Michał Kozielski

570 total citations
29 papers, 336 citations indexed

About

Michał Kozielski is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Michał Kozielski has authored 29 papers receiving a total of 336 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 4 papers in Control and Systems Engineering. Recurrent topics in Michał Kozielski's work include Handwritten Text Recognition Techniques (6 papers), Natural Language Processing Techniques (5 papers) and Fault Detection and Control Systems (4 papers). Michał Kozielski is often cited by papers focused on Handwritten Text Recognition Techniques (6 papers), Natural Language Processing Techniques (5 papers) and Fault Detection and Control Systems (4 papers). Michał Kozielski collaborates with scholars based in Poland, Germany and Slovakia. Michał Kozielski's co-authors include Hermann Ney, Patrick Doetsch, Marek Sikora, Łukasz Wróbel, Jens Förster, Dominik Ślȩzak, Marek Grzegorowski, Sebastian Stawicki, Andrzej Janusz and Sinh Hoa Nguyen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Sensors.

In The Last Decade

Michał Kozielski

26 papers receiving 311 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michał Kozielski Poland 9 173 162 37 24 22 29 336
Rifat Edizkan Türkiye 8 187 1.1× 76 0.5× 39 1.1× 38 1.6× 13 0.6× 33 388
Benjamin Yao United States 12 275 1.6× 447 2.8× 31 0.8× 38 1.6× 13 0.6× 23 616
M.A. Saleem Durai India 6 145 0.8× 193 1.2× 21 0.6× 6 0.3× 13 0.6× 29 368
Huanhuan Chen China 6 200 1.2× 110 0.7× 36 1.0× 32 1.3× 15 0.7× 10 380
Inzamam Mashood Nasir Pakistan 14 177 1.0× 183 1.1× 26 0.7× 14 0.6× 11 0.5× 28 489
S. Praveena India 7 117 0.7× 77 0.5× 22 0.6× 25 1.0× 8 0.4× 41 352
Fiza Murtaza Pakistan 11 146 0.8× 220 1.4× 11 0.3× 7 0.3× 21 1.0× 24 372
Mohammed Ali Saudi Arabia 10 102 0.6× 89 0.5× 96 2.6× 26 1.1× 9 0.4× 16 323
Md. Haidar Sharif Türkiye 12 181 1.0× 136 0.8× 14 0.4× 16 0.7× 22 1.0× 33 336

Countries citing papers authored by Michał Kozielski

Since Specialization
Citations

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

Fields of papers citing papers by Michał Kozielski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michał Kozielski

This figure shows the co-authorship network connecting the top 25 collaborators of Michał Kozielski. A scholar is included among the top collaborators of Michał Kozielski 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 Michał Kozielski. Michał Kozielski 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
1.
Kozielski, Michał, et al.. (2025). Towards consistency of rule-based explainer and black box model — Fusion of rule induction and XAI-based feature importance. Knowledge-Based Systems. 311. 113092–113092. 3 indexed citations
2.
Borys, Damian & Michał Kozielski. (2024). Classification of flotation froth images using neural networks with explanations. Procedia Computer Science. 246. 910–919.
3.
Kozielski, Michał. (2023). Contextual Explanations for Decision Support in Predictive Maintenance. Applied Sciences. 13(18). 10068–10068. 5 indexed citations
4.
Kozielski, Michał, et al.. (2022). Rule-based approximation of black-box classifiers for tabular data to generate global and local explanations. SHILAP Revista de lepidopterología. 30. 89–92. 2 indexed citations
5.
Kozielski, Michał, et al.. (2022). RuleXAI—A package for rule-based explanations of machine learning model. SoftwareX. 20. 101209–101209. 13 indexed citations
6.
Kozielski, Michał, Małgorzata Bach, Aleksandra Gruca, et al.. (2021). Screening Support System Based on Patient Survey Data—Case Study on Classification of Initial, Locally Collected COVID-19 Data. Applied Sciences. 11(22). 10790–10790. 5 indexed citations
7.
Żyła, Joanna, Małgorzata Bach, Aleksandra Werner, et al.. (2021). Symptom-based early-stage differentiation between SARS-CoV-2 versus other respiratory tract infections—Upper Silesia pilot study. Scientific Reports. 11(1). 13580–13580. 5 indexed citations
8.
Kozielski, Michał, Aleksandra Gruca, Joanna Żyła, et al.. (2021). Enhancement of COVID-19 symptom-based screening with quality-based classifier optimisation. Bulletin of the Polish Academy of Sciences Technical Sciences. 137349–137349. 2 indexed citations
9.
Kozielski, Michał, Marek Sikora, & Łukasz Wróbel. (2021). Data on methane concentration collected by underground coal mine sensors. SHILAP Revista de lepidopterología. 39. 107457–107457. 10 indexed citations
10.
Kozielski, Michał, et al.. (2021). A Sensor Data-Driven Decision Support System for Liquefied Petroleum Gas Suppliers. Applied Sciences. 11(8). 3474–3474. 2 indexed citations
11.
Kozielski, Michał, et al.. (2021). Sensor-Based Predictive Maintenance with Reduction of False Alarms—A Case Study in Heavy Industry. Sensors. 22(1). 226–226. 19 indexed citations
12.
Ślȩzak, Dominik, Marek Grzegorowski, Andrzej Janusz, et al.. (2018). A framework for learning and embedding multi-sensor forecasting models into a decision support system: A case study of methane concentration in coal mines. Information Sciences. 451-452. 112–133. 51 indexed citations
13.
Kozielski, Michał & Aleksandra Gruca. (2014). Soft Approach to Identification of Cohesive Clusters in Two Gene Representations. Procedia Computer Science. 35. 281–289. 3 indexed citations
14.
Kozielski, Michał, et al.. (2014). Towards Unsupervised Learning for Handwriting Recognition. 1. 549–554. 5 indexed citations
15.
Kozielski, Michał, et al.. (2014). Multilingual Off-Line Handwriting Recognition in Real-World Images. 26. 121–125. 8 indexed citations
16.
Harȩżlak, Katarzyna & Michał Kozielski. (2013). Metody analizy sieci kryminalnych. Digital Library of the Silesian University of Technology (Silesian University of Technology). 31. 35–46.
17.
Kozielski, Michał & Aleksandra Gruca. (2013). Visual comparison of clustering gene ontology with different similarity measures. Studia Informatica System and information technology. 32. 169–180. 1 indexed citations
18.
Kozielski, Michał, Jens Förster, & Hermann Ney. (2012). Moment-Based Image Normalization for Handwritten Text Recognition. 256–261. 27 indexed citations
19.
Sikora, Marek & Michał Kozielski. (2006). Hybrid Data Exploration Methods to Prediction Tasks Solving. 18(1). 57–74. 2 indexed citations
20.
Kozielski, Michał. (2006). Improving the Results and Performance of Clustering Bit-encoded XML Documents. 60–64. 4 indexed citations

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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