Jakub Rydzewski

1.6k citations
25 papers · 248 indexed · h-index 9
Topics
Protein Structure and Dynamics (12 papers)Machine Learning in Materials Science (6 papers)Spectroscopy and Quantum Chemical Studies (4 papers)

In The Last Decade

Jakub Rydzewski

23 papers receiving 246 citations

Peers

Jakub Rydzewski
Comparison fields: 5 of 62
  • Molecular Biology 189
  • Materials Chemistry 87
  • Computational Theory and Mathematics 52
  • Atomic and Molecular Physics, and Optics 32
  • Biomedical Engineering 24
Replace Z. Faidon Brotzakis with:
Z. Faidon Brotzakis United Kingdom
Xinqiang Ding United States
Marc Fasnacht United States
Mattia Bernetti Italy
Dahlia A. Goldfeld United States
Mookyung Cheon South Korea
Mauro L. Mugnai United States
Fahimeh Baftizadeh United States
Yuriy Khalak Germany
Sergio Bacallado United States
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Citations per field
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Citations per year

Countries citing papers authored by Jakub Rydzewski

Since Specialization
Citations

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

Fields of papers citing papers by Jakub Rydzewski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jakub Rydzewski

This figure shows the co-authorship network connecting the top 25 collaborators of Jakub Rydzewski. A scholar is included among the top collaborators of Jakub Rydzewski 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 Jakub Rydzewski. Jakub Rydzewski 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
#WorkIndexed citations
1 6
2 4
3 1
4 4
5 9
6 0
7 8
8 1
9 6
10 5
11 28
12 10
13 6
14 21
15 5
16 51
17 3
18 9
19 2
20 8

About Jakub Rydzewski

Jakub Rydzewski is a scholar working on Molecular Biology, Condensed Matter Physics and Statistical and Nonlinear Physics, having authored 25 papers that have together received 248 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (12 papers), Machine Learning in Materials Science (6 papers) and Spectroscopy and Quantum Chemical Studies (4 papers). The work is most often cited by research in Computational Theory and Mathematics (52 citations), Molecular Biology (189 citations) and Condensed Matter Physics (22 citations). Jakub Rydzewski has collaborated with scholars based in Poland, United States and Azerbaijan. Frequent co-authors include Wiesław Nowak, Ómar Valsson, Ming Chen, Helmut Grubmüller, Tushar K. Ghosh, Krzysztof Kuczera, Jacek Błażewicz, Wojciech Strzałka, Bruno Lapied and Giuseppe Nicosia. Their work appears in journals such as The Journal of Chemical Physics, The Journal of Physical Chemistry B and Scientific Reports.

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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