Michał Studziński

660 citations
27 papers · 441 · h-index 11

Impact in

Papers in

Michał Studziński

24 papers receiving 434 citations

Peers

Michał Studziński
Comparison fields: 5 of 35
  • Artificial Intelligence 351
  • Atomic and Molecular Physics, and Optics 321
  • Statistical and Nonlinear Physics 124
  • Geometry and Topology 30
  • Numerical Analysis 13
Replace Gen Kimura with:
Gen Kimura Japan
Sergii Strelchuk United Kingdom
Ludovico Lami Germany
Lech Jakóbczyk Poland
M. E. Shirokov Russia
Martin Fraas Switzerland
Giacomo De Palma Italy
Biswajit Dutta India
Marcelo A. Marchiolli Brazil
Guillaume Aubrun France
Michał Studziński relative to Gen Kimura Japan Gen Kimura's profile →
Citations per field
00.5×2.8×
Gen Kimura · 1×
Citations per year

Countries citing papers authored by Michał Studziński

Since Specialization
Citations

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

Fields of papers citing papers by Michał Studziński

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Michał Studziński, 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 Michał Studziński Line = papers co-authored together Michał Studziński links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015214
2 201732
3 201832
4 202216
5 201814
6 201714
7 202012
8 202111
9 202111
10 201411
11 201310
12 201210
13 201310
14 20148
15 20236
16 20215
17 20215
18 20135
19 20234
20 20144

About Michał Studziński

Michał Studziński is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Geometry and Topology, Algebra and Number Theory and Mathematical Physics, having authored 27 papers that have together received 441 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (18 papers), Quantum Computing Algorithms and Architecture (17 papers), Quantum Mechanics and Applications (11 papers), Algebraic structures and combinatorial models (7 papers), Advanced Topics in Algebra (5 papers), Quantum optics and atomic interactions (3 papers), Quantum-Dot Cellular Automata (2 papers) and Advanced Algebra and Geometry (2 papers). The work is most often cited by research in Artificial Intelligence (351 citations), Atomic and Molecular Physics, and Optics (321 citations), Statistical and Nonlinear Physics (124 citations), Geometry and Topology (30 citations) and Numerical Analysis (13 citations). Michał Studziński has collaborated with scholars based in Poland, United Kingdom and France. Frequent co-authors include Michał Horodecki, Piotr Ćwikliński, Jonathan Oppenheim, Marek Mozrzymas, Sergii Strelchuk, Nilanjana Datta, Maria Przybylska, Daniel Stilck França, Paweł Mazurek and Andrzej Grudka. Their work appears in journals such as Journal of Physics A Mathematical and Theoretical, New Journal of Physics, Quantum, IEEE Transactions on Information Theory and Physical Review Letters.

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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