	305
H. Prade	201 0.7×	71 0.7×	21 0.4×	65 1.9×	22 0.7×	5	251
Tian Sang	189 0.7×	52 0.5×	62 1.3×	15 0.4×	50 1.6×	5	216
Antony Courtney	124 0.4×	95 0.9×	58 1.2×	19 0.5×	14 0.5×	5	233
Erhard Schwecke	157 0.6×	40 0.4×	27 0.6×	78 2.2×	29 0.9×	6	215
M.E. Stickel	208 0.7×	77 0.7×	80 1.7×	9 0.3×	19 0.6×	10	255
Francisco J. Estrella	167 0.6×	93 0.9×	16 0.3×	256 7.3×	14 0.5×	7	322
Karen Seidel	253 0.9×	212 2.0×	47 1.0×	6 0.2×	17 0.5×	9	317
Christophe Hancart	271 1.0×	123 1.2×	32 0.7×	8 0.2×	30 1.0×	5	335
Wiesław Zielonka	227 0.8×	300 2.9×	46 1.0×	17 0.5×	6 0.2×	12	351
Zhanyong Wan	101 0.4×	93 0.9×	97 2.1×	23 0.7×	14 0.5×	8	337

Countries citing papers authored by D. Dubois

Since Specialization

Citations

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

Fields of papers citing papers by D. Dubois

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Dubois

This figure shows the co-authorship network connecting the top 25 collaborators of D. Dubois. A scholar is included among the top collaborators of D. Dubois 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 D. Dubois. D. Dubois 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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