Paweł Ksieniewicz

867 total citations
33 papers, 353 citations indexed

About

Paweł Ksieniewicz is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, Paweł Ksieniewicz has authored 33 papers receiving a total of 353 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 6 papers in Information Systems and 5 papers in Sociology and Political Science. Recurrent topics in Paweł Ksieniewicz's work include Data Stream Mining Techniques (13 papers), Machine Learning and Data Classification (11 papers) and Anomaly Detection Techniques and Applications (11 papers). Paweł Ksieniewicz is often cited by papers focused on Data Stream Mining Techniques (13 papers), Machine Learning and Data Classification (11 papers) and Anomaly Detection Techniques and Applications (11 papers). Paweł Ksieniewicz collaborates with scholars based in Poland, Spain and Australia. Paweł Ksieniewicz's co-authors include Michał Woźniak, Michał Choraś, Agata Giełczyk, Salvador García, Katarzyna Stąpor, Krzysztof Walkowiak, Konstantinos Demestichas, Daniel Urda, Álvaro Herrero and Bogusław Cyganek and has published in prestigious journals such as PLoS ONE, IEEE Access and Information Sciences.

In The Last Decade

Paweł Ksieniewicz

31 papers receiving 336 citations

Peers

Paweł Ksieniewicz
Comparison fields: 5 of 66
  • Artificial Intelligence 197
  • Sociology and Political Science 95
  • Information Systems 82
  • Signal Processing 58
  • Electrical and Electronic Engineering 57
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Mohamed Taha Egypt
Shengjie Wang China
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Poonam Rani India
Munish Sabharwal India
Resul Kara Türkiye
Nuria Rodríguez-Barroso Spain
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Citations per field, relative to Paweł Ksieniewicz
Paweł Ksieniewicz · 1×
Citations per year, relative to Paweł Ksieniewicz
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Countries citing papers authored by Paweł Ksieniewicz

Since Specialization
Citations

This map shows the geographic impact of Paweł Ksieniewicz'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 Paweł Ksieniewicz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paweł Ksieniewicz more than expected).

Fields of papers citing papers by Paweł Ksieniewicz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paweł Ksieniewicz. 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 Paweł Ksieniewicz. The network helps show where Paweł Ksieniewicz may publish in the future.

Co-authorship network of co-authors of Paweł Ksieniewicz

This figure shows the co-authorship network connecting the top 25 collaborators of Paweł Ksieniewicz. A scholar is included among the top collaborators of Paweł Ksieniewicz 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 Paweł Ksieniewicz. Paweł Ksieniewicz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 3
3 0
4 1
5 17
6 7
7 0
8 1
9 4
10 15
11 7
12 7
13 53
14 4
15 24
16 8
17 19
18
Dealing with the task of imbalanced, multidimensional data classification using ensembles of exposers.
2
19 2
20 2

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.

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