Gregor Seiler

About

Gregor Seiler is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Gregor Seiler has authored 10 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 5 papers in Information Systems and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Gregor Seiler’s work include Cryptography and Data Security (9 papers), Cryptography and Residue Arithmetic (5 papers) and Cryptographic Implementations and Security (3 papers). Gregor Seiler is often cited by papers focused on Cryptography and Data Security (9 papers), Cryptography and Residue Arithmetic (5 papers) and Cryptographic Implementations and Security (3 papers). Gregor Seiler collaborates with scholars based in Switzerland, Germany and Taiwan. Gregor Seiler's co-authors include Vadim Lyubashevsky, Damien Stehlé, Peter Schwabe, Eike Kiltz, Tancrède Lepoint, Léo Ducas, Bo‐Yin Yang, Rafaël del Pino, Vincent Hwang and Matthias J. Kannwischer and has published in prestigious journals such as IACR Transactions on Cryptographic Hardware and Embedded Systems, Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security and 2022 IEEE International Symposium on Information Theory (ISIT).

In The Last Decade

Co-authorship network of co-authors of Gregor Seiler i

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Fields of papers citing papers by Gregor Seiler

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Gregor Seiler

Since Specialization

Citations

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