XU Ya

104 total papers · 424 total citations
26 papers, 129 citations indexed

About

XU Ya is a scholar working on Organic Chemistry, Pathology and Forensic Medicine and Artificial Intelligence. According to data from OpenAlex, XU Ya has authored 26 papers receiving a total of 129 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Organic Chemistry, 3 papers in Pathology and Forensic Medicine and 3 papers in Artificial Intelligence. Recurrent topics in XU Ya's work include Parasitic infections in humans and animals (2 papers), Advanced Computational Techniques and Applications (2 papers) and Geophysical and Geoelectrical Methods (2 papers). XU Ya is often cited by papers focused on Parasitic infections in humans and animals (2 papers), Advanced Computational Techniques and Applications (2 papers) and Geophysical and Geoelectrical Methods (2 papers). XU Ya collaborates with scholars based in China, United States and Canada. XU Ya's co-authors include Jie Lin, Yujie Chen, Min Xia, Peiwen Guo, Xin Liu, Hua Feng, Yuan Cao, Lei Xu, Rong Li and Xiaoding Xu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science and Pollution Research and Ecotoxicology and Environmental Safety.

In The Last Decade

XU Ya

21 papers receiving 126 citations

Author Peers

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

Author						Papers	Cites
XU Ya	29	27	23	14	14	26	129
Seungjae Lee	44 1.5×	43 1.6×	26 1.1×	9 0.6×	25 1.8×	23	285
Laimdota Zizmare	16 0.6×	77 2.9×	19 0.8×	22 1.6×	6 0.4×	21	183
Ömer Faruk Türkoğlu	15 0.5×	45 1.7×	54 2.3×	8 0.6×	18 1.3×	18	227
Aleksandra Podlecka‐Piętowska	32 1.1×	62 2.3×	44 1.9×	40 2.9×	4 0.3×	31	245
Junxiang Gu	7 0.2×	46 1.7×	21 0.9×	11 0.8×	22 1.6×	28	176
Heng Zhao	7 0.2×	53 2.0×	12 0.5×	11 0.8×	31 2.2×	23	184
Karl J. Habashy	33 1.1×	65 2.4×	67 2.9×	40 2.9×	18 1.3×	23	222
Sheng Qiu	43 1.5×	28 1.0×	115 5.0×	17 1.2×	10 0.7×	17	221
Gleb Makshakov	27 0.9×	40 1.5×	93 4.0×	32 2.3×	6 0.4×	21	214
Jakob V. E. Gerstl	11 0.4×	21 0.8×	31 1.3×	6 0.4×	15 1.1×	30	161

Countries citing papers authored by XU Ya

Since Specialization

Citations

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

Fields of papers citing papers by XU Ya

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of XU Ya

This figure shows the co-authorship network connecting the top 25 collaborators of XU Ya. A scholar is included among the top collaborators of XU Ya 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 XU Ya. XU Ya 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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