Artur Gramacki
- Artificial Intelligence
- Control and Systems Engineering top 10%
- Cognitive Neuroscience
- Computer Vision and Pattern Recognition
- Signal Processing
- Co-authors
- Barbara MorawinAgnieszka Zembroń-ŁacnyAnna TylutkaKrzysztof GałkowskiEric RogersD.H. OwensMarek KowalJózef Korbicz
- Topics
- Iterative Learning Control Systems (9 papers)Metallurgy and Cultural Artifacts (3 papers)Model Reduction and Neural Networks (3 papers)
- Cited by
- ArcheologyEquineSignal Processing
- Journals
- PLoS ONEScientific ReportsNutrients
- Partner nations
- PolandUnited KingdomDenmark
In The Last Decade
Artur Gramacki
23 papers receiving 418 citations
Peers
Comparison fields: 5 of 134
- Artificial Intelligence 86
- Control and Systems Engineering 66
- Cognitive Neuroscience 49
- Computer Vision and Pattern Recognition 39
- Signal Processing 38
Countries citing papers authored by Artur Gramacki
This map shows the geographic impact of Artur Gramacki'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 Artur Gramacki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Artur Gramacki more than expected).
Fields of papers citing papers by Artur Gramacki
This network shows the impact of papers produced by Artur Gramacki. 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 Artur Gramacki. The network helps show where Artur Gramacki may publish in the future.
Co-authorship network of co-authors of Artur Gramacki
This figure shows the co-authorship network connecting the top 25 collaborators of Artur Gramacki. A scholar is included among the top collaborators of Artur Gramacki 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 Artur Gramacki. Artur Gramacki 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 | 0 | |
| 3 | 48 | |
| 4 | 12 | |
| 5 | 20 | |
| 6 | 44 | |
| 7 | 165 | |
| 8 | 11 | |
| 9 | 13 | |
| 10 | 18 | |
| 11 | 1 | |
| 12 | Szacowanie emisji tlenków azotu (NOx) na podstawie danych eksploatacyjnych rzeczywistego obiektu przemysłowego | 0 |
| 13 | Java based toolbox for linear repetitive processesn. | 1 |
| 14 | 1 | |
| 15 | 0 | |
| 16 | From Continuous to Discrete Models of Linear Repetitive Processes | 1 |
| 17 | 26 | |
| 18 | On a New Method of Discretization of Differential Linear Repetitive Processes | 1 |
| 19 | On the stability properties of discrete approximations to the dynamics of differential linear repetitive processes | 1 |
| 20 | 1 |
About Artur Gramacki
Artur Gramacki is a scholar working on Archeology, Equine and Biological Psychiatry, having authored 27 papers that have together received 428 indexed citations. Recurring topics across this work include Iterative Learning Control Systems (9 papers), Metallurgy and Cultural Artifacts (3 papers) and Model Reduction and Neural Networks (3 papers). The work is most often cited by research in Archeology (8 citations), Equine (10 citations) and Signal Processing (38 citations). Artur Gramacki has collaborated with scholars based in Poland, United Kingdom and Denmark. Frequent co-authors include Barbara Morawin, Agnieszka Zembroń-Łacny, Anna Tylutka, Krzysztof Gałkowski, Eric Rogers, D.H. Owens, Marek Kowal, Józef Korbicz, Thomas Birch and Hieronim Frąckowiak. Their work appears in journals such as PLoS ONE, Scientific Reports and Nutrients.
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.