Zhiguo Qu

2.3k citations
107 papers · 1.6k indexed · 2 hit papers · h-index 24

Zhiguo Qu

102 papers receiving 1.5k citations

Hit Papers

Parallel TimesNet-BiLSTM mo...192023202620242025204060

Peers

Zhiguo Qu
Comparison fields: 5 of 111
  • Artificial Intelligence 981
  • Computer Vision and Pattern Recognition 262
  • Atomic and Molecular Physics, and Optics 378
  • Information Systems 250
  • Computational Theory and Mathematics 130
Replace Yewang Chen with:
Yewang Chen China
Huamin Yang China
Min Yao China
Hua Huang United States
Kushal Kanti Ghosh India
V. S. Shankar Sriram United States
Minjie Wang China
Fan Li China
Rabah Attia Tunisia
Zhiguo Qu relative to Yewang Chen China Yewang Chen's profile →
Citations per field
00.5×4.5×
Yewang Chen · 1×
Citations per year

Countries citing papers authored by Zhiguo Qu

Since Specialization
Citations

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

Fields of papers citing papers by Zhiguo Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202515
2 20252
3 20254
4 20245
5 20241
6 202417
7 20247
8 20242
9 20241
10 202338
11 20239
12 202314
13 202310
14 202240
15 202139
16 201932
17 201815
18 201810
19 20188
20 201854

About Zhiguo Qu

Zhiguo Qu is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Computational Theory and Mathematics, having authored 107 papers that have together received 1.6k indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (56 papers), Quantum Information and Cryptography (49 papers), Quantum Mechanics and Applications (23 papers), Quantum-Dot Cellular Automata (11 papers), Blockchain Technology Applications and Security (8 papers), Neural Networks and Reservoir Computing (6 papers), Underwater Vehicles and Communication Systems (5 papers) and ECG Monitoring and Analysis (5 papers). The work is most often cited by research in Artificial Intelligence (981 citations), Computer Vision and Pattern Recognition (262 citations) and Atomic and Molecular Physics, and Optics (378 citations). Zhiguo Qu has collaborated with scholars based in China, Ireland and Sweden. Frequent co-authors include Prayag Tiwari, Xiaojun Wang, Min Zheng, Le Sun, Ghulam Muhammad, Xiu‐Bo Chen, Yixian Yang, Ming‐Ming Wang, Naixue Xiong and Wenjie Liu. Their work appears in journals such as Quantum Information Processing, IEEE Internet of Things Journal, Science China Information Sciences, Marine Georesources and Geotechnology and IEEE Transactions on Consumer Electronics.

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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