Qing Gao

3.7k total citations · 1 hit paper
196 papers, 2.4k citations indexed

About

Qing Gao is a scholar working on Control and Systems Engineering, Artificial Intelligence and Mechanics of Materials. According to data from OpenAlex, Qing Gao has authored 196 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Control and Systems Engineering, 55 papers in Artificial Intelligence and 27 papers in Mechanics of Materials. Recurrent topics in Qing Gao's work include Adaptive Control of Nonlinear Systems (20 papers), Stability and Control of Uncertain Systems (19 papers) and Quantum Computing Algorithms and Architecture (18 papers). Qing Gao is often cited by papers focused on Adaptive Control of Nonlinear Systems (20 papers), Stability and Control of Uncertain Systems (19 papers) and Quantum Computing Algorithms and Architecture (18 papers). Qing Gao collaborates with scholars based in China, Australia and Hong Kong. Qing Gao's co-authors include Yong Wang, Gang Feng, Jianbin Qiu, Guozheng Kang, Xianjie Yang, Yingfei Xiong, Lu Liu, Hongyu Zhang, Jiajun Jiang and Xiangqun Chen and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Astrophysical Journal and IEEE Transactions