Philipp Seidl

7 papers and 92 indexed citations i.

About

Philipp Seidl is a scholar working on Materials Chemistry, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Philipp Seidl has authored 7 papers receiving a total of 92 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Materials Chemistry, 3 papers in Artificial Intelligence and 3 papers in Computational Theory and Mathematics. Recurrent topics in Philipp Seidl’s work include Machine Learning in Materials Science (4 papers), Computational Drug Discovery Methods (3 papers) and Machine Learning in Healthcare (2 papers). Philipp Seidl is often cited by papers focused on Machine Learning in Materials Science (4 papers), Computational Drug Discovery Methods (3 papers) and Machine Learning in Healthcare (2 papers). Philipp Seidl collaborates with scholars based in Austria, United States and United Kingdom. Philipp Seidl's co-authors include Sepp Hochreiter, Philipp Renz, Günter Klambauer, Marwin Segler, Jörg K. Wegner, Jonas Verhoeven, Natalia Dyubankova, Andreu Vall, Markus Hofmarcher and Andreas Mayr and has published in prestigious journals such as Journal of Chemical Information and Modeling, Faraday Discussions and Journal of Clinical Anesthesia.

In The Last Decade

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

Fields of papers citing papers by Philipp Seidl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Philipp Seidl

Since Specialization
Citations

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