Andrei Păun

2.5k citations
77 papers · 1.3k · h-index 16

Impact in

Papers in

Andrei Păun

71 papers receiving 1.3k citations

Peers

Andrei Păun
Comparison fields: 5 of 108
  • Computational Theory and Mathematics 352
  • Molecular Biology 1.1k
  • Mechanical Engineering 561
  • Electrical and Electronic Engineering 269
  • Artificial Intelligence 96
Replace Masami Hagiya with:
Masami Hagiya Japan
Damien Woods United States
Young‐Rae Cho United States
Qi Cheng United States
Hailin Chen China
Michael Krein United States
Pei Yang United States
Randolph Lopez United States
Matteo Manica Switzerland
Nataša Jonoska United States
Andrei Păun relative to Masami Hagiya Japan Masami Hagiya's profile →
Citations per field
00.5×3.3×
Masami Hagiya · 1×
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 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002194
2 2006166
3 2017110
4 2015101
5 201688
6 201886
7 200774
8 200971
9 200663
10 200632
11 200232
12 200722
13 202118
14 201218
15 200216
16 200216
17 201315
18 201613
19 201713
20 201512

About Andrei Păun

Andrei Păun is a scholar working on Molecular Biology, Computational Theory and Mathematics, Artificial Intelligence, Mechanical Engineering and Electrical and Electronic Engineering, having authored 77 papers that have together received 1.3k indexed citations. Recurring topics across this work include DNA and Biological Computing (48 papers), Advanced biosensing and bioanalysis techniques (33 papers), semigroups and automata theory (13 papers), Modular Robots and Swarm Intelligence (12 papers), Advanced Memory and Neural Computing (9 papers), Cellular Automata and Applications (8 papers), Machine Learning and Algorithms (6 papers) and Algorithms and Data Compression (4 papers). The work is most often cited by research in Computational Theory and Mathematics (352 citations), Molecular Biology (1.1k citations), Mechanical Engineering (561 citations), Electrical and Electronic Engineering (269 citations) and Artificial Intelligence (96 citations). Andrei Păun has collaborated with scholars based in Romania, Spain and United States. Frequent co-authors include Gheorghe Pǎun, Linqiang Pan, Tingfang Wu, Alfonso Rodríguez‐Patón, Óscar H. Ibarra, Xingyi Zhang, Niculina D. Hădade, Codruţa C. Paraschivescu, Mihaela Matache and Petr Sosı́k. Their work appears in journals such as Theoretical Computer Science, International Journal of Foundations of Computer Science, Natural Computing, Journal of Crohn s and Colitis 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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