Xiaolan Liu

848 citations
59 papers · 685 · h-index 15

Impact in

Papers in

Xiaolan Liu

56 papers receiving 668 citations

Peers

Xiaolan Liu
Comparison fields: 5 of 105
  • Computational Mathematics 34
  • Metals and Alloys 57
  • Biomaterials 97
  • Computer Vision and Pattern Recognition 115
  • Materials Chemistry 225
Replace Ahmet Cecen with:
Ahmet Cecen United States
Kun Wei China
Thomas Carraro Germany
Enrui Zhang China
Zhenze Yang United States
Zhilei Wang Japan
Tianyu Huang China
Haiyou Huang China
Yu Shi China
Ryan Cohn United States
Xiaolan Liu relative to Ahmet Cecen United States Ahmet Cecen's profile →
Citations per field
00.5×11.3×
Ahmet Cecen · 1×
Citations per year

Countries citing papers authored by Xiaolan Liu

Since Specialization
Citations

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

Fields of papers citing papers by Xiaolan Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200876
2 201867
3 200947
4 202046
5 202042
6 202037
7 201831
8 201526
9 200922
10 201722
11 201722
12 201721
13 202019
14 200917
15 201915
16 201014
17 201412
18 202111
19 201811
20 201811

About Xiaolan Liu

Xiaolan Liu is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Computational Mechanics, Materials Chemistry and Molecular Biology, having authored 59 papers that have together received 685 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (11 papers), Face and Expression Recognition (8 papers), Chalcogenide Semiconductor Thin Films (8 papers), Quantum Dots Synthesis And Properties (6 papers), Image and Signal Denoising Methods (6 papers), Remote-Sensing Image Classification (4 papers), Semiconductor Quantum Structures and Devices (3 papers) and Corrosion Behavior and Inhibition (3 papers). The work is most often cited by research in Computational Mathematics (34 citations), Metals and Alloys (57 citations), Biomaterials (97 citations), Computer Vision and Pattern Recognition (115 citations) and Materials Chemistry (225 citations). Xiaolan Liu has collaborated with scholars based in China, United States and Iran. Frequent co-authors include Xiaowei Yang, Guozhe Meng, Fuhui Wang, Yawei Shao, Le Han, Tao Zhang, Hao Wang, Xianmin Zhang, Tonghui Yang and Naiqiang Yin. Their work appears in journals such as Journal of Intelligent & Fuzzy Systems, Materials Science in Semiconductor Processing, Applied Intelligence, Corrosion Science and Journal of Nanoparticle Research.

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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