Joris M. Mooij

117 total papers · 8.6k total citations
47 papers, 3.4k citations indexed

About

Joris M. Mooij is a scholar working on Artificial Intelligence, Molecular Biology and Computer Networks and Communications. According to data from OpenAlex, Joris M. Mooij has authored 47 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Artificial Intelligence, 9 papers in Molecular Biology and 8 papers in Computer Networks and Communications. Recurrent topics in Joris M. Mooij's work include Bayesian Modeling and Causal Inference (37 papers), Machine Learning and Algorithms (9 papers) and Error Correcting Code Techniques (8 papers). Joris M. Mooij is often cited by papers focused on Bayesian Modeling and Causal Inference (37 papers), Machine Learning and Algorithms (9 papers) and Error Correcting Code Techniques (8 papers). Joris M. Mooij collaborates with scholars based in Netherlands, Germany and Switzerland. Joris M. Mooij's co-authors include Tom Heskes, Daniëlle Posthuma, Christiaan de Leeuw, Dominik Janzing, Bernhard Schölkopf, Jonas Peters, Hilbert J. Kappen, Patrik O. Hoyer, Jakob Zscheischler and Kun Zhang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and IEEE Transactions on Information Theory.

In The Last Decade

Joris M. Mooij

43 papers receiving 3.2k citations

Hit Papers

MAGMA: Generalized Gene-S... 2015 2026 2018 2022 2015 500 1000 1.5k

Author Peers

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

Author Last Decade Papers Cites
Joris M. Mooij 1.3k 919 913 287 204 47 3.4k
Daniel L. Koller 2.0k 1.6× 1.4k 1.6× 927 1.0× 256 0.9× 331 1.6× 74 6.3k
Tom Heskes 1.7k 1.3× 1.2k 1.3× 1.1k 1.2× 282 1.0× 317 1.6× 229 5.9k
Christophe Ambroise 764 0.6× 1.1k 1.2× 240 0.3× 280 1.0× 116 0.6× 52 2.7k
Anna Goldenberg 1.1k 0.9× 2.4k 2.6× 308 0.3× 119 0.4× 82 0.4× 126 5.8k
Ka Yee Yeung 1.0k 0.8× 2.2k 2.4× 280 0.3× 233 0.8× 150 0.7× 56 3.7k
Pat Brown 593 0.5× 1.7k 1.8× 339 0.4× 196 0.7× 113 0.6× 25 3.4k
Andrew B. Nobel 854 0.7× 5.4k 5.9× 1.5k 1.7× 399 1.4× 167 0.8× 85 10.6k
Guido Sanguinetti 487 0.4× 2.5k 2.8× 557 0.6× 74 0.3× 123 0.6× 135 4.2k
Alexander Statnikov 1.6k 1.3× 1.8k 1.9× 161 0.2× 156 0.5× 113 0.6× 83 4.6k
Ji Zhu 933 0.7× 1.2k 1.4× 292 0.3× 664 2.3× 97 0.5× 181 5.8k

Countries citing papers authored by Joris M. Mooij

Since Specialization
Citations

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

Fields of papers citing papers by Joris M. Mooij

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joris M. Mooij. 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 Joris M. Mooij. The network helps show where Joris M. Mooij may publish in the future.

Co-authorship network of co-authors of Joris M. Mooij

This figure shows the co-authorship network connecting the top 25 collaborators of Joris M. Mooij. A scholar is included among the top collaborators of Joris M. Mooij 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 Joris M. Mooij. Joris M. Mooij 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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