Shudi Yang

545 citations
28 papers · 358 · h-index 12

Impact in

Papers in

Shudi Yang

27 papers receiving 342 citations

Peers

Shudi Yang
Comparison fields: 5 of 28
  • Discrete Mathematics and Combinatorics 61
  • Artificial Intelligence 321
  • Computer Networks and Communications 143
  • Electrical and Electronic Engineering 213
  • Computational Theory and Mathematics 52
Replace Michael E. O’Sullivan with:
Michael E. O’Sullivan United States
Ragnar Freij-Hollanti Finland
Iwan Duursma United States
S.M. Dodunekov Bulgaria
Juriaan Simonis Netherlands
Rongquan Feng China
Maozhi Xu China
Shuqin Fan China
Xiaoni Du China
Nicolas Sendrier France
Shudi Yang relative to Michael E. O’Sullivan United States Michael E. O’Sullivan's profile →
Citations per field
00.5×3.6×
Michael E. O’Sullivan · 1×
Citations per year

Countries citing papers authored by Shudi Yang

Since Specialization
Citations

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

Fields of papers citing papers by Shudi Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside Shudi Yang, 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 Shudi Yang Line = papers co-authored together Shudi Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201652
2 201744
3 201840
4 201538
5 201625
6 201821
7 201517
8 201916
9 201714
10 201814
11 201814
12 201712
13 20179
14 20206
15 20185
16 20204
17 20204
18 20234
19 20193
20 20193

About Shudi Yang

Shudi Yang is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Networks and Communications, Computational Theory and Mathematics and Discrete Mathematics and Combinatorics, having authored 28 papers that have together received 358 indexed citations. Recurring topics across this work include Coding theory and cryptography (25 papers), graph theory and CDMA systems (18 papers), Cooperative Communication and Network Coding (8 papers), Finite Group Theory Research (4 papers), Cellular Automata and Applications (3 papers), Cryptographic Implementations and Security (3 papers), Quantum Computing Algorithms and Architecture (2 papers) and Error Correcting Code Techniques (2 papers). The work is most often cited by research in Discrete Mathematics and Combinatorics (61 citations), Artificial Intelligence (321 citations), Computer Networks and Communications (143 citations), Electrical and Electronic Engineering (213 citations) and Computational Theory and Mathematics (52 citations). Shudi Yang has collaborated with scholars based in China, South Korea and Spain. Frequent co-authors include Zheng‐an Yao, Chengju Li, Chunming Tang, Chang‐An Zhao, Qin Yue, Haode Yan, Hao Liu, Jae-Hyun Ahn, Yansheng Wu and Stephen S.‐T. Yau. Their work appears in journals such as Advances in Mathematics of Communications, Finite Fields and Their Applications, IEEE Access, Discrete Mathematics and Cryptography and Communications.

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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