Guojing Cong

1.3k citations
63 papers · 565 · h-index 12

Impact in

Papers in

Guojing Cong

58 papers receiving 543 citations

Peers

Guojing Cong
Comparison fields: 5 of 78
  • Hardware and Architecture 215
  • Computer Networks and Communications 304
  • Computer Vision and Pattern Recognition 215
  • Statistical and Nonlinear Physics 59
  • Artificial Intelligence 148
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Scott Beamer United States
Kuen Hung Tsoi United Kingdom
Lifeng Nai United States
Zhihao Jia United States
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Jesper Larsson Träff Austria
Tarek S. Abdelrahman Canada
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Citations per field
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Citations per year

Countries citing papers authored by Guojing Cong

Since Specialization
Citations

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

Fields of papers citing papers by Guojing Cong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200865
2 200561
3 200560
4 200644
5 201034
6 201226
7 200423
8 200421
9 202019
10 200516
11 200713
12 200811
13 200910
14 201710
15 201110
16 20129
17 20178
18 20128
19 20068
20 20217

About Guojing Cong

Guojing Cong is a scholar working on Computer Networks and Communications, Artificial Intelligence, Hardware and Architecture, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 63 papers that have together received 565 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (16 papers), Interconnection Networks and Systems (11 papers), Graph Theory and Algorithms (10 papers), Stochastic Gradient Optimization Techniques (8 papers), Advanced Graph Neural Networks (7 papers), Advanced Data Storage Technologies (7 papers), Sparse and Compressive Sensing Techniques (6 papers) and Caching and Content Delivery (6 papers). The work is most often cited by research in Hardware and Architecture (215 citations), Computer Networks and Communications (304 citations), Computer Vision and Pattern Recognition (215 citations), Statistical and Nonlinear Physics (59 citations) and Artificial Intelligence (148 citations). Guojing Cong has collaborated with scholars based in United States, Japan and China. Frequent co-authors include David A. Bader, Vijay Saraswat, John Feo, Konstantin Makarychev, I‐Hsin Chung, Sriram Krishnamoorthy, Tong Wen, George Almási, Doug Lea and Onkar Bhardwaj. Their work appears in journals such as Journal of Parallel and Distributed Computing, Journal of Computational Physics, Frontiers in Molecular Biosciences, BMC Bioinformatics and IEEE Transactions on Parallel and Distributed Systems.

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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