Xinya Wu

637 citations
13 papers · 499 · 1 hit paper · h-index 8

Impact in

Papers in

Xinya Wu

13 papers receiving 491 citations

Xinya Wu's Hit Papers

A hybrid classification autoencoder for semi-supervised fault diagnosis in rotating machinery 2020 · 202 citations
2020+2+4Years since publication50100150200

Peers

Xinya Wu
Comparison fields: 5 of 58
  • Control and Systems Engineering 218
  • Computer Networks and Communications 109
  • Polymers and Plastics 59
  • Signal Processing 40
  • Artificial Intelligence 113
Replace Xiaoyu Fang with:
Xiaoyu Fang China
Md. Nazmul Hasan Bangladesh
Yao Wang China
Shize Huang China
MyungKeun Yoon South Korea
L.A.L. de Almeida Brazil
Cheng Luo China
Xinya Wu relative to Xiaoyu Fang China Xiaoyu Fang's profile →
Citations per field
00.5×3.7×
Xiaoyu Fang · 1×
Citations per year

Countries citing papers authored by Xinya Wu

Since Specialization
Citations

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

Fields of papers citing papers by Xinya Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1
A hybrid classification autoencoder for semi-supervised fault diagnosis in rotating machinery
Hit paper breakdown →
2020202
2 2021101
3 201358
4 201952
5 201321
6 202218
7 202017
8 202014
9 20247
10 20215
11 20252
12 20241
13 20251

About Xinya Wu

Xinya Wu is a scholar working on Materials Chemistry, Computer Networks and Communications, Artificial Intelligence, Organic Chemistry and Civil and Structural Engineering, having authored 13 papers that have together received 499 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (4 papers), Catalytic Processes in Materials Science (3 papers), Engineering Diagnostics and Reliability (2 papers), Thermal Radiation and Cooling Technologies (2 papers), Software System Performance and Reliability (2 papers), Machine Fault Diagnosis Techniques (2 papers), Catalysis and Oxidation Reactions (2 papers) and Fault Detection and Control Systems (2 papers). The work is most often cited by research in Control and Systems Engineering (218 citations), Computer Networks and Communications (109 citations), Polymers and Plastics (59 citations), Signal Processing (40 citations) and Artificial Intelligence (113 citations). Xinya Wu has collaborated with scholars based in China and Hong Kong. Frequent co-authors include Zhike Peng, Changming Cheng, Yan Zhang, Shien‐Ping Feng, Yijie Mu, Yonghong Chen, Kelong Ao, Jingkui Qu, Yang Luo and Zhiwen Zhou. Their work appears in journals such as IEEE Communications Letters, Nature Communications, ACS Nano, Journal of environmental chemical engineering and Applied Surface Science.

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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