Surat Teerapittayanon

17 papers receiving 2.2k citations

Hit Papers

Rapid prototyping of 3D DNA-origami shapes with caDNAno2009202620142020200920162017250500750

Peers

Surat Teerapittayanon
Comparison fields: 5 of 105
  • Molecular Biology 938
  • Computer Vision and Pattern Recognition 668
  • Computer Networks and Communications 592
  • Artificial Intelligence 537
  • Biomedical Engineering 380
Replace Karin Strauß with:
Karin Strauß United States
Luís Ceze United States
Lianghua He China
Eric Klavins United States
Sasitharan Balasubramaniam Ireland
Zahoor Jan Pakistan
Mark Moll United States
Andy M. Tyrrell United Kingdom
Cong Xu China
Surat Teerapittayanon relative to Karin Strauß United States Karin Strauß's profile →
Citations per field
00.5×2.7×
Karin Strauß · 1×
Citations per year

Countries citing papers authored by Surat Teerapittayanon

Since Specialization
Citations

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

Fields of papers citing papers by Surat Teerapittayanon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Surat Teerapittayanon

This figure shows the co-authorship network connecting the top 25 collaborators of Surat Teerapittayanon. A scholar is included among the top collaborators of Surat Teerapittayanon 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 Surat Teerapittayanon. Surat Teerapittayanon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
#WorkIndexed citations
1 0
2 1
3 2
4 1
5 1
6 2
7 7
8 21
9 22
10 9
11 2
12 2
13
Distributed Deep Neural Networks Over the Cloud, the Edge and End Devicesbreakdown →
528
14
BranchyNet: Fast inference via early exiting from deep neural networksbreakdown →
692
15 5
16 4
17 1
18
Rapid prototyping of 3D DNA-origami shapes with caDNAnobreakdown →
955

About Surat Teerapittayanon

Surat Teerapittayanon is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Human-Computer Interaction, having authored 18 papers that have together received 2.3k indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (3 papers), Advanced Neural Network Applications (3 papers) and Biosensors and Analytical Detection (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (668 citations), Computer Networks and Communications (592 citations) and Artificial Intelligence (537 citations). Surat Teerapittayanon has collaborated with scholars based in Thailand, United States and United Kingdom. Frequent co-authors include H. T. Kung, Bradley McDanel, George M. Church, Alejandro Vázquez, William M. Shih, Shawn M. Douglas, Adam Marblestone, Itthi Chatnuntawech, Sirawaj Itthipuripat and Chaipat Chunharas. Their work appears in journals such as Nucleic Acids Research, Scientific Reports and IEEE Transactions on Geoscience and Remote Sensing.

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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