Jan Bouda

557 citations
15 papers · 141 · h-index 7

Impact in

Papers in

Jan Bouda

12 papers receiving 137 citations

Peers

Jan Bouda
Comparison fields: 5 of 19
  • Artificial Intelligence 130
  • Atomic and Molecular Physics, and Optics 108
  • Computer Vision and Pattern Recognition 27
  • Computational Theory and Mathematics 15
  • Hardware and Architecture 4
Replace Si-Ran Zhao with:
Si-Ran Zhao China
Carl A. Miller United States
Ziyue Hua China
Jingzheng Huang China
Hou-Man Chin Denmark
André Chailloux France
Youwei Zhao China
Andrea Coladangelo United States
Akinori Kawachi Japan
Haoran Zhang China
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Citations per field
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Citations per year

Countries citing papers authored by Jan Bouda

Since Specialization
Citations

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

Fields of papers citing papers by Jan Bouda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Jan Bouda, 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 Jan Bouda Line = papers co-authored together Jan Bouda links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 201240
2 200125
3 201418
4 200717
5 200213
6 201110
7 20086
8 20094
9 20143
10 20122
11 20112
12
Encryption and authentication in SECOQC
20061
13 20240
14
New directions in quantum cryptography
20080
15 20030

About Jan Bouda

Jan Bouda is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Computer Vision and Pattern Recognition, Computer Networks and Communications and Statistical and Nonlinear Physics, having authored 15 papers that have together received 141 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (13 papers), Quantum Information and Cryptography (10 papers), Quantum Mechanics and Applications (7 papers), Chaos-based Image/Signal Encryption (2 papers), Cryptography and Data Security (2 papers), Internet Traffic Analysis and Secure E-voting (2 papers), Statistical Mechanics and Entropy (1 paper) and Computability, Logic, AI Algorithms (1 paper). The work is most often cited by research in Artificial Intelligence (130 citations), Atomic and Molecular Physics, and Optics (108 citations), Computer Vision and Pattern Recognition (27 citations), Computational Theory and Mathematics (15 citations) and Hardware and Architecture (4 citations). Jan Bouda has collaborated with scholars based in Czechia, Slovakia and United Kingdom. Frequent co-authors include Vladimír Bužek, Matej Pivoluska, Martin Plesch, Nikola Paunković, Paulo Mateus, Marcin Pawłowski, Mátyás Koniorczyk, Daniel Reitzner, Oliver Maurhart and Rajagopal Nagarajan. Their work appears in journals such as Physical Review A, Theoretical Computer Science, The European Physical Journal D, Journal of Modern Optics and Quantum Information Processing.

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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