Xuejun Liu

737 total citations
32 papers, 190 citations indexed

About

Xuejun Liu is a scholar working on Psychiatry and Mental health, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Xuejun Liu has authored 32 papers receiving a total of 190 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Psychiatry and Mental health, 7 papers in Artificial Intelligence and 6 papers in Computer Networks and Communications. Recurrent topics in Xuejun Liu's work include Schizophrenia research and treatment (6 papers), Data Management and Algorithms (4 papers) and Anomaly Detection Techniques and Applications (4 papers). Xuejun Liu is often cited by papers focused on Schizophrenia research and treatment (6 papers), Data Management and Algorithms (4 papers) and Anomaly Detection Techniques and Applications (4 papers). Xuejun Liu collaborates with scholars based in China, United States and Japan. Xuejun Liu's co-authors include Tingting Ge, He Huang, Hong Liu, Anne Marie Salapatek, William Barchuk, Hualiang Jiang, Shiyu Chen, Jingkang Shen, Hongbo He and Xinru Chen and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of Allergy and Clinical Immunology.

In The Last Decade

Xuejun Liu

30 papers receiving 183 citations

Peers

Xuejun Liu
Comparison fields: 5 of 87
  • Physiology 44
  • Psychiatry and Mental health 39
  • Organic Chemistry 34
  • Molecular Biology 21
  • Computer Networks and Communications 15
Replace M. Waite with:
M. Waite United States
James L. Barnes United States
Thomas K. Shaughnessy United States
Haruhiko Takeuchi Japan
Mingxuan Wang China
Himanshu Verma India
Hao Shu China
Parul Verma United States
Olavi Kilkku Finland
Keith McCormack United Kingdom
M. Waite United States View profile →
Citations per field, relative to Xuejun Liu
Xuejun Liu · 1×
Citations per year, relative to Xuejun Liu
Xuejun Liu · 1×

Countries citing papers authored by Xuejun Liu

Since Specialization
Citations

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

Fields of papers citing papers by Xuejun Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xuejun Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Xuejun Liu. A scholar is included among the top collaborators of Xuejun 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 Xuejun Liu. Xuejun 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 2
2 5
3 0
4 4
5 3
6 4
7 2
8 3
9 10
10 1
11 11
12
A new algorithm for finding the k shortest transport paths in dynamic stochastic networks
2
13
Outlier Time Series Detection Based on WSN
0
14 24
15 35
16 3
17 1
18 32
19
Terrain Complexity Index and Its Derivation from DEMs
5
20
Dynamic Parameter Spring Modeling Algorithm for Graph Drawing
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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