David Suendermann

15 papers and 82 indexed citations i.

About

David Suendermann is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, David Suendermann has authored 15 papers receiving a total of 82 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 2 papers in Signal Processing and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in David Suendermann’s work include Speech and dialogue systems (12 papers), Natural Language Processing Techniques (8 papers) and Topic Modeling (6 papers). David Suendermann is often cited by papers focused on Speech and dialogue systems (12 papers), Natural Language Processing Techniques (8 papers) and Topic Modeling (6 papers). David Suendermann collaborates with scholars based in Germany, United States and Pakistan. David Suendermann's co-authors include Jackson Liscombe, Roberto Pieraccini, Keelan Evanini, Hermann Ney, Antonio Bonafonte, Wolfgang Minker, Michael Scholz, Alexander Schmitt and Guoqiang Li and has published in prestigious journals such as International Journal of Artificial Intelligence Tools, CiteSeer X (The Pennsylvania State University) and North American Chapter of the Association for Computational Linguistics.

In The Last Decade

Co-authorship network of co-authors of David Suendermann i

Fields of papers citing papers by David Suendermann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by David Suendermann

Since Specialization
Citations

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