Mai Oudah

25 total papers · 577 total citations
15 papers, 315 citations indexed

About

Mai Oudah is a scholar working on Artificial Intelligence, Molecular Biology and Management Science and Operations Research. According to data from OpenAlex, Mai Oudah has authored 15 papers receiving a total of 315 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 5 papers in Molecular Biology and 2 papers in Management Science and Operations Research. Recurrent topics in Mai Oudah's work include Topic Modeling (7 papers), Natural Language Processing Techniques (7 papers) and Gut microbiota and health (4 papers). Mai Oudah is often cited by papers focused on Topic Modeling (7 papers), Natural Language Processing Techniques (7 papers) and Gut microbiota and health (4 papers). Mai Oudah collaborates with scholars based in United Arab Emirates, United States and Qatar. Mai Oudah's co-authors include Khaled Shaalan, Andreas Henschel, Nizar Habash, Alexander Erdmann, Salam Khalifa, Ossama Obeid, Go Inoue, Fadhl Eryani, Nasser Zalmout and Dima Taji and has published in prestigious journals such as BMC Bioinformatics, Microbiological Research and Sociological Methodology.

In The Last Decade

Mai Oudah

14 papers receiving 292 citations

Author Peers

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

Author						Papers	Cites
Mai Oudah	221	77	19	17	16	15	315
Graham Jackson	70 0.3×	53 0.7×	22 1.2×	29 1.7×	17 1.1×	17	299
Wim De Smet	205 0.9×	66 0.9×	48 2.5×	14 0.8×	26 1.6×	20	312
Simone Gittelson	39 0.2×	85 1.1×	15 0.8×	10 0.6×	27 1.7×	17	224
Rüdiger Klar	80 0.4×	55 0.7×	14 0.7×	31 1.8×	17 1.1×	17	238
Yingying Wen	115 0.5×	58 0.8×	43 2.3×	21 1.2×	8 0.5×	21	296
Masato Hagiwara	217 1.0×	57 0.7×	38 2.0×	17 1.0×	10 0.6×	31	346
Nicolas Fiorini	159 0.7×	152 2.0×	38 2.0×	9 0.5×	3 0.2×	11	296
Scott Mardis	184 0.8×	160 2.1×	28 1.5×	9 0.5×	19 1.2×	12	312
Md Shoaib Ahmed	105 0.5×	35 0.5×	35 1.8×	23 1.4×	6 0.4×	18	283
Taeuk Kim	211 1.0×	49 0.6×	18 0.9×	53 3.1×	3 0.2×	24	296

Countries citing papers authored by Mai Oudah

Since Specialization

Citations

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

Fields of papers citing papers by Mai Oudah

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mai Oudah

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