Xiao‐Bai Li

1.3k citations
50 papers · 909 · h-index 19

Impact in

Papers in

Xiao‐Bai Li

45 papers receiving 859 citations

Peers

Xiao‐Bai Li
Comparison fields: 5 of 118
  • Artificial Intelligence 498
  • Management Science and Operations Research 100
  • Information Systems 146
  • Computer Science Applications 31
  • Health Information Management 20
Replace Grigorios Loukides with:
Grigorios Loukides United Kingdom
Fida K. Dankar Canada
Vijay Mago Canada
Ton de Waal Netherlands
Zhiyuan Chen United States
Fawaz S. Al–Anzi Kuwait
Yacine Jernite United States
Nathaniel D. Bastian United States
Nina Mishra United States
Xiao‐Bai Li relative to Grigorios Loukides United Kingdom Grigorios Loukides's profile →
Citations per field
00.5×
Grigorios Loukides · 1×
Citations per year

Countries citing papers authored by Xiao‐Bai Li

Since Specialization
Citations

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

Fields of papers citing papers by Xiao‐Bai Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiao‐Bai Li, 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 Xiao‐Bai Li Line = papers co-authored together Xiao‐Bai Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008130
2 200589
3 201751
4 200647
5 200646
6 200441
7 200540
8 201135
9 200335
10 202034
11 201629
12 200929
13 201027
14 201227
15 200125
16 201325
17 201324
18 201421
19 201221
20 200916

About Xiao‐Bai Li

Xiao‐Bai Li is a scholar working on Artificial Intelligence, Sociology and Political Science, Information Systems, Management Science and Operations Research and Computer Networks and Communications, having authored 50 papers that have together received 909 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (20 papers), Privacy, Security, and Data Protection (15 papers), Cryptography and Data Security (8 papers), Data Quality and Management (8 papers), Data Mining Algorithms and Applications (8 papers), Rough Sets and Fuzzy Logic (4 papers), Imbalanced Data Classification Techniques (3 papers) and Advanced Statistical Process Monitoring (3 papers). The work is most often cited by research in Artificial Intelligence (498 citations), Management Science and Operations Research (100 citations), Information Systems (146 citations), Computer Science Applications (31 citations) and Health Information Management (20 citations). Xiao‐Bai Li has collaborated with scholars based in United States and China. Frequent co-authors include Sumit Sarkar, Zhanlue Zhao, X.R. Li, Jialun Qin, Luvai Motiwalla, Srinivasan Raghunathan, James T. C. Teng, Lori A. Thombs, Joan M. Donohue and Yosef Khan. Their work appears in journals such as Journal of the Association for Information Systems, Information Systems Research, Decision Support Systems, INFORMS journal on computing and IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans.

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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