Ya Xiao

44 total papers · 652 total citations
26 papers, 333 citations indexed

About

Ya Xiao is a scholar working on Signal Processing, Artificial Intelligence and Information Systems. According to data from OpenAlex, Ya Xiao has authored 26 papers receiving a total of 333 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Signal Processing, 13 papers in Artificial Intelligence and 12 papers in Information Systems. Recurrent topics in Ya Xiao's work include Advanced Malware Detection Techniques (15 papers), Security and Verification in Computing (8 papers) and Software Engineering Research (6 papers). Ya Xiao is often cited by papers focused on Advanced Malware Detection Techniques (15 papers), Security and Verification in Computing (8 papers) and Software Engineering Research (6 papers). Ya Xiao collaborates with scholars based in United States, China and Australia. Ya Xiao's co-authors include Danfeng Yao, Long Cheng, Guojun Peng, Ke Tian, Murat Kantarcıoğlu, Na Meng, Ying Zhang, Barton P. Miller, Shihui Zheng and Bin Sun and has published in prestigious journals such as ACM Computing Surveys, IEEE Transactions on Software Engineering and Computer.

In The Last Decade

Ya Xiao

22 papers receiving 320 citations

Author Peers

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

Author						Papers	Cites
Ya Xiao	199	167	133	123	79	26	333
Ning Lu	133 0.7×	70 0.4×	134 1.0×	182 1.5×	102 1.3×	39	386
Gabriela Ciocarlie	131 0.7×	130 0.8×	246 1.8×	106 0.9×	57 0.7×	27	351
Amir Namavar Jahromi	226 1.1×	187 1.1×	282 2.1×	88 0.7×	107 1.4×	15	395
Hequn Xian	195 1.0×	141 0.8×	198 1.5×	205 1.7×	18 0.2×	36	396
Tommaso Zoppi	212 1.1×	106 0.6×	210 1.6×	34 0.3×	63 0.8×	39	357
Stefano Iannucci	126 0.6×	69 0.4×	278 2.1×	215 1.7×	52 0.7×	25	363
Chin‐Wei Tien	117 0.6×	159 1.0×	168 1.3×	166 1.3×	22 0.3×	20	314
Waheed Ali H. M. Ghanem	230 1.2×	81 0.5×	150 1.1×	81 0.7×	28 0.4×	22	356
Abdullah Alzaqebah	179 0.9×	52 0.3×	158 1.2×	122 1.0×	31 0.4×	21	373
Chaoran Li	194 1.0×	205 1.2×	176 1.3×	107 0.9×	19 0.2×	13	380

Countries citing papers authored by Ya Xiao

Since Specialization

Citations

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

Fields of papers citing papers by Ya Xiao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ya Xiao

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