Michał Koziarski

901 total citations
20 papers, 546 citations indexed

About

Michał Koziarski is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Michał Koziarski has authored 20 papers receiving a total of 546 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 5 papers in Electrical and Electronic Engineering. Recurrent topics in Michał Koziarski's work include Machine Learning and Data Classification (7 papers), Imbalanced Data Classification Techniques (7 papers) and Electricity Theft Detection Techniques (5 papers). Michał Koziarski is often cited by papers focused on Machine Learning and Data Classification (7 papers), Imbalanced Data Classification Techniques (7 papers) and Electricity Theft Detection Techniques (5 papers). Michał Koziarski collaborates with scholars based in Poland, United States and Canada. Michał Koziarski's co-authors include Michał Woźniak, Bogusław Cyganek, Bartosz Krawczyk, Paweł Forczmański, Piotr Bródka, Wojciech Maleika, Stanisław Saganowski, Przemysław Kazienko, Jakub Swadźba and Bogdan Kwolek and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nature Biotechnology and PLoS ONE.

In The Last Decade

Michał Koziarski

16 papers receiving 529 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 Koziarski Poland 10 304 151 104 59 47 20 546
Xiangli Yang China 3 322 1.1× 52 0.3× 215 2.1× 17 0.3× 43 0.9× 7 670
Chan‐Yun Yang Taiwan 13 156 0.5× 74 0.5× 147 1.4× 9 0.2× 17 0.4× 69 460
Gaojuan Fan China 7 154 0.5× 61 0.4× 51 0.5× 9 0.2× 9 0.2× 15 307
Joseph Isabona Nigeria 14 90 0.3× 328 2.2× 48 0.5× 45 0.8× 48 1.0× 79 639
Alfonso Rojas‐Domínguez Mexico 12 368 1.2× 39 0.3× 244 2.3× 19 0.3× 36 0.8× 32 653
Shen Li-ming China 5 231 0.8× 40 0.3× 78 0.8× 30 0.5× 9 0.2× 8 493
Aida Ali Malaysia 8 197 0.6× 71 0.5× 55 0.5× 5 0.1× 9 0.2× 22 394
Katharina Beckh Germany 4 188 0.6× 56 0.4× 38 0.4× 26 0.4× 12 0.3× 8 493
M. Arafa Egypt 10 120 0.4× 114 0.8× 65 0.6× 25 0.4× 17 0.4× 16 543
Laura von Rueden Germany 3 187 0.6× 57 0.4× 39 0.4× 27 0.5× 13 0.3× 5 485

Countries citing papers authored by Michał Koziarski

Since Specialization
Citations

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

Fields of papers citing papers by Michał Koziarski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michał Koziarski

This figure shows the co-authorship network connecting the top 25 collaborators of Michał Koziarski. A scholar is included among the top collaborators of Michał Koziarski 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 Koziarski. Michał Koziarski 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.
Koziarski, Michał, et al.. (2025). Diverse and feasible retrosynthesis using GFlowNets. Information Sciences. 714. 122194–122194.
2.
Scalia, Gabriele, Steven T. Rutherford, Kerry R. Buchholz, et al.. (2025). Deep-learning-based virtual screening of antibacterial compounds. Nature Biotechnology.
3.
Koziarski, Michał, Álex Hernández-García, Chenghao Liu, et al.. (2024). Towards equilibrium molecular conformation generation with GFlowNets. Digital Discovery. 3(5). 1038–1047.
4.
Koziarski, Michał, et al.. (2024). DiagSet: a dataset for prostate cancer histopathological image classification. Scientific Reports. 14(1). 6780–6780. 13 indexed citations
5.
Koziarski, Michał & Michał Woźniak. (2024). Local neighborhood encodings for imbalanced data classification. Machine Learning. 113(10). 7421–7449.
6.
Batey, Robert A., et al.. (2024). RGFN: Synthesizable Molecular Generation Using GFlowNets. 46908–46955. 2 indexed citations
7.
Koziarski, Michał, et al.. (2023). Optimized hybrid imbalanced data sampling for decision tree training. 17. 339–342. 1 indexed citations
8.
Koziarski, Michał, et al.. (2022). Multicriteria Classifier Ensemble Learning for Imbalanced Data. IEEE Access. 10. 16807–16818. 13 indexed citations
9.
Cyganek, Bogusław, et al.. (2020). Classification of Histopathological Images using Scale-Invariant Feature Transform. 506–512. 3 indexed citations
10.
Koziarski, Michał, et al.. (2020). A Study on Pattern Recognition with the Histograms of Oriented Gradients in Distorted and Noisy Images. JUCS - Journal of Universal Computer Science. 26(4). 454–478. 3 indexed citations
11.
Saganowski, Stanisław, Piotr Bródka, Michał Koziarski, & Przemysław Kazienko. (2019). Analysis of group evolution prediction in complex networks. PLoS ONE. 14(10). e0224194–e0224194. 10 indexed citations
12.
13.
Krawczyk, Bartosz, Michał Koziarski, & Michał Woźniak. (2019). Radial-Based Oversampling for Multiclass Imbalanced Data Classification. IEEE Transactions on Neural Networks and Learning Systems. 31(8). 2818–2831. 85 indexed citations
14.
Koziarski, Michał, Bartosz Krawczyk, & Michał Woźniak. (2019). Radial-Based oversampling for noisy imbalanced data classification. Neurocomputing. 343. 19–33. 107 indexed citations
15.
Maleika, Wojciech, Michał Koziarski, & Paweł Forczmański. (2018). A Multiresolution Grid Structure Applied to Seafloor Shape Modeling. ISPRS International Journal of Geo-Information. 7(3). 119–119. 10 indexed citations
16.
Koziarski, Michał & Bogusław Cyganek. (2018). Impact of Low Resolution on Image Recognition with Deep Neural Networks: An Experimental Study. International Journal of Applied Mathematics and Computer Science. 28(4). 735–744. 72 indexed citations
17.
Koziarski, Michał & Michał Woźniak. (2017). CCR: A combined cleaning and resampling algorithm for imbalanced data classification. International Journal of Applied Mathematics and Computer Science. 27(4). 727–736. 83 indexed citations
18.
Koziarski, Michał & Bogusław Cyganek. (2017). Image recognition with deep neural networks in presence of noise – Dealing with and taking advantage of distortions. Integrated Computer-Aided Engineering. 24(4). 337–349. 128 indexed citations
19.
Koziarski, Michał, Bartosz Krawczyk, & Michał Woźniak. (2017). The deterministic subspace method for constructing classifier ensembles. Pattern Analysis and Applications. 20(4). 981–990. 10 indexed citations
20.
Koziarski, Michał, Bartosz Krawczyk, & Michał Woźniak. (2016). Forming Classifier Ensembles with Deterministic Feature Subspaces. SHILAP Revista de lepidopterología. 8. 89–95. 2 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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