Lili Yu

895 total citations
38 papers, 555 citations indexed

About

Lili Yu is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Lili Yu has authored 38 papers receiving a total of 555 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Statistics and Probability, 5 papers in Artificial Intelligence and 5 papers in Statistics, Probability and Uncertainty. Recurrent topics in Lili Yu's work include Statistical Methods and Bayesian Inference (18 papers), Statistical Methods and Inference (14 papers) and Statistical Distribution Estimation and Applications (10 papers). Lili Yu is often cited by papers focused on Statistical Methods and Bayesian Inference (18 papers), Statistical Methods and Inference (14 papers) and Statistical Distribution Estimation and Applications (10 papers). Lili Yu collaborates with scholars based in United States, China and South Africa. Lili Yu's co-authors include Liang Liu, Dennis K. Pearl, Karl E. Peace, Hani M. Samawi, Donna A. Wall, J J Shuster, Tom Bowen, Douglas Strother, BM Camitta and T Pick and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Lili Yu

31 papers receiving 547 citations

Peers

Lili Yu
Comparison fields: 5 of 94
  • Molecular Biology 297
  • Genetics 249
  • Statistics and Probability 79
  • Ecology, Evolution, Behavior and Systematics 77
  • Paleontology 76
Replace Vinícius Bonato with:
Vinícius Bonato Brazil
Dongsheng Lu China
Zhuo T. Su United States
Sophie Ancelet France
Patrick Brunet‐Lecomte France
Yoshiki Yasukochi Japan
Shazia Mahamdallie United Kingdom
Robinson United States
Bjarki Eldon Germany
Xiaobei Zhou China
Vinícius Bonato Brazil View profile →
Citations per field, relative to Lili Yu
Lili Yu · 1×
Citations per year, relative to Lili Yu
Lili Yu · 1×

Countries citing papers authored by Lili Yu

Since Specialization
Citations

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

Fields of papers citing papers by Lili Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lili Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Lili Yu. A scholar is included among the top collaborators of Lili Yu 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 Lili Yu. Lili Yu 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
# Work Indexed citations
1 0
2 0
3 0
4 1
5 3
6 0
7 1
8 8
9 8
10 2
11 2
12 9
13 1
14 3
15 6
16 168
17 52
18 4
19 1
20 81

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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