Christian Wirth
- Artificial Intelligence top 5%
- Software top 5%
- Hardware and Architecture top 10%
- Computer Networks and Communications
- Information Systems top 10%
- Co-authors
- Johannes FürnkranzGerhard NeumannHanspeter MössenböckHerbert PrähoferChristian HumerAndreas WößJudith Eckle‐KohlerIryna Gurevych
- Topics
- Model-Driven Software Engineering Techniques (6 papers)Software Engineering Research (5 papers)Reinforcement Learning in Robotics (5 papers)
- Journals
- IEEE Transactions on Industrial InformaticsJournal of Machine Learning ResearchACM SIGPLAN Notices
- Partner nations
- AustriaGermanyUnited States
In The Last Decade
Christian Wirth
21 papers receiving 268 citations
Peers
Comparison fields: 5 of 48
- Artificial Intelligence 217
- Software 58
- Hardware and Architecture 54
- Computer Networks and Communications 49
- Information Systems 48
Countries citing papers authored by Christian Wirth
This map shows the geographic impact of Christian Wirth'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 Christian Wirth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christian Wirth more than expected).
Fields of papers citing papers by Christian Wirth
This network shows the impact of papers produced by Christian Wirth. 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 Christian Wirth. The network helps show where Christian Wirth may publish in the future.
Co-authorship network of co-authors of Christian Wirth
This figure shows the co-authorship network connecting the top 25 collaborators of Christian Wirth. A scholar is included among the top collaborators of Christian Wirth based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Christian Wirth. Christian Wirth is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 37 | |
| 3 | 32 | |
| 4 | 5 | |
| 5 | 24 | |
| 6 | 36 | |
| 7 | 8 | |
| 8 | EPMC: Every Visit Preference Monte Carlo for Reinforcement Learning | 4 |
| 9 | 3 | |
| 10 | Preference-Based Reinforcement Learning: A Preliminary Survey | 4 |
| 11 | 10 | |
| 12 | UBY - A Large-Scale Unified Lexical-Semantic Resource Based on LMF | 67 |
| 13 | 3 | |
| 14 | 27 | |
| 15 | 8 | |
| 16 | 3 | |
| 17 | 2 | |
| 18 | Monaco: A DSL Approach for Programming Automation Systems | 8 |
| 19 | 2 | |
| 20 | 1 |
About Christian Wirth
Christian Wirth is a scholar working on Software, Hardware and Architecture and Artificial Intelligence, having authored 23 papers that have together received 306 indexed citations. Recurring topics across this work include Model-Driven Software Engineering Techniques (6 papers), Software Engineering Research (5 papers) and Reinforcement Learning in Robotics (5 papers). The work is most often cited by research in Software (58 citations), Hardware and Architecture (54 citations) and Artificial Intelligence (217 citations). Christian Wirth has collaborated with scholars based in Austria, Germany and United States. Frequent co-authors include Johannes Fürnkranz, Gerhard Neumann, Hanspeter Mössenböck, Herbert Prähofer, Christian Humer, Andreas Wöß, Judith Eckle‐Kohler, Iryna Gurevych, Christian M. Meyer and Silvana Hartmann. Their work appears in journals such as IEEE Transactions on Industrial Informatics, Journal of Machine Learning Research and ACM SIGPLAN Notices.
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.