Xian Wu

13.1k citations
453 papers · 7.7k indexed · 2 hit papers · h-index 43

Impact in

Papers in

Xian Wu

405 papers receiving 7.4k citations

Hit Papers

Large language models for generative information extraction: a survey 2024 · 71 citations
71201020262015202050100150200

Peers

Xian Wu
Comparison fields: 5 of 210
  • Applied Mathematics 1.2k
  • Computational Theory and Mathematics 1.1k
  • Health Informatics 84
  • Artificial Intelligence 1.8k
  • Computational Mathematics 28
Replace Runze Li with:
Runze Li United States
Yurong Liu China
Quan Z. Sheng Australia
Wen Zhang China
Xiaotong Shen United States
Theodoros Evgeniou France
Ming Yuan United States
Hong Wang China
Hong Yan Hong Kong
Shuai Liu China
Xian Wu relative to Runze Li United States Runze Li's profile →
Citations per field
00.5×5.6×
Runze Li · 1×
Citations per year

Countries citing papers authored by Xian Wu

Since Specialization
Citations

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

Fields of papers citing papers by Xian Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20255
3 20252
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5 202420
6 20249
7 20242
8 20243
9 202412
10 20240
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12 20237
13 202322
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15 20231
16 20220
17 202216
18 20214
19 202122
20 20160

About Xian Wu

Xian Wu is a scholar working on Applied Mathematics, Health Informatics, Computational Theory and Mathematics, Artificial Intelligence and Numerical Analysis, having authored 453 papers that have together received 7.7k indexed citations. Recurring topics across this work include Nonlinear Partial Differential Equations (50 papers), Topic Modeling (43 papers), Nonlinear Differential Equations Analysis (39 papers), Optimization and Variational Analysis (24 papers), Advanced Mathematical Modeling in Engineering (22 papers), Recommender Systems and Techniques (20 papers), Multimodal Machine Learning Applications (16 papers) and Machine Learning in Healthcare (16 papers). The work is most often cited by research in Applied Mathematics (1.2k citations), Computational Theory and Mathematics (1.1k citations), Health Informatics (84 citations), Artificial Intelligence (1.8k citations) and Computational Mathematics (28 citations). Xian Wu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Shen Ge, Yong Yu, Fenglin Liu, Bitao Cheng, Lei Zhang, Wei Fan, Zhaopeng Qiu, Yuexian Zou, Wei Fan and Fukun Zhao. Their work appears in journals such as Journal of Mathematical Analysis and Applications, Nonlinear Analysis, Computers & Mathematics with Applications, ACM Transactions on Information Systems and Journal of Hazardous Materials.

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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