Ming Ouyang

26 papers receiving 540 citations

Peers

Ming Ouyang
Comparison fields: 5 of 112
  • Developmental Neuroscience 44
  • Statistics and Probability 40
  • Molecular Biology 302
  • Artificial Intelligence 134
  • Computer Vision and Pattern Recognition 77
Replace Cong Lei with:
Cong Lei China
Florence d’Alché–Buc France
Zhizheng Zhang China
Wenya Guo China
Vanathi Gopalakrishnan United States
Hyong Kim United States
Beatrix Jones New Zealand
Carlos Riveros Australia
Chenxi Sun China
Blaise Hanczar France
Ming Ouyang relative to Cong Lei China Cong Lei's profile →
Citations per field
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Citations per year

Countries citing papers authored by Ming Ouyang

Since Specialization
Citations

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

Fields of papers citing papers by Ming Ouyang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004129
2 200594
3 200777
4 200953
5 200825
6
Hierarchical Clustering with CUDA/GPU.
200923
7 200820
8 201020
9 200718
10 200118
11 200717
12 200316
13 201711
14 19986
15
AES and DES Encryption with GPU
20096
16 20165
17 20184
18 20184
19 19983
20 20033

About Ming Ouyang

Ming Ouyang is a scholar working on Molecular Biology, Artificial Intelligence, Computer Vision and Pattern Recognition, Statistics and Probability and Genetics, having authored 31 papers that have together received 568 indexed citations. Recurring topics across this work include Gene expression and cancer classification (8 papers), Statistical Methods and Inference (5 papers), Bioinformatics and Genomic Networks (5 papers), Bayesian Methods and Mixture Models (4 papers), Statistical Methods and Bayesian Inference (3 papers), Genetic Mapping and Diversity in Plants and Animals (3 papers), Complexity and Algorithms in Graphs (3 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Developmental Neuroscience (44 citations), Statistics and Probability (40 citations), Molecular Biology (302 citations), Artificial Intelligence (134 citations) and Computer Vision and Pattern Recognition (77 citations). Ming Ouyang has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include William J. Welsh, Panos G. Georgopoulos, Rebecka Jörnsten, Eric C. Rouchka, Dongming Sun, Yu R. Han, Patrizia Casaccia‐Bonnefil, Mark R. Plummer, Jiadong Li and Andrew Y. S. Cheng. Their work appears in journals such as Bioinformatics, Journal of Exposure Science & Environmental Epidemiology, Journal of Neuroscience, Journal of Molecular Evolution and BMC Bioinformatics.

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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