Tianyu Gu

3.0k total citations · 1 hit paper
20 papers, 898 citations indexed

About

Tianyu Gu is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Automotive Engineering. According to data from OpenAlex, Tianyu Gu has authored 20 papers receiving a total of 898 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 4 papers in Signal Processing and 3 papers in Automotive Engineering. Recurrent topics in Tianyu Gu's work include Autonomous Vehicle Technology and Safety (3 papers), Robotic Path Planning Algorithms (3 papers) and Data Management and Algorithms (3 papers). Tianyu Gu is often cited by papers focused on Autonomous Vehicle Technology and Safety (3 papers), Robotic Path Planning Algorithms (3 papers) and Data Management and Algorithms (3 papers). Tianyu Gu collaborates with scholars based in China, United States and Switzerland. Tianyu Gu's co-authors include Siddharth Garg, Brendan Dolan-Gavitt, Kang Liu, John M. Dolan, Jarrod Snider, Jin‐Woo Lee, Jin Woo Lee, Caleb Warren, Nooshin L. Warren and Ye Zhao and has published in prestigious journals such as Journal of Marketing, IEEE Access and International Journal of Environmental Research and Public Health.

In The Last Decade

Tianyu Gu

16 papers receiving 871 citations

Hit Papers

BadNets: Evaluating Backdooring Attacks on Deep Neural Ne... 2019 2026 2021 2023 2019 200 400 600

Peers

Tianyu Gu
Comparison fields: 5 of 89
  • Artificial Intelligence 570
  • Computer Vision and Pattern Recognition 302
  • Signal Processing 171
  • Automotive Engineering 132
  • Computer Networks and Communications 97
Replace Xiaohu Qie with:
Xiaohu Qie China
Eric Liang United States
Vijay Gadepally United States
Zuobin Xiong United States
Christos Dimitrakakis Sweden
Dongyuan Zhan United States
Tachio Terauchi Japan
Quang Do United States
Ramiro Liscano Canada
Ashish Jain India
Xiaohu Qie China View profile →
Citations per field, relative to Tianyu Gu
Tianyu Gu · 1×
Citations per year, relative to Tianyu Gu
Tianyu Gu · 1×

Countries citing papers authored by Tianyu Gu

Since Specialization
Citations

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

Fields of papers citing papers by Tianyu Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tianyu Gu

This figure shows the co-authorship network connecting the top 25 collaborators of Tianyu Gu. A scholar is included among the top collaborators of Tianyu Gu 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 Tianyu Gu. Tianyu Gu 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
# Work Indexed citations
1 0
2 2
3 0
4 0
5 5
6 3
7 4
8 15
9 7
10 1
11 41
12 0
13
BadNets: Evaluating Backdooring Attacks on Deep Neural Networks breakdown →
606
14 27
15
SafetyNets: verifiable execution of deep neural networks on an untrusted cloud
13
16 17
17 27
18 35
19 2
20 93

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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