Thomas Seidl

138 papers and 2.6k indexed citations i.

About

Thomas Seidl is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Thomas Seidl has authored 138 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Artificial Intelligence, 45 papers in Signal Processing and 41 papers in Computer Vision and Pattern Recognition. Recurrent topics in Thomas Seidl’s work include Data Management and Algorithms (39 papers), Data Mining Algorithms and Applications (24 papers) and Advanced Clustering Algorithms Research (22 papers). Thomas Seidl is often cited by papers focused on Data Management and Algorithms (39 papers), Data Mining Algorithms and Applications (24 papers) and Advanced Clustering Algorithms Research (22 papers). Thomas Seidl collaborates with scholars based in Germany, United Kingdom and Denmark. Thomas Seidl's co-authors include Ira Assent, Hans‐Peter Kriegel, Stephan Günnemann, Reinhard Hoffmann, Emmanuel Müller, Fritz Melchers, Marwan Hassani, Antonius Rolink, H.-P. Kriegel and Austin Kulasekararaj and has published in prestigious journals such as The Journal of Experimental Medicine, Nature Communications and Blood.

In The Last Decade

Co-authorship network of co-authors of Thomas Seidl i

Fields of papers citing papers by Thomas Seidl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Thomas Seidl

Since Specialization
Citations

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

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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2025