D. Wilk-Kołodziejczyk

440 total citations
61 papers, 292 citations indexed

About

D. Wilk-Kołodziejczyk is a scholar working on Mechanical Engineering, Industrial and Manufacturing Engineering and Materials Chemistry. According to data from OpenAlex, D. Wilk-Kołodziejczyk has authored 61 papers receiving a total of 292 indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Mechanical Engineering, 16 papers in Industrial and Manufacturing Engineering and 14 papers in Materials Chemistry. Recurrent topics in D. Wilk-Kołodziejczyk's work include Surface Treatment and Coatings (16 papers), Materials Engineering and Processing (14 papers) and Manufacturing Process and Optimization (12 papers). D. Wilk-Kołodziejczyk is often cited by papers focused on Surface Treatment and Coatings (16 papers), Materials Engineering and Processing (14 papers) and Manufacturing Process and Optimization (12 papers). D. Wilk-Kołodziejczyk collaborates with scholars based in Poland, Czechia and United Kingdom. D. Wilk-Kołodziejczyk's co-authors include Krzysztof Regulski, G. Gumienny, Bartłomiej Śnieżyński, M. Głowacki, Marek Hawryluk, K.P. Korona, Kamil Wróbel, Piotr Długosz and Aleksander Byrski and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of Alloys and Compounds.

In The Last Decade

D. Wilk-Kołodziejczyk

51 papers receiving 270 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. Wilk-Kołodziejczyk Poland 11 191 73 70 66 24 61 292
Krzysztof Regulski Poland 10 166 0.9× 66 0.9× 70 1.0× 60 0.9× 26 1.1× 55 279
M. Perzyk Poland 10 209 1.1× 33 0.5× 55 0.8× 125 1.9× 20 0.8× 46 322
Mingfa Zheng China 9 131 0.7× 126 1.7× 25 0.4× 52 0.8× 21 0.9× 19 273
Gaoyang Li China 6 47 0.2× 91 1.2× 21 0.3× 19 0.3× 29 1.2× 9 346
Jiayin Wang China 11 85 0.4× 63 0.9× 13 0.2× 92 1.4× 34 1.4× 59 389
Hongchang Zhang China 11 101 0.5× 13 0.2× 14 0.2× 25 0.4× 17 0.7× 50 282
Mourad Zegrari Morocco 10 61 0.3× 7 0.1× 30 0.4× 59 0.9× 21 0.9× 40 322
Norfadzlan Yusup Malaysia 4 245 1.3× 6 0.1× 13 0.2× 116 1.8× 39 1.6× 13 370
P. S. Ranjit India 14 120 0.6× 47 0.6× 6 0.1× 10 0.2× 24 1.0× 41 426

Countries citing papers authored by D. Wilk-Kołodziejczyk

Since Specialization
Citations

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

Fields of papers citing papers by D. Wilk-Kołodziejczyk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. Wilk-Kołodziejczyk. 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 D. Wilk-Kołodziejczyk. The network helps show where D. Wilk-Kołodziejczyk may publish in the future.

