Igor T. Podolak

54 total papers · 444 total citations
25 papers, 192 citations indexed

About

Igor T. Podolak is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Igor T. Podolak has authored 25 papers receiving a total of 192 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 6 papers in Computational Theory and Mathematics. Recurrent topics in Igor T. Podolak's work include Neural Networks and Applications (6 papers), Machine Learning and Data Classification (4 papers) and Fuzzy Logic and Control Systems (4 papers). Igor T. Podolak is often cited by papers focused on Neural Networks and Applications (6 papers), Machine Learning and Data Classification (4 papers) and Fuzzy Logic and Control Systems (4 papers). Igor T. Podolak collaborates with scholars based in Poland, South Korea and United States. Igor T. Podolak's co-authors include Seong‐Whan Lee, Sabina Podlewska, Jacek Tabor, Stanisław Jastrzȩbski, Agnieszka Galanty, Dominika Dudek, Magdalena Fąfrowicz, Adrian Andrzej Chrobak, Bartosz Zieliński and Irma Podolak and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and Computer Physics Communications.

In The Last Decade

Igor T. Podolak

25 papers receiving 179 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Igor T. Podolak	60	57	30	26	26	25	192
Paresh Rawat	39 0.7×	74 1.3×	32 1.1×	27 1.0×	24 0.9×	37	234
Sonja Georgievska	53 0.9×	38 0.7×	64 2.1×	76 2.9×	33 1.3×	19	264
Albert Gu	78 1.3×	39 0.7×	22 0.7×	26 1.0×	5 0.2×	20	168
Deng Pan	90 1.5×	30 0.5×	18 0.6×	12 0.5×	49 1.9×	21	237
Shiyang Chen	48 0.8×	45 0.8×	9 0.3×	6 0.2×	16 0.6×	27	146
Zaid Bassfar	69 1.1×	112 2.0×	24 0.8×	12 0.5×	4 0.2×	32	247
Paul Prasse	73 1.2×	31 0.5×	8 0.3×	30 1.2×	43 1.7×	27	235
Yin-Te Tsai	91 1.5×	21 0.4×	39 1.3×	64 2.5×	8 0.3×	27	227
Zhizhe Liu	113 1.9×	54 0.9×	9 0.3×	24 0.9×	36 1.4×	17	245
Xi Zhou	106 1.8×	49 0.9×	16 0.5×	9 0.3×	6 0.2×	25	241

Countries citing papers authored by Igor T. Podolak

Since Specialization

Citations

This map shows the geographic impact of Igor T. Podolak'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 Igor T. Podolak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Igor T. Podolak more than expected).

Fields of papers citing papers by Igor T. Podolak

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Igor T. Podolak. 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 Igor T. Podolak. The network helps show where Igor T. Podolak may publish in the future.

Co-authorship network of co-authors of Igor T. Podolak

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

All Works

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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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