Jiashuo Liu

743 total citations
30 papers, 285 citations indexed

About

Jiashuo Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Ecology. According to data from OpenAlex, Jiashuo Liu has authored 30 papers receiving a total of 285 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 4 papers in Ecology. Recurrent topics in Jiashuo Liu's work include Domain Adaptation and Few-Shot Learning (4 papers), High voltage insulation and dielectric phenomena (3 papers) and Microbial Community Ecology and Physiology (3 papers). Jiashuo Liu is often cited by papers focused on Domain Adaptation and Few-Shot Learning (4 papers), High voltage insulation and dielectric phenomena (3 papers) and Microbial Community Ecology and Physiology (3 papers). Jiashuo Liu collaborates with scholars based in China, United States and Hong Kong. Jiashuo Liu's co-authors include Peng Cui, Liping Li, Ziting Zhang, Junjian Wang, Jiangming Mo, Yan Zheng, Quanhui Ye, Wei Zhang, Jintao Li and Yinghui Wang and has published in prestigious journals such as Water Research, Soil Biology and Biochemistry and Green Chemistry.

In The Last Decade

Jiashuo Liu

26 papers receiving 282 citations

Peers

Jiashuo Liu
Comparison fields: 5 of 75
  • Artificial Intelligence 94
  • Ecology 56
  • Geophysics 40
  • Soil Science 37
  • Information Systems 32
Replace Cheng Su with:
Cheng Su China
Yini Wang China
Jordan Bell United States
Huan Xu China
Yunzhao Li China
Lixiang Liu China
Yunfei Liu China
Elisabeth Schöepfer Germany
Nizom Farmonov Hungary
Min Ji Germany
Cheng Su China View profile →
Citations per field, relative to Jiashuo Liu
Jiashuo Liu · 1×
Citations per year, relative to Jiashuo Liu
Jiashuo Liu · 1×

Countries citing papers authored by Jiashuo Liu

Since Specialization
Citations

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

Fields of papers citing papers by Jiashuo Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiashuo Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Jiashuo Liu. A scholar is included among the top collaborators of Jiashuo Liu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jiashuo Liu. Jiashuo Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 7
2 0
3 2
4 0
5 1
6 3
7 5
8 3
9 2
10 33
11 2
12 16
13 40
14
Integrated Latent Heterogeneity and Invariance Learning in Kernel Space
0
15 13
16 19
17 90
18 23
19 1
20 1

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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