Lvzhou Li

2.9k citations
161 papers · 1.9k · h-index 21

Impact in

Papers in

Lvzhou Li

146 papers receiving 1.8k citations

Peers

Lvzhou Li
Comparison fields: 5 of 93
  • Artificial Intelligence 988
  • Computational Theory and Mathematics 317
  • Atomic and Molecular Physics, and Optics 580
  • Polymers and Plastics 134
  • Mechanics of Materials 188
Replace Sijing Chen with:
Sijing Chen China
Xinmiao Liu China
Yu Lan China
Gage Hills United States
G. Schmidt Germany
Markus Becherer Germany
Zhiyi Yu China
Paolo Pavan Italy
Guangjun Xie China
Lvzhou Li relative to Sijing Chen China Sijing Chen's profile →
Citations per field
00.5×9.9×
Sijing Chen · 1×
Citations per year

Countries citing papers authored by Lvzhou Li

Since Specialization
Citations

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

Fields of papers citing papers by Lvzhou Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 161 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009154
2 2016114
3 2020103
4 2013100
5 201566
6 202356
7 202144
8 201835
9 201931
10 201830
11 201430
12 202229
13 202328
14 200828
15 202326
16 201824
17 202323
18 202322
19 200922
20 202321

About Lvzhou Li

Lvzhou Li is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computational Theory and Mathematics, Atomic and Molecular Physics, and Optics and Biomedical Engineering, having authored 161 papers that have together received 1.9k indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (78 papers), Quantum Information and Cryptography (49 papers), Quantum Mechanics and Applications (22 papers), Advanced Sensor and Energy Harvesting Materials (22 papers), Perovskite Materials and Applications (18 papers), Quantum-Dot Cellular Automata (16 papers), Computability, Logic, AI Algorithms (14 papers) and Machine Learning and Algorithms (14 papers). The work is most often cited by research in Artificial Intelligence (988 citations), Computational Theory and Mathematics (317 citations), Atomic and Molecular Physics, and Optics (580 citations), Polymers and Plastics (134 citations) and Mechanics of Materials (188 citations). Lvzhou Li has collaborated with scholars based in China, Portugal and Australia. Frequent co-authors include Daowen Qiu, Haozhen Situ, Shenggen Zheng, Paulo Mateus, Jianning Ding, Xiangfu Zou, Yu Tian, Zhimin He, Chen Xie and Xu Dong. Their work appears in journals such as Physical review. A, Theoretical Computer Science, Information and Computation, Solar Energy Materials and Solar Cells 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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