Yucheng Low

4.6k total citations · 2 hit papers
11 papers, 2.5k citations indexed

About

Yucheng Low is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Yucheng Low has authored 11 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Information Systems. Recurrent topics in Yucheng Low's work include Graph Theory and Algorithms (4 papers), Bayesian Modeling and Causal Inference (3 papers) and Advanced Graph Neural Networks (3 papers). Yucheng Low is often cited by papers focused on Graph Theory and Algorithms (4 papers), Bayesian Modeling and Causal Inference (3 papers) and Advanced Graph Neural Networks (3 papers). Yucheng Low collaborates with scholars based in United States and United Kingdom. Yucheng Low's co-authors include Carlos Guestrin, Joseph E. Gonzalez, Danny Bickson, Haijie Gu, Aapo Kyrola, Joseph M. Hellerstein, Alexander J. Smola, Vanja Josifovski, Amr Ahmed and Mohamed Aly and has published in prestigious journals such as Proceedings of the VLDB Endowment, Operating Systems Design and Implementation and arXiv (Cornell University).

In The Last Decade

Yucheng Low

11 papers receiving 2.4k citations

Hit Papers

Distributed GraphLab 2012 2026 2016 2021 2012 2012 250 500 750 1000
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Distributed GraphLab
    2012 1.2k citations Yucheng Low, Danny Bickson et al. Proceedings of the VLDB Endowment profile →
  2. PowerGraph: distributed graph-parallel computation on natural graphs
    2012 1000 citations Joseph E. Gonzalez, Yucheng Low et al. Operating Systems Design and Implementation profile →

Peers

Yucheng Low
Danny Bickson Israel
Aapo Kyrola United States
Grzegorz Malewicz United States
Grzegorz Czajkowski United States
James C. Dehnert United States
Yuanyuan Tian United States
Wook-Shin Han South Korea
Yuxiong He United States
Seif Haridi Sweden
Avi Silberschatz United States
Danny Bickson Israel
Yucheng Low
Citations per year, relative to Yucheng Low Yucheng Low (= 1×) peers Danny Bickson

Countries citing papers authored by Yucheng Low

Since Specialization
Citations

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

Fields of papers citing papers by Yucheng Low

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yucheng Low

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

All Works

11 of 11 papers shown
1.
Gonzalez, Joseph E. & Yucheng Low. (2023). The Story of GraphLab - From Scaling Machine Learning to Shaping Graph Systems Research (VLDB 2023 Test-of-Time Award Talk). Proceedings of the VLDB Endowment. 16(12). 4138–4138. 1 indexed citations
2.
Agrawal, Pulkit, et al.. (2019). Data Platform for Machine Learning. 1803–1816. 17 indexed citations
3.
Gonzalez, Joseph E., Yucheng Low, Haijie Gu, Danny Bickson, & Carlos Guestrin. (2012). PowerGraph: distributed graph-parallel computation on natural graphs. Operating Systems Design and Implementation. 17–30. 1000 indexed citations breakdown →
4.
Low, Yucheng, Danny Bickson, Joseph E. Gonzalez, et al.. (2012). Distributed GraphLab. Proceedings of the VLDB Endowment. 5(8). 716–727. 1151 indexed citations breakdown →
5.
Low, Yucheng & Alice X. Zheng. (2012). Fast top-k similarity queries via matrix compression. 2070–2074. 5 indexed citations
6.
Gonzalez, Joseph E., Yucheng Low, Carlos Guestrin, & David R. O’Hallaron. (2012). Distributed Parallel Inference on Large Factor Graphs. arXiv (Cornell University). 29 indexed citations
7.
Gonzalez, Joseph E., Yucheng Low, Arthur Gretton, & Carlos Guestrin. (2011). Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees. International Conference on Artificial Intelligence and Statistics. 324–332. 78 indexed citations
8.
Ahmed, Amr, Yucheng Low, Mohamed Aly, Vanja Josifovski, & Alexander J. Smola. (2011). Scalable distributed inference of dynamic user interests for behavioral targeting. 114–122. 111 indexed citations
9.
Low, Yucheng, Deepak Agarwal, & Alexander J. Smola. (2011). Multiple domain user personalization. 123–131. 17 indexed citations
10.
Gonzalez, Joseph E., Yucheng Low, & Carlos Guestrin. (2010). Parallel Splash Belief Propagation. 4 indexed citations
11.
Gonzalez, Joseph E., Yucheng Low, & Carlos Guestrin. (2009). Residual Splash for Optimally Parallelizing Belief Propagation. International Conference on Artificial Intelligence and Statistics. 177–184. 72 indexed citations

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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