Mingyu Gao

52 papers receiving 1.4k citations

Peers

Mingyu Gao
Comparison fields: 5 of 128
  • Hardware and Architecture 517
  • Electrical and Electronic Engineering 510
  • Computer Networks and Communications 398
  • Computer Vision and Pattern Recognition 369
  • Artificial Intelligence 342
Replace Yansong Gao with:
Yansong Gao China
S. Vassiliadis Netherlands
Zhiyuan Li United States
Yasuaki Ito Japan
Maya Gokhale United States
Ritesh Aggarwal India
Bin Ren United States
Guojie Luo China
Alexandru Nicolau United States
Rong Chen China
Mingyu Gao relative to Yansong Gao China Yansong Gao's profile →
Citations per field
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Citations per year

Countries citing papers authored by Mingyu Gao

Since Specialization
Citations

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

Fields of papers citing papers by Mingyu Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingyu Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Mingyu Gao. A scholar is included among the top collaborators of Mingyu Gao 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 Mingyu Gao. Mingyu Gao 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
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5 7
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10
PET: Optimizing Tensor Programs with Partially Equivalent Transformations and Automated Corrections.
13
11
Improving the Accuracy, Scalability, and Performance of Graph Neural Networks with Roc
90
12
Optimizing DNN Computation with Relaxed Graph Substitutions
30
13
Special session paper 3D nanosystems enable embedded abundant-data computing
3
14 131
15 14
16 26
17 25
18 11
19 114
20 36

About Mingyu Gao

Mingyu Gao is a scholar working on Hardware and Architecture, Computational Mathematics and Computer Networks and Communications, having authored 62 papers that have together received 1.5k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (21 papers), Advanced Data Storage Technologies (10 papers) and Advanced Memory and Neural Computing (8 papers). The work is most often cited by research in Hardware and Architecture (517 citations), Computer Vision and Pattern Recognition (369 citations) and Computer Networks and Communications (398 citations). Mingyu Gao has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Christos Kozyrakis, Grant Ayers, Xuan Yang, Jing Pu, Mark Horowitz, Zhihao Jia, Matei Zaharia, Alex Aiken, Ying Yang and Youwei Zhuo. Their work appears in journals such as Angewandte Chemie International Edition, American Journal of Respiratory and Critical Care Medicine and Green Chemistry.

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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