Gang Xu

2.5k citations
137 papers · 1.9k indexed · 4 hit papers · h-index 23

Gang Xu

120 papers receiving 1.7k citations

Hit Papers

CBRFL: A framework for Committee-based Byza...1820242026202510203040

Peers

Gang Xu
Comparison fields: 5 of 100
  • Artificial Intelligence 1.6k
  • Atomic and Molecular Physics, and Optics 983
  • Information Systems 311
  • Computer Networks and Communications 166
  • Computational Theory and Mathematics 107
Replace Kejia Zhang with:
Kejia Zhang China
Chaoyang Li China
Xiaoyu Cao China
Zoe L. Jiang China
Angela Amphawan Malaysia
Ronghua Shi China
Muyuan Li United States
Chip Elliott United States
Saif Al‐Kuwari Qatar
Ajay Kumar India
Gang Xu relative to Kejia Zhang China Kejia Zhang's profile →
Citations per field
00.5×
Kejia Zhang · 1×
Citations per year

Countries citing papers authored by Gang Xu

Since Specialization
Citations

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

Fields of papers citing papers by Gang Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1
CBRFL: A framework for Committee-based Byzantine-Resilient Federated Learningbreakdown →
202518
2 20255
3
Anonymity-Enhanced Sequential Multi-Signer Ring Signature for Secure Medical Data Sharing in IoMTbreakdown →
202516
4
A Model Value Transfer Incentive Mechanism for Federated Learning With Smart Contracts in AIoTbreakdown →
202444
5 20236
6 20235
7 20230
8 20231
9 20233
10 202211
11 202220
12 202292
13 202220
14 20226
15 20216
16 202036
17 201929
18 201931
19 20140
20
Conservation and inheritance of nomadic culture
20104

About Gang Xu

Gang Xu is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Information Systems, having authored 137 papers that have together received 1.9k indexed citations. Recurring topics across this work include Quantum Information and Cryptography (64 papers), Quantum Computing Algorithms and Architecture (61 papers), Quantum Mechanics and Applications (41 papers), Cryptography and Data Security (40 papers), Blockchain Technology Applications and Security (23 papers), Privacy-Preserving Technologies in Data (20 papers), Complexity and Algorithms in Graphs (8 papers) and Quantum-Dot Cellular Automata (6 papers). The work is most often cited by research in Artificial Intelligence (1.6k citations), Atomic and Molecular Physics, and Optics (983 citations) and Information Systems (311 citations). Gang Xu has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Xiu‐Bo Chen, Yixian Yang, Qiaoyan Wen, Xinxin Niu, Zongpeng Li, Xiu‐Bo Chen, Mianxiong Dong, Cong Wang, Yiru Sun and Chaoyang Li. Their work appears in journals such as Quantum Information Processing, Computers, materials & continua/Computers, materials & continua (Print), Electronics, Scientific Reports and IEEE Access.

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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