Andrei Păun

2.5k citations
108 papers · 2.1k · h-index 21

Impact in

Papers in

Andrei Păun

104 papers receiving 1.9k citations

Peers

Andrei Păun
Comparison fields: 5 of 114
  • Computational Theory and Mathematics 639
  • Molecular Biology 1.8k
  • Mechanical Engineering 913
  • Artificial Intelligence 195
  • Electrical and Electronic Engineering 320
Replace Yuan-Jyue Chen with:
Yuan-Jyue Chen United States
Damien Woods Ireland
Ion Petre Finland
Qi Jin Cheng United States
Eduardo García Sánchez Switzerland
Randolph M. Lopez United States
David Doty United States
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Citations per field
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Citations per year

Countries citing papers authored by Andrei Păun

Since Specialization
Citations

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

Fields of papers citing papers by Andrei Păun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Andrei Păun, 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 Andrei Păun Line = papers co-authored together Andrei Păun links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 108 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002294
2 2006203
3 2015124
4 2017116
5 200795
6 201692
7 201892
8 200682
9 200978
10 200649
11 200144
12 200243
13 200338
14 200238
15 200730
16 200629
17 200625
18
Membrane systems with coupled transport: universality and normal forms
200223
19 200223
20 200622

About Andrei Păun

Andrei Păun is a scholar working on Computational Theory and Mathematics, Molecular Biology, Mechanical Engineering, Artificial Intelligence and Biophysics, having authored 108 papers that have together received 2.1k indexed citations. Recurring topics across this work include DNA and Biological Computing (76 papers), Advanced biosensing and bioanalysis techniques (51 papers), Modular Robots and Swarm Intelligence (27 papers), semigroups and automata theory (22 papers), Cellular Automata and Applications (13 papers), Advanced Memory and Neural Computing (11 papers), Algorithms and Data Compression (10 papers) and Machine Learning and Algorithms (8 papers). The work is most often cited by research in Computational Theory and Mathematics (639 citations), Molecular Biology (1.8k citations), Mechanical Engineering (913 citations), Artificial Intelligence (195 citations) and Electrical and Electronic Engineering (320 citations). Andrei Păun has collaborated with scholars based in Romania, United States and Spain. Frequent co-authors include Gheorghe Pǎun, Linqiang Pan, Alfonso Rodríguez‐Patón, Óscar H. Ibarra, Tingfang Wu, Xingyi Zhang, Mario J. Pérez-Jímenez, Zhiqiang Zhang, Mihai F. Ionescu and Rudolf Freund. Their work appears in journals such as Theoretical Computer Science, International Journal of Foundations of Computer Science, Natural Computing, Lecture notes in computer science and IEEE Transactions on Neural Networks and Learning Systems.

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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