Xiaowei Ying

939 total citations
13 papers, 458 citations indexed

About

Xiaowei Ying is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Computer Networks and Communications. According to data from OpenAlex, Xiaowei Ying has authored 13 papers receiving a total of 458 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Statistical and Nonlinear Physics and 3 papers in Computer Networks and Communications. Recurrent topics in Xiaowei Ying's work include Complex Network Analysis Techniques (7 papers), Privacy-Preserving Technologies in Data (5 papers) and Internet Traffic Analysis and Secure E-voting (5 papers). Xiaowei Ying is often cited by papers focused on Complex Network Analysis Techniques (7 papers), Privacy-Preserving Technologies in Data (5 papers) and Internet Traffic Analysis and Secure E-voting (5 papers). Xiaowei Ying collaborates with scholars based in United States and China. Xiaowei Ying's co-authors include Xintao Wu, Ling Guo, Kai Pan, Daniel Barbará, Zhi‐Hua Zhou, Aidong Lu, Zhi Zhou and Lane Harrison and has published in prestigious journals such as IEEE Transactions on Knowledge and Data Engineering, Knowledge and Information Systems and International Joint Conference on Artificial Intelligence.

In The Last Decade

Xiaowei Ying

13 papers receiving 434 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Xiaowei Ying United States	10	372	232	113	70	45	13	458
Traian Marius Truţă United States	13	310 0.8×	225 1.0×	36 0.3×	117 1.7×	46 1.0×	36	437
Disha Makhija United States	2	162 0.4×	39 0.2×	126 1.1×	90 1.3×	42 0.9×	2	251
Bogdan Cautis France	10	137 0.4×	42 0.2×	58 0.5×	74 1.1×	127 2.8×	35	279
Zhengyou Xia China	10	128 0.3×	52 0.2×	179 1.6×	85 1.2×	94 2.1×	31	326
Yuqing Zhu China	12	93 0.3×	44 0.2×	223 2.0×	74 1.1×	75 1.7×	41	349
Shubha U. Nabar United States	8	230 0.6×	111 0.5×	34 0.3×	75 1.1×	82 1.8×	13	316
Xiaobin Rui China	11	118 0.3×	69 0.3×	219 1.9×	43 0.6×	54 1.2×	24	329
Lotfi Ben Romdhane Tunisia	13	158 0.4×	46 0.2×	355 3.1×	87 1.2×	100 2.2×	29	471
Yabing Yao China	11	141 0.4×	50 0.2×	317 2.8×	39 0.6×	44 1.0×	28	375
Nishith Pathak United States	8	97 0.3×	70 0.3×	188 1.7×	90 1.3×	49 1.1×	16	306

Countries citing papers authored by Xiaowei Ying

Since Specialization

Citations

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

Fields of papers citing papers by Xiaowei Ying

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaowei Ying

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

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

1.

Ying, Xiaowei, et al.. (2012). Examining spectral space of complex networks with positive and negative links. 1(1). 91–91. 11 indexed citations

2.

Ying, Xiaowei, et al.. (2011). Line orthogonality in adjacency eigenspace with application to community partition. International Joint Conference on Artificial Intelligence. 2349–2354. 18 indexed citations

3.

Ying, Xiaowei, Xintao Wu, & Daniel Barbará. (2011). Spectrum based fraud detection in social networks. 912–923. 28 indexed citations

4.

Ying, Xiaowei, et al.. (2010). Reconstruction from Randomized Graph via Low Rank Approximation. 60–71. 18 indexed citations

5.

Harrison, Lane, et al.. (2010). Interactive detection of network anomalies via coordinated multiple views. 91–101. 8 indexed citations

6.

Ying, Xiaowei, et al.. (2010). Spectrum based fraud detection in social networks. 747–749. 7 indexed citations

7.

Ying, Xiaowei & Xintao Wu. (2010). On link privacy in randomizing social networks. Knowledge and Information Systems. 28(3). 645–663. 40 indexed citations

8.

Guo, Ling, Xiaowei Ying, & Xintao Wu. (2010). On Attribute Disclosure in Randomization Based Privacy Preserving Data Publishing. 466–473. 6 indexed citations

9.

Ying, Xiaowei, et al.. (2010). A Spectrum-Based Framework for Quantifying Randomness of Social Networks. IEEE Transactions on Knowledge and Data Engineering. 23(12). 1842–1856. 9 indexed citations

10.

Ying, Xiaowei & Xintao Wu. (2009). On Randomness Measures for Social Networks. 709–720. 16 indexed citations

11.

Ying, Xiaowei & Xintao Wu. (2009). Graph Generation with Prescribed Feature Constraints. 966–977. 41 indexed citations

12.

Ying, Xiaowei, Kai Pan, Xintao Wu, & Ling Guo. (2009). Comparisons of randomization and K-degree anonymization schemes for privacy preserving social network publishing. 1–10. 51 indexed citations

13.

Ying, Xiaowei & Xintao Wu. (2008). Randomizing Social Networks: a Spectrum Preserving Approach. 739–750. 205 indexed citations

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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