Wu Xin

661 citations
46 papers · 469 · h-index 11

Impact in

Papers in

Wu Xin

40 papers receiving 455 citations

Peers

Wu Xin
Comparison fields: 5 of 70
  • Cellular and Molecular Neuroscience 131
  • Cognitive Neuroscience 121
  • Electrical and Electronic Engineering 336
  • Artificial Intelligence 118
  • Health Information Management 10
Replace Hongyu An with:
Hongyu An United States
Emiliano Torre Germany
Tariq Alshawi Saudi Arabia
Stephen J. Weddell New Zealand
Jorge Igual Spain
Sunghun Kim South Korea
Xudong Xie China
Andrzej Skoczeń Poland
Jacek Starzyński Poland
Wu Xin relative to Hongyu An United States Hongyu An's profile →
Citations per field
00.5×1.5×2.3×
Hongyu An · 1×
Citations per year

Countries citing papers authored by Wu Xin

Since Specialization
Citations

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

Fields of papers citing papers by Wu Xin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015117
2 201564
3 200942
4 199938
5 201529
6 201524
7 201823
8 201818
9 201814
10 202110
11 202210
12
Multiple Criteria Rainfall-Runoff Model Calibration Using a Parallel Genetic Algorithm in a Cluster of Computers
20068
13 20148
14 20177
15 20165
16 20174
17 20154
18
Contrast test of the transient electromagnetic system (CASTEM) at the Dawangzhuang iron mine in Anhui province
20164
19 20024
20 20154

About Wu Xin

Wu Xin is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience, Artificial Intelligence, Safety, Risk, Reliability and Quality and Cognitive Neuroscience, having authored 46 papers that have together received 469 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (10 papers), Neuroscience and Neural Engineering (5 papers), Geoscience and Mining Technology (5 papers), Photonic and Optical Devices (5 papers), Topic Modeling (5 papers), Ferroelectric and Negative Capacitance Devices (5 papers), Optical Network Technologies (4 papers) and Advancements in PLL and VCO Technologies (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (131 citations), Cognitive Neuroscience (121 citations), Electrical and Electronic Engineering (336 citations), Artificial Intelligence (118 citations) and Health Information Management (10 citations). Wu Xin has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Vishal Saxena, Kehan Zhu, Xiaojun Tang, Wan Kuang, N.D. Black, Philippe Lopes, Werner Dubitzky, Francisco Azuaje, John Albert White and Kristy A. Campbell. Their work appears in journals such as IEEE Transactions on Circuits & Systems II Express Briefs, Artificial Intelligence in Medicine, International Journal of Energy Research, Physica A Statistical Mechanics and its Applications and Applied Intelligence.

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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