Co-authorship network of co-authors of D. Wilk-Kołodziejczyk

This figure shows the co-authorship network connecting the top 25 collaborators of D. Wilk-Kołodziejczyk. A scholar is included among the top collaborators of D. Wilk-Kołodziejczyk 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 D. Wilk-Kołodziejczyk. D. Wilk-Kołodziejczyk 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.
Wilk-Kołodziejczyk, D., et al.. (2025). Analysis of the impact of selected factors on the occurrence of corrosion in a specific material using neural networks. Journal of Alloys and Compounds. 1040. 183640–183640. 1 indexed citations
2.
Wilk-Kołodziejczyk, D., et al.. (2024). Decision Support Tool in the Selection of Powder for 3D Printing. Materials. 17(8). 1873–1873. 4 indexed citations
3.
Wilk-Kołodziejczyk, D., et al.. (2024). Analysis of the possibility of using exploration and learning algorithms in the production of castings. Archives of Civil and Mechanical Engineering. 25(1). 1 indexed citations
4.
Wilk-Kołodziejczyk, D., et al.. (2024). Analysis of the Possibility of Making a Digital Twin for Devices Operating in Foundries. Electronics. 13(2). 349–349. 2 indexed citations
5.
Wilk-Kołodziejczyk, D., et al.. (2023). Modification of Casting Production Parameters in Order to Obtain Products with the Assumed Parameters with Using Machine Learning. International Journal of Metalcasting. 17(4). 2680–2688. 3 indexed citations
6.
Wilk-Kołodziejczyk, D., et al.. (2023). Selection of casting production parameters with the use of machine learning and data supplementation methods in order to obtain products with the assumed parameters. Archives of Civil and Mechanical Engineering. 23(2). 4 indexed citations
7.
Wilk-Kołodziejczyk, D., et al.. (2022). Prediction of Selected Mechanical Properties in Austempered Ductile Iron with Different Wall Thickness by the Decision Support Systems. Archives of Foundry Engineering. 137–144. 2 indexed citations
8.
Regulski, Krzysztof, et al.. (2017). Approximation of Ausferrite Content in the Compacted Graphite Iron with the Use of Combined Techniques of Data Mining. Archives of Foundry Engineering. 17(3). 117–122. 4 indexed citations
9.
Wilk-Kołodziejczyk, D., et al.. (2016). Mathematical formalisms to represent knowledge concerning the production process of austempered ductile iron. SHILAP Revista de lepidopterología. 6 indexed citations
10.
Wilk-Kołodziejczyk, D.. (2016). Supporting the Manufacturing Process of Metal Products with the Methods of Artificial Intelligence. Archives of Metallurgy and Materials. 61(4). 1995–1998. 4 indexed citations
11.
Regulski, Krzysztof, et al.. (2016). Computer-Assisted Methods of the Design of New Materials in the Domain of Copper Alloy Manufacturing. Key engineering materials. 682. 143–150. 2 indexed citations
12.
Śnieżyński, Bartłomiej, et al.. (2015). The recommendation system knowledge representation and reasoning procedures under uncertainty for metal casting. Metalurgija. 54(1). 263–266. 3 indexed citations
13.
Wilk-Kołodziejczyk, D., et al.. (2014). Computer-Assisted Integration of Knowledge in the Context of Identification of the Causes of Defects in Castings. Archives of Metallurgy and Materials. 59(2). 743–746. 11 indexed citations
14.
Wilk-Kołodziejczyk, D., et al.. (2011). Acquisition of technology knowledge from online information sources. Archives of Foundry Engineering. 107–112. 2 indexed citations
15.
Wilk-Kołodziejczyk, D., et al.. (2010). Diagnosis of casting defects using uncertain and incomplete knowledge. Archives of Metallurgy and Materials. 827–836. 17 indexed citations
16.
Wilk-Kołodziejczyk, D., et al.. (2010). Attribute-based knowledge representation in the process of defect diagnosis. Archives of Metallurgy and Materials. 819–826. 11 indexed citations
17.
Byrski, Aleksander, et al.. (2008). Optimization Of Simulation Model Parameters For Solidification Of Metals With Use Of Agent-Based Evolutionary Algorithm. SHILAP Revista de lepidopterología. 1 indexed citations
18.
Wilk-Kołodziejczyk, D., et al.. (2007). The logistic of plausible reasoning in the diagnosis of castings defects. Archives of Metallurgy and Materials. 375–380. 12 indexed citations
19.
Wilk-Kołodziejczyk, D., et al.. (2007). Knowledge Representation of Casting Metal Defects by Means of Ontology. Archives of Foundry Engineering. 75–78. 7 indexed citations
20.
Wilk-Kołodziejczyk, D., et al.. (2004). Problem budowy bazy wiedzy dla potrzeb diagnostyki wad wyrobów metalowych. HUTNIK - WIADOMOŚCI HUTNICZE. 71. 265–270. 1 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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