Sebastian Brechtel
- Automotive Engineering top 1%
- Control and Systems Engineering top 5%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Safety, Risk, Reliability and Quality top 2%
- Topics
- Autonomous Vehicle Technology and Safety (5 papers)Bayesian Modeling and Causal Inference (5 papers)Target Tracking and Data Fusion in Sensor Networks (5 papers)
- Journals
- IEEE Intelligent Transportation Systems MagazineInternational Conference on Machine LearningRepository KITopen (Karlsruhe Institute of Technology)
- Partner nations
- Germany
In The Last Decade
Sebastian Brechtel
9 papers receiving 661 citations
Peers
Comparison fields: 5 of 45
- Automotive Engineering 527
- Control and Systems Engineering 244
- Computer Vision and Pattern Recognition 203
- Artificial Intelligence 171
- Safety, Risk, Reliability and Quality 142
Countries citing papers authored by Sebastian Brechtel
This map shows the geographic impact of Sebastian Brechtel'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 Sebastian Brechtel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sebastian Brechtel more than expected).
Fields of papers citing papers by Sebastian Brechtel
This network shows the impact of papers produced by Sebastian Brechtel. 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 Sebastian Brechtel. The network helps show where Sebastian Brechtel may publish in the future.
Co-authorship network of co-authors of Sebastian Brechtel
This figure shows the co-authorship network connecting the top 25 collaborators of Sebastian Brechtel. A scholar is included among the top collaborators of Sebastian Brechtel 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 Sebastian Brechtel. Sebastian Brechtel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 140 | |
| 3 | 198 | |
| 4 | Solving Continuous POMDPs: Value Iteration with Incremental Learning of an Efficient Space Representation | 24 |
| 5 | 44 | |
| 6 | 45 | |
| 7 | 152 | |
| 8 | 19 | |
| 9 | 56 |
About Sebastian Brechtel
Sebastian Brechtel is a scholar working on Automotive Engineering, Artificial Intelligence and Building and Construction, having authored 9 papers that have together received 681 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (5 papers), Bayesian Modeling and Causal Inference (5 papers) and Target Tracking and Data Fusion in Sensor Networks (5 papers). The work is most often cited by research in Automotive Engineering (527 citations), Safety, Risk, Reliability and Quality (142 citations) and Control and Systems Engineering (244 citations). Sebastian Brechtel has collaborated with scholars based in Germany. Frequent co-authors include Tobias Gindele, Rüdiger Dillmann, Joachim Schröder and R. Dillmann. Their work appears in journals such as IEEE Intelligent Transportation Systems Magazine, International Conference on Machine Learning and Repository KITopen (Karlsruhe Institute of Technology).
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.