Birgit Kirsch

891 citations
3 papers · 519 indexed · 1 hit paper · h-index 2

Impact in

Papers in

Birgit Kirsch

3 papers receiving 498 citations

Hit Papers

Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems 2021 · 469 citations
4692021202620222024100200300400

Peers

Birgit Kirsch
Comparison fields: 5 of 110
  • Health Informatics 11
  • Artificial Intelligence 183
  • Statistical and Nonlinear Physics 49
  • Control and Systems Engineering 68
  • Communication 20
Replace Anna Kruspe with:
Anna Kruspe Germany
Ning Xie China
Štefan Dlugolinský Slovakia
Wenxin Jiang China
Haifeng Zhao China
George Almpanidis China
Bogdan Georgiev Germany
Laura von Rueden Germany
Rajkumar Ramamurthy Germany
Birgit Kirsch relative to Anna Kruspe Germany Anna Kruspe's profile →
Citations per field
00.5×3.7×
Anna Kruspe · 1×
Citations per year

Countries citing papers authored by Birgit Kirsch

Since Specialization
Citations

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

Fields of papers citing papers by Birgit Kirsch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Birgit Kirsch, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Birgit Kirsch Line = papers co-authored together Birgit Kirsch links everyone, so they are left out of the graph.

All Works

3 of 3 papers shown
#Work
1
Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems
Hit paper breakdown →
2021469
2 201749
3 20221

About Birgit Kirsch

Birgit Kirsch is a scholar working on Geography, Planning and Development, Communication, Statistical and Nonlinear Physics, Artificial Intelligence and Epidemiology, having authored 3 papers that have together received 519 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (1 paper), Natural Language Processing Techniques (1 paper), Machine Learning and Algorithms (1 paper), Logic, Reasoning, and Knowledge (1 paper), Neural Networks and Applications (1 paper), Public Relations and Crisis Communication (1 paper), Model Reduction and Neural Networks (1 paper) and Data-Driven Disease Surveillance (1 paper). The work is most often cited by research in Health Informatics (11 citations), Artificial Intelligence (183 citations), Statistical and Nonlinear Physics (49 citations), Control and Systems Engineering (68 citations) and Communication (20 citations). Birgit Kirsch has collaborated with scholars based in Germany, Switzerland and Italy. Frequent co-authors include Sebastian Mayer, Jochen Garcke, Raoul Heese, Michał Walczak, Katharina Beckh, Julius Pfrommer, Bogdan Georgiev, Christian Bauckhage, Sven Giesselbach and Rajkumar Ramamurthy. Their work appears in journals such as Sensors, IEEE Transactions on Knowledge and Data Engineering and Fraunhofer-Publica (Fraunhofer-Gesellschaft).

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026