Jacek Koronacki
- Molecular Biology
- Artificial Intelligence top 10%
- Statistics and Probability top 5%
- Computer Vision and Pattern Recognition
- Information Systems
- Co-authors
- Michał DramińskiJan KomorowskiStefan EnrothClaes WadeliusÁlvaro Rada-IglesiasJoost N. KokAndrzej SkowronStan Matwin
- Topics
- Bayesian Methods and Mixture Models (6 papers)Statistical Methods and Inference (5 papers)Advanced Statistical Process Monitoring (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of the American Statistical AssociationBioinformatics
- Partner nations
- PolandUnited StatesSweden
In The Last Decade
Jacek Koronacki
26 papers receiving 483 citations
Peers
Comparison fields: 5 of 131
- Molecular Biology 178
- Artificial Intelligence 172
- Statistics and Probability 52
- Computer Vision and Pattern Recognition 50
- Information Systems 43
Countries citing papers authored by Jacek Koronacki
This map shows the geographic impact of Jacek Koronacki'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 Jacek Koronacki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacek Koronacki more than expected).
Fields of papers citing papers by Jacek Koronacki
This network shows the impact of papers produced by Jacek Koronacki. 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 Jacek Koronacki. The network helps show where Jacek Koronacki may publish in the future.
Co-authorship network of co-authors of Jacek Koronacki
This figure shows the co-authorship network connecting the top 25 collaborators of Jacek Koronacki. A scholar is included among the top collaborators of Jacek Koronacki 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 Jacek Koronacki. Jacek Koronacki is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 11 | |
| 3 | 25 | |
| 4 | 23 | |
| 5 | 3 | |
| 6 | 7 | |
| 7 | 21 | |
| 8 | 198 | |
| 9 | Proceedings of the 18th European conference on Machine Learning | 16 |
| 10 | Statistical process control : the deming paradigm and beyond | 15 |
| 11 | 8 | |
| 12 | Testing for a difference between conditional variance functions of nonlinear time series | 1 |
| 13 | 6 | |
| 14 | 2 | |
| 15 | 1 | |
| 16 | 20 | |
| 17 | 1 | |
| 18 | 1 | |
| 19 | 0 | |
| 20 | 11 |
About Jacek Koronacki
Jacek Koronacki is a scholar working on Statistics, Probability and Uncertainty, Statistics and Probability and Virology, having authored 30 papers that have together received 523 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (6 papers), Statistical Methods and Inference (5 papers) and Advanced Statistical Process Monitoring (5 papers). The work is most often cited by research in Statistics and Probability (52 citations), Artificial Intelligence (172 citations) and Statistics, Probability and Uncertainty (22 citations). Jacek Koronacki has collaborated with scholars based in Poland, United States and Sweden. Frequent co-authors include Michał Dramiński, Jan Komorowski, Stefan Enroth, Claes Wadelius, Álvaro Rada-Iglesias, Joost N. Kok, Andrzej Skowron, Stan Matwin, Stan Lipovetsky and W. Feluch. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Bioinformatics.
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.