Mohamed Nadif

217 total papers · 2.5k total citations
84 papers, 1.3k citations indexed

About

Mohamed Nadif is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Mohamed Nadif has authored 84 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Artificial Intelligence, 21 papers in Computer Vision and Pattern Recognition and 16 papers in Statistical and Nonlinear Physics. Recurrent topics in Mohamed Nadif's work include Advanced Clustering Algorithms Research (42 papers), Bayesian Methods and Mixture Models (27 papers) and Complex Network Analysis Techniques (16 papers). Mohamed Nadif is often cited by papers focused on Advanced Clustering Algorithms Research (42 papers), Bayesian Methods and Mixture Models (27 papers) and Complex Network Analysis Techniques (16 papers). Mohamed Nadif collaborates with scholars based in France, Belgium and United Kingdom. Mohamed Nadif's co-authors include Gérard Govaert, Lazhar Labiod, Aghiles Salah, G. Govaert, Blaise Hanczar, Simon Fossier, Florence Démenais, Nicole Le Moual, Régis Matran and Rachel Nadif and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, European Journal of Operational Research and Pattern Recognition.

In The Last Decade

Mohamed Nadif

81 papers receiving 1.3k citations

Author Peers

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

Author						Papers	Cites
Mohamed Nadif	899	326	232	188	186	84	1.3k
David J. Marchette	611 0.7×	188 0.6×	288 1.2×	98 0.5×	121 0.7×	72	1.3k
Xiaowen Dong	767 0.9×	229 0.7×	467 2.0×	104 0.6×	90 0.5×	53	1.5k
Guy Lebanon	727 0.8×	441 1.4×	98 0.4×	51 0.3×	411 2.2×	56	1.3k
Michael Collins	1.3k 1.5×	391 1.2×	51 0.2×	118 0.6×	122 0.7×	27	1.7k
Éric Gaussier	1.3k 1.5×	265 0.8×	53 0.2×	197 1.0×	250 1.3×	69	1.7k
Yingyu Liang	1.1k 1.2×	349 1.1×	101 0.4×	45 0.2×	142 0.8×	55	1.6k
Nagarajan Natarajan	682 0.8×	209 0.6×	236 1.0×	298 1.6×	267 1.4×	62	1.6k
Hisao Tamaki	881 1.0×	360 1.1×	138 0.6×	96 0.5×	245 1.3×	62	1.8k
Maria-Florina Balcan	1.0k 1.2×	295 0.9×	90 0.4×	42 0.2×	87 0.5×	86	1.7k
Ata Kabán	706 0.8×	321 1.0×	42 0.2×	73 0.4×	101 0.5×	83	1.1k

Countries citing papers authored by Mohamed Nadif

Since Specialization

Citations

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

Fields of papers citing papers by Mohamed Nadif

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohamed Nadif

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