Koji Nuida

40 papers receiving 256 citations

Peers

Koji Nuida
Comparison fields: 5 of 43
  • Discrete Mathematics and Combinatorics 21
  • Artificial Intelligence 169
  • Computational Theory and Mathematics 51
  • Computer Vision and Pattern Recognition 59
  • Geometry and Topology 18
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Khodakhast Bibak United States
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Citations per year

Countries citing papers authored by Koji Nuida

Since Specialization
Citations

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

Fields of papers citing papers by Koji Nuida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200943
2 201641
3 201037
4 201715
5 201514
6 202014
7 20188
8 20188
9
Optimal Observables for Minimum-Error State Discrimination in General Probabilistic Theories
20127
10 20097
11 20187
12
Optimal probabilistic fingerprinting codes using optimal finite random variables related to numerical quadrature
20066
13 20186
14 20175
15 20164
16
Candidate Constructions of Fully Homomorphic Encryption on Finite Simple Groups without Ciphertext Noise
20154
17 20193
18
On the direct indecomposability of infinite irreducible Coxeter groups and the Isomorphism Problem of Coxeter groups
20123
19 20113
20 20093

About Koji Nuida

Koji Nuida is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Discrete Mathematics and Combinatorics, Electrical and Electronic Engineering and Geometry and Topology, having authored 46 papers that have together received 265 indexed citations. Recurring topics across this work include Cryptography and Data Security (20 papers), Coding theory and cryptography (11 papers), Advanced Combinatorial Mathematics (11 papers), graph theory and CDMA systems (9 papers), Complexity and Algorithms in Graphs (7 papers), Advanced Steganography and Watermarking Techniques (6 papers), Chaos-based Image/Signal Encryption (6 papers) and Algebraic structures and combinatorial models (5 papers). The work is most often cited by research in Discrete Mathematics and Combinatorics (21 citations), Artificial Intelligence (169 citations), Computational Theory and Mathematics (51 citations), Computer Vision and Pattern Recognition (59 citations) and Geometry and Topology (18 citations). Koji Nuida has collaborated with scholars based in Japan, Bulgaria and Czechia. Frequent co-authors include Hideki Imai, Kana Shimizu, Gen Kimura, Gunnar Rätsch, Kazumasa Shinagawa, Goichiro Hanaoka, Manabu Hagiwara, Takashi Kitagawa, Eiji Okamoto and Yuji Hashimoto. Their work appears in journals such as Designs Codes and Cryptography, Journal of Group Theory, IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, IEEE Transactions on Dependable and Secure Computing and Journal of Mathematical Cryptology.

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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