Peihua Qiu

170 papers receiving 3.9k citations

Peers

Peihua Qiu
Comparison fields: 5 of 188
  • Statistics, Probability and Uncertainty 1.9k
  • Statistics and Probability 1.6k
  • Control and Systems Engineering 707
  • Computer Vision and Pattern Recognition 534
  • Artificial Intelligence 381
Replace Varun Chandola with:
Varun Chandola United States
Seoung Bum Kim South Korea
Víctor Leiva Chile
Christian Weiß Germany
Thomas J. Santner United States
Igor V. Nikiforov France
Roger Sauter Australia
S. Chakraborti United States
Haipeng Shen United States
Bartosz Krawczyk Poland
Peihua Qiu relative to Varun Chandola United States Varun Chandola's profile →
Citations per field
00.5×8.2×
Varun Chandola · 1×
Citations per year

Countries citing papers authored by Peihua Qiu

Since Specialization
Citations

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

Fields of papers citing papers by Peihua Qiu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peihua Qiu

This figure shows the co-authorship network connecting the top 25 collaborators of Peihua Qiu. A scholar is included among the top collaborators of Peihua Qiu 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 Peihua Qiu. Peihua Qiu 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
#WorkIndexed citations
1 1
2 5
3 0
4 1
5 0
6 1
7 5
8 9
9 1
10 3
11 44
12 35
13 30
14 22
15
High Generic Drug Prices and Market Competition
1
16 12
17 49
18
Edge structure preserving 3-D image denoising
1
19 92
20 36

About Peihua Qiu

Peihua Qiu is a scholar working on Statistics, Probability and Uncertainty, Statistics and Probability and Computer Vision and Pattern Recognition, having authored 181 papers that have together received 4.0k indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (59 papers), Advanced Statistical Methods and Models (45 papers) and Scientific Measurement and Uncertainty Evaluation (30 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (1.9k citations), Statistics and Probability (1.6k citations) and Medical Laboratory Technology (73 citations). Peihua Qiu has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Douglas M. Hawkins, Changliang Zou, Chang Wook Kang, Zhonghua Li, Dongdong Xiang, Snigdhansu Chatterjee, Irène Gijbels, Partha S. Mukherjee, Xing Chen and Jun Li. Their work appears in journals such as Journal of the American Statistical Association, Annals of Internal Medicine and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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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