Birgit Kirsch
Impact in
- Health Informatics top 10%
- Artificial Intelligence top 10%
- Topic Modeling
- Explainable Artificial Intelligence (XAI)
- Anomaly Detection Techniques and Applications
- Neural Networks and Applications
Papers in
-
- Natural Language Processing Techniques 2
- Advanced Text Analysis Techniques 2
- Topic Modeling 2
- Logic, Reasoning, and Knowledge 1
- Machine Learning and Algorithms 1
- Semantic Web and Ontologies 1
-
- Public Relations and Crisis Communication 2
- Co-authors
- Sven Giesselbach (3 shared papers)Katharina Beckh (1 shared paper)Christian Bauckhage (1 shared paper)Laura von Rueden (1 shared paper)Jochen Garcke (1 shared paper)Rajkumar Ramamurthy (1 shared paper)Michał Walczak (1 shared paper)Julius Pfrommer (1 shared paper)
- Journals
- IEEE Transactions on Knowledge and Data Engineering (1 paper)Sensors (1 paper)Communications in computer and information science (1 paper)Fraunhofer-Publica (Fraunhofer-Gesellschaft) (2 papers)SpringerBriefs in criminology (1 paper)
In The Last Decade
Birgit Kirsch
5 papers receiving 574 citations
Birgit Kirsch's Hit Papers
Peers
Comparison fields: 5 of 113
- Health Informatics 11
- Artificial Intelligence 210
- Statistical and Nonlinear Physics 54
- Control and Systems Engineering 76
- Industrial and Manufacturing Engineering 34
Countries citing papers authored by Birgit Kirsch
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
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 24 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.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems Hit paper breakdown → | 2021 | 526 |
| 2 | 2017 | 56 | |
| 3 | 2018 | 4 | |
| 4 | 2020 | 3 | |
| 5 | 2022 | 2 | |
| 6 | 2025 | 0 |
About Birgit Kirsch
Birgit Kirsch is a scholar working on Artificial Intelligence, Communication, Information Systems, Statistical and Nonlinear Physics and Epidemiology, having authored 6 papers that have together received 591 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (2 papers), Public Relations and Crisis Communication (2 papers), Advanced Text Analysis Techniques (2 papers), Topic Modeling (2 papers), Logic, Reasoning, and Knowledge (1 paper), Machine Learning and Algorithms (1 paper), Semantic Web and Ontologies (1 paper) and Data-Driven Disease Surveillance (1 paper). The work is most often cited by research in Health Informatics (11 citations), Artificial Intelligence (210 citations), Statistical and Nonlinear Physics (54 citations), Control and Systems Engineering (76 citations) and Industrial and Manufacturing Engineering (34 citations). Birgit Kirsch has collaborated with scholars based in Germany, Austria and Italy. Frequent co-authors include Sven Giesselbach, Katharina Beckh, Christian Bauckhage, Laura von Rueden, Jochen Garcke, Rajkumar Ramamurthy, Michał Walczak, Julius Pfrommer, Sebastian Mayer and Bogdan Georgiev. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Sensors, Communications in computer and information science, Fraunhofer-Publica (Fraunhofer-Gesellschaft) and SpringerBriefs in criminology.
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.