Xin Dang

747 citations
44 papers · 462 · h-index 11

Impact in

Papers in

    • Advanced Statistical Methods and Models 20
    • Statistical Methods and Inference 18
    • Statistical Methods and Bayesian Inference 7
    • Statistical Distribution Estimation and Applications 4
    • Bayesian Methods and Mixture Models 6
    • Neural Networks and Applications 4

Xin Dang

37 papers receiving 431 citations

Peers

Xin Dang
Comparison fields: 5 of 98
  • Statistics and Probability 146
  • Accounting 91
  • Statistics, Probability and Uncertainty 49
  • Artificial Intelligence 190
  • Management Science and Operations Research 69
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Giulianella Coletti Italy
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Citations per year

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-authors

The 25 scholars most cited alongside Xin Dang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xin Dang Line = papers co-authored together Xin Dang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201179
2 200871
3 201470
4 200949
5 202021
6 201814
7 201913
8 200913
9 200713
10 201413
11 201411
12 20089
13 20178
14 20208
15 20167
16 20096
17 20105
18 20165
19 20234
20 20194

About Xin Dang

Xin Dang is a scholar working on Statistics and Probability, Artificial Intelligence, Computer Vision and Pattern Recognition, Statistics, Probability and Uncertainty and Molecular Biology, having authored 44 papers that have together received 462 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (20 papers), Statistical Methods and Inference (18 papers), Face and Expression Recognition (7 papers), Statistical Methods and Bayesian Inference (7 papers), Advanced Statistical Process Monitoring (6 papers), Bayesian Methods and Mixture Models (6 papers), Neural Networks and Applications (4 papers) and Statistical Distribution Estimation and Applications (4 papers). The work is most often cited by research in Statistics and Probability (146 citations), Accounting (91 citations), Statistics, Probability and Uncertainty (49 citations), Artificial Intelligence (190 citations) and Management Science and Operations Research (69 citations). Xin Dang has collaborated with scholars based in United States, China and South Korea. Frequent 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. Their work appears in journals such as BMC Bioinformatics, Journal of Statistical Planning and Inference, Journal of Multivariate Analysis, Knowledge-Based Systems and Water.

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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