Xin Dang

747 total citations
44 papers, 462 citations indexed

About

Xin Dang is a scholar working on Statistics and Probability, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Xin Dang has authored 44 papers receiving a total of 462 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Statistics and Probability, 20 papers in Artificial Intelligence and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Xin Dang's work include Advanced Statistical Methods and Models (20 papers), Statistical Methods and Inference (18 papers) and Statistical Methods and Bayesian Inference (7 papers). Xin Dang is often cited by papers focused on Advanced Statistical Methods and Models (20 papers), Statistical Methods and Inference (18 papers) and Statistical Methods and Bayesian Inference (7 papers). Xin Dang collaborates with scholars based in United States, China and South Korea. Xin Dang's co-authors include Zhi Xiao, Robert Serfling, Yixin Chen, Henry L. Bart, Ying Han Pang, Dawn Wilkins, Yichuan Zhao, Wei Liang, Zhijian Yu and Tingyi Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Environmental Management.

In The Last Decade

Xin Dang

37 papers receiving 431 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xin Dang United States 11 190 146 91 69 55 44 462
Pakize Taylan Türkiye 10 75 0.4× 64 0.4× 17 0.2× 70 1.0× 52 0.9× 19 398
Jack C. Lee Taiwan 14 272 1.4× 422 2.9× 42 0.5× 68 1.0× 12 0.2× 24 703
Mogens Bladt Denmark 16 110 0.6× 264 1.8× 9 0.1× 205 3.0× 57 1.0× 42 686
Zheng Tracy Ke United States 12 113 0.6× 113 0.8× 16 0.2× 40 0.6× 9 0.2× 31 357
Cheng–Der Fuh Taiwan 13 94 0.5× 135 0.9× 14 0.2× 99 1.4× 14 0.3× 57 426
Eric S. Fung Hong Kong 8 64 0.3× 27 0.2× 22 0.2× 36 0.5× 20 0.4× 16 275
Krzysztof Jajuga Poland 9 166 0.9× 61 0.4× 27 0.3× 67 1.0× 41 0.7× 52 359
Zaven A. Karian United States 11 90 0.5× 200 1.4× 5 0.1× 60 0.9× 23 0.4× 26 464
Joan del Castillo Spain 10 74 0.4× 182 1.2× 6 0.1× 29 0.4× 20 0.4× 32 399
Naftali A. Langberg United States 13 88 0.5× 432 3.0× 14 0.2× 126 1.8× 9 0.2× 52 664

Countries citing papers authored by Xin Dang

Since Specialization
Citations

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

Fields of papers citing papers by Xin Dang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xin Dang

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

All Works

20 of 20 papers shown
1.
Zhang, Ya, et al.. (2025). Near-natural conversion of plantations primarily enhances the abundance and functionality of nematodes within medium-sized soil aggregates. Journal of Environmental Management. 378. 124751–124751. 3 indexed citations
2.
Mo, Jiangming, et al.. (2025). Compound Flood Risk Assessment of Extreme Rainfall and High River Water Level. Water. 17(6). 841–841.
3.
Dang, Xin, et al.. (2024). Grouped feature screening for ultrahigh-dimensional classification via Gini distance correlation. Journal of Multivariate Analysis. 204. 105360–105360. 1 indexed citations
4.
Dang, Xin, et al.. (2024). Asymptotic normality of a modified estimator of Gini distance correlation. Statistical Papers. 65(8). 4843–4860.
5.
Dang, Xin, et al.. (2023). Unadjusted Langevin Algorithm for Non-convex Weakly Smooth Potentials. Communications in Mathematics and Statistics. 13(4). 979–1036. 2 indexed citations
6.
Dang, Xin, et al.. (2023). Asymptotic normality of Gini correlation in high dimension with applications to the K-sample problem. Electronic Journal of Statistics. 17(2). 4 indexed citations
7.
Li, Tingyi, Wei Liang, Zhijian Yu, & Xin Dang. (2020). Analysis of the Influence of Entrepreneur’s Psychological Capital on Employee’s Innovation Behavior Under Leader-Member Exchange Relationship. Frontiers in Psychology. 11. 1853–1853. 21 indexed citations
8.
Dang, Xin, et al.. (2020). Two symmetric and computationally efficient Gini correlations. SHILAP Revista de lepidopterología. 8(1). 373–395. 1 indexed citations
9.
Zhang, Silu, et al.. (2019). Estimating Feature-Label Dependence Using Gini Distance Statistics. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(6). 1947–1963. 13 indexed citations
10.
Dang, Xin, et al.. (2019). Empirical likelihood test for diagonal symmetry. Statistics & Probability Letters. 156. 108595–108595. 2 indexed citations
11.
Dang, Xin, et al.. (2019). A rank-based Cramér–von-Mises-type test for two samples. Brazilian Journal of Probability and Statistics. 33(3). 4 indexed citations
12.
Dang, Xin, et al.. (2016). Symmetric Gini covariance and correlation. Canadian Journal of Statistics. 44(3). 323–342. 7 indexed citations
13.
Nan, Xiaofei, Gang Fu, Sheng Liu, et al.. (2011). Leveraging domain information to restructure biological prediction. BMC Bioinformatics. 12(S10). S22–S22. 2 indexed citations
14.
Dang, Xin & Robert Serfling. (2010). A numerical study of multiple imputation methods using nonparametric multivariate outlier identifiers and depth-based performance criteria with clinical laboratory data. Journal of Statistical Computation and Simulation. 81(5). 547–560. 5 indexed citations
15.
Nan, Xiaofei, Yixin Chen, Xin Dang, & Dawn Wilkins. (2010). Learning to rank using 1-norm regularization and convex hull reduction. 1–6. 3 indexed citations
16.
Gao, Cuilan, Xin Dang, Yixin Chen, & Dawn Wilkins. (2009). Graph ranking for exploratory gene data analysis. BMC Bioinformatics. 10(S11). S19–S19. 13 indexed citations
17.
Dang, Xin, et al.. (2009). A unified approach for analyzing exchangeable binary data with applications to developmental toxicity studies. Statistics in Medicine. 28(20). 2580–2604. 6 indexed citations
18.
Dang, Xin, Robert Serfling, & Weihua Zhou. (2008). Influence functions of some depth functions, and application to depth-weighted L-statistics. Journal of nonparametric statistics. 21(1). 49–66. 9 indexed citations
19.
Chen, Yixin, et al.. (2008). Outlier Detection with the Kernelized Spatial Depth Function. IEEE Transactions on Pattern Analysis and Machine Intelligence. 31(2). 288–305. 71 indexed citations
20.
Ding, Yuanyuan, et al.. (2007). Robust clustering in high dimensional data using statistical depths. BMC Bioinformatics. 8(S7). S8–S8. 13 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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