Stephan Seufert

993 total citations
13 papers, 593 citations indexed

About

Stephan Seufert is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Stephan Seufert has authored 13 papers receiving a total of 593 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 4 papers in Computer Networks and Communications. Recurrent topics in Stephan Seufert's work include Graph Theory and Algorithms (5 papers), Advanced Graph Neural Networks (4 papers) and Semantic Web and Ontologies (3 papers). Stephan Seufert is often cited by papers focused on Graph Theory and Algorithms (5 papers), Advanced Graph Neural Networks (4 papers) and Semantic Web and Ontologies (3 papers). Stephan Seufert collaborates with scholars based in Germany, India and Belgium. Stephan Seufert's co-authors include Gerhard Weikum, Srikanta Bedathur, Martin Theobald, Andrey Gubichev, Sairam Gurajada, Iris Miliaraki, Johannes Hoffart, Dat Ba Nguyen, Sebastian Schelter and Avishek Anand and has published in prestigious journals such as Max Planck Institute for Plasma Physics and IEEE Data(base) Engineering Bulletin.

In The Last Decade

Stephan Seufert

13 papers receiving 549 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Stephan Seufert Germany	9	365	207	175	156	109	13	593
Orri Erling United States	10	271 0.7×	249 1.2×	218 1.2×	103 0.7×	169 1.6×	16	521
Riccardo Torlone Italy	16	414 1.1×	531 2.6×	145 0.8×	254 1.6×	292 2.7×	85	837
Maya Ramanath Germany	14	634 1.7×	284 1.4×	129 0.7×	253 1.6×	275 2.5×	53	871
Sandeep Tata United States	14	312 0.9×	321 1.6×	125 0.7×	134 0.9×	372 3.4×	37	745
Kemafor Anyanwu United States	12	503 1.4×	429 2.1×	127 0.7×	186 1.2×	494 4.5×	36	880
Carlos Hurtado Chile	10	469 1.3×	518 2.5×	104 0.6×	306 2.0×	199 1.8×	17	677
Sara Cohen Israel	17	475 1.3×	547 2.6×	71 0.4×	394 2.5×	153 1.4×	62	806
Sean Kandel United States	5	237 0.6×	164 0.8×	285 1.6×	130 0.8×	156 1.4×	9	615
Baile Shi China	13	567 1.6×	132 0.6×	125 0.7×	142 0.9×	232 2.1×	58	792
Wolfgang Gatterbauer United States	16	336 0.9×	404 2.0×	88 0.5×	224 1.4×	303 2.8×	50	780

Countries citing papers authored by Stephan Seufert

Since Specialization

Citations

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

Fields of papers citing papers by Stephan Seufert

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephan Seufert

This figure shows the co-authorship network connecting the top 25 collaborators of Stephan Seufert. A scholar is included among the top collaborators of Stephan Seufert 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 Stephan Seufert. Stephan Seufert is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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13 of 13 papers shown

1.

Schelter, Sebastian, et al.. (2019). Unit Testing Data with Deequ. 1993–1996. 11 indexed citations

2.

Schelter, Sebastian, et al.. (2017). Automatically Tracking Metadata and Provenance of Machine Learning Experiments. 44 indexed citations

3.

Seufert, Stephan, et al.. (2016). Instant Espresso. 251–254. 5 indexed citations

4.

Seufert, Stephan, et al.. (2016). ESPRESSO. 1311–1320. 6 indexed citations

5.

Schelter, Sebastian, et al.. (2015). On Challenges in Machine Learning Model Management. IEEE Data(base) Engineering Bulletin. 41. 5–15. 85 indexed citations

6.

Gurajada, Sairam, Stephan Seufert, Iris Miliaraki, & Martin Theobald. (2014). Using Graph Summarization for Join-Ahead Pruning in a Distributed RDF Engine. 1–4. 2 indexed citations

7.

Gurajada, Sairam, Stephan Seufert, Iris Miliaraki, & Martin Theobald. (2014). TriAD. 289–300. 105 indexed citations

8.

Seufert, Stephan, Avishek Anand, Srikanta Bedathur, & Gerhard Weikum. (2013). FERRARI: Flexible and efficient reachability range assignment for graph indexing. 1009–1020. 72 indexed citations

9.

Gubichev, Andrey, Srikanta Bedathur, & Stephan Seufert. (2013). Sparqling kleene. 1–7. 20 indexed citations

10.

Hoffart, Johannes, Stephan Seufert, Dat Ba Nguyen, Martin Theobald, & Gerhard Weikum. (2012). KORE. 545–554. 126 indexed citations

11.

Seufert, Stephan, Srikanta Bedathur, Julián Mestre, & Gerhard Weikum. (2010). Bonsai: Growing Interesting Small Trees. Max Planck Institute for Plasma Physics. 1013–1018. 6 indexed citations

12.

Gubichev, Andrey, Srikanta Bedathur, Stephan Seufert, & Gerhard Weikum. (2010). Fast and accurate estimation of shortest paths in large graphs. Max Planck Institute for Plasma Physics. 499–508. 88 indexed citations

13.

Seufert, Stephan, et al.. (2010). Antourage. 1121–1122. 23 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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