Qingyao Wu

60 total papers · 1.2k total citations
38 papers, 594 citations indexed

About

Qingyao Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Qingyao Wu has authored 38 papers receiving a total of 594 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 7 papers in Electrical and Electronic Engineering. Recurrent topics in Qingyao Wu's work include Domain Adaptation and Few-Shot Learning (4 papers), Stock Market Forecasting Methods (3 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Qingyao Wu is often cited by papers focused on Domain Adaptation and Few-Shot Learning (4 papers), Stock Market Forecasting Methods (3 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Qingyao Wu collaborates with scholars based in China, Hong Kong and United Kingdom. Qingyao Wu's co-authors include Pengshuai Yin, Chuangxin Guo, Xiaoxin Zhou, Junpeng Zhan, Yuguang Yan, Huaqing Min, Hanrui Wu, Peilin Zhao, Bin Li and Junzhou Huang and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Power Systems and Expert Systems with Applications.

In The Last Decade

Qingyao Wu

36 papers receiving 572 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Qingyao Wu	182	176	161	97	63	38	594
Necaattin Barışçı	118 0.6×	90 0.5×	133 0.8×	117 1.2×	42 0.7×	58	526
Bayram Akdemïr	130 0.7×	203 1.2×	212 1.3×	73 0.8×	10 0.2×	43	616
Mohaimenul Azam Khan Raiaan	92 0.5×	220 1.3×	87 0.5×	40 0.4×	23 0.4×	25	545
Pan Su	278 1.5×	176 1.0×	168 1.0×	16 0.2×	39 0.6×	29	611
Aamir Shahzad	148 0.8×	121 0.7×	167 1.0×	20 0.2×	33 0.5×	46	677
Manas Ranjan Senapati	111 0.6×	257 1.5×	141 0.9×	68 0.7×	11 0.2×	48	539
Awais Mehmood	151 0.8×	194 1.1×	219 1.4×	30 0.3×	16 0.3×	23	532
Ebenezer Daniel	129 0.7×	78 0.4×	223 1.4×	37 0.4×	78 1.2×	23	530
Siyamalan Manivannan	143 0.8×	216 1.2×	192 1.2×	45 0.5×	16 0.3×	38	579
José Luis Vázquez Noguera	83 0.5×	78 0.4×	233 1.4×	106 1.1×	7 0.1×	62	612

Countries citing papers authored by Qingyao Wu

Since Specialization

Citations

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

Fields of papers citing papers by Qingyao Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qingyao Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Qingyao Wu. A scholar is included among the top collaborators of Qingyao Wu 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 Qingyao Wu. Qingyao Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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