Konrad Giżyński

22 papers receiving 315 citations

Peers

Konrad Giżyński
Comparison fields: 5 of 65
  • Cellular and Molecular Neuroscience 85
  • Computer Networks and Communications 93
  • Condensed Matter Physics 38
  • Biomedical Engineering 139
  • Statistical and Nonlinear Physics 30
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Jean Anne C. Incorvia United States
Kurtis D. Cantley United States
Д. В. Гусейнов Russia
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Abu Kausar Malaysia
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Hirotada Honda Japan
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Countries citing papers authored by Konrad Giżyński

Since Specialization
Citations

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

Fields of papers citing papers by Konrad Giżyński

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Konrad Giżyński, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Konrad Giżyński Line = papers co-authored together Konrad Giżyński links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201543
2 201543
3 201731
4 201429
5 201724
6
Droplets with information processing ability
201123
7 201722
8 201721
9 201615
10 202314
11 201712
12 20229
13 20228
14 20237
15 20235
16 20165
17 20223
18 20242
19 20202
20 20231

About Konrad Giżyński

Konrad Giżyński is a scholar working on Biomedical Engineering, Computer Networks and Communications, Statistical and Nonlinear Physics, Electrical and Electronic Engineering and Materials Chemistry, having authored 23 papers that have together received 321 indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (6 papers), Slime Mold and Myxomycetes Research (6 papers), Advanced Thermodynamics and Statistical Mechanics (5 papers), Electrowetting and Microfluidic Technologies (3 papers), Micro and Nano Robotics (3 papers), Pickering emulsions and particle stabilization (3 papers), Photoreceptor and optogenetics research (3 papers) and Nanomaterials and Printing Technologies (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (85 citations), Computer Networks and Communications (93 citations), Condensed Matter Physics (38 citations), Biomedical Engineering (139 citations) and Statistical and Nonlinear Physics (30 citations). Konrad Giżyński has collaborated with scholars based in Poland, Germany and South Korea. Frequent co-authors include Jerzy Górecki, Jan Guzowski, Piotr Garstecki, Bartosz A. Grzybowski, Peter Dittrich, Gerd Gruenert, J. Górecka, Taehoon Lee, Bashar Ibrahim and Zhijie Yang. Their work appears in journals such as Physical Chemistry Chemical Physics, Advanced Materials, Materials & Design, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences and Journal of Biomedical Materials Research Part B Applied Biomaterials.

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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