Mohamed Nadif

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, Régis Matran, Nicole Le Moual and Orianne Dumas 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

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mohamed Nadif France 20 903 329 233 190 185 84 1.3k
M.H.C. Law United States 12 794 0.9× 570 1.7× 86 0.4× 121 0.6× 201 1.1× 13 1.3k
Subramanyam Mallela United States 8 1.0k 1.1× 477 1.4× 279 1.2× 184 1.0× 451 2.4× 9 1.5k
Steffen Bickel Germany 14 1.0k 1.1× 520 1.6× 150 0.6× 129 0.7× 201 1.1× 17 1.5k
Natthakan Iam-On Thailand 16 629 0.7× 336 1.0× 153 0.7× 160 0.8× 147 0.8× 51 966
Tossapon Boongoen Thailand 18 615 0.7× 286 0.9× 139 0.6× 160 0.8× 177 1.0× 59 994
Kazumi Saito Japan 18 582 0.6× 286 0.9× 705 3.0× 89 0.5× 261 1.4× 102 1.5k
Max Chickering United States 11 1.1k 1.2× 241 0.7× 75 0.3× 109 0.6× 430 2.3× 18 1.7k
Wu Xiaoyun United States 12 889 1.0× 393 1.2× 166 0.7× 132 0.7× 234 1.3× 18 1.4k
Éric Gaussier France 21 1.3k 1.5× 266 0.8× 56 0.2× 199 1.0× 251 1.4× 70 1.8k
Hisashi Kashima Japan 12 563 0.6× 234 0.7× 143 0.6× 171 0.9× 108 0.6× 28 1.0k

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

20 of 20 papers shown
1.
Nadif, Mohamed, et al.. (2024). WordGraph: A Python Package for Reconstructing Interactive Causal Graphical Models from Text Data. SPIRE - Sciences Po Institutional REpository. 1046–1049.
2.
Labiod, Lazhar, et al.. (2023). Scalable Attributed-Graph Subspace Clustering. Proceedings of the AAAI Conference on Artificial Intelligence. 37(6). 7559–7567. 13 indexed citations
3.
Nadif, Mohamed, et al.. (2023). Is Anisotropy Truly Harmful? A Case Study on Text Clustering. SPIRE - Sciences Po Institutional REpository. 1194–1203. 3 indexed citations
4.
Nadif, Mohamed, et al.. (2023). Unsupervised Anomaly Detection in Multi-Topic Short-Text Corpora. SPIRE - Sciences Po Institutional REpository. 1392–1403. 2 indexed citations
5.
Labiod, Lazhar, et al.. (2022). Efficient and Effective Optimal Transport-Based Biclustering. SPIRE - Sciences Po Institutional REpository. 32989–33000.
6.
Labiod, Lazhar, et al.. (2022). CAEclust: A Consensus of Autoencoders Representations for Clustering. Image Processing On Line. 12. 590–603. 1 indexed citations
7.
Nadif, Mohamed, et al.. (2022). A survey on machine learning methods for churn prediction. International Journal of Data Science and Analytics. 14(3). 217–242. 34 indexed citations
8.
Salah, Aghiles, et al.. (2022). Improving NMF clustering by leveraging contextual relationships among words. Neurocomputing. 495. 105–117. 7 indexed citations
9.
Nadif, Mohamed, et al.. (2022). An effective strategy for churn prediction and customer profiling. Data & Knowledge Engineering. 142. 102100–102100. 11 indexed citations
10.
Nadif, Mohamed, et al.. (2021). Unsupervised and self-supervised deep learning approaches for biomedical text mining. Briefings in Bioinformatics. 22(2). 1592–1603. 50 indexed citations
11.
Salah, Aghiles & Mohamed Nadif. (2017). Social regularized von Mises–Fisher mixture model for item recommendation. Data Mining and Knowledge Discovery. 31(5). 1218–1241. 15 indexed citations
12.
Nadif, Mohamed, et al.. (2017). Model-based co-clustering for the effective handling of sparse data. Pattern Recognition. 72. 108–122. 26 indexed citations
13.
Nadif, Mohamed, et al.. (2016). Unsupervised text mining for assessing and augmenting GWAS results. Journal of Biomedical Informatics. 60. 252–259. 10 indexed citations
14.
Carvalho, Francisco de A.T. de, et al.. (2015). Fuzzy co-clustering with automated variable weighting. HAL (Le Centre pour la Communication Scientifique Directe). 1–8. 2 indexed citations
15.
Hanczar, Blaise & Mohamed Nadif. (2013). Precision-recall space to correct external indices for biclustering. International Conference on Machine Learning. 136–144. 4 indexed citations
16.
Nadif, Mohamed, et al.. (2009). Classification de données ordinales : modèles et algorithmes. HAL (Le Centre pour la Communication Scientifique Directe). 2 indexed citations
17.
Nadif, Mohamed & Gérard Govaert. (2008). Algorithms for Model-based Block Gaussian Clustering.. 536–542. 4 indexed citations
18.
Govaert, Gérard & Mohamed Nadif. (2007). Block clustering with Bernoulli mixture models: Comparison of different approaches. Computational Statistics & Data Analysis. 52(6). 3233–3245. 111 indexed citations
19.
Nadif, Mohamed & G. Govaert. (2005). Block clustering via the block GEM and two-way EM algorithms. 124–129. 8 indexed citations
20.
Nadif, Mohamed & Federico Marchetti. (1993). Classification de données qualitatives et modèles. French digital mathematics library (Numdam). 41(1). 55–69. 1 indexed citations

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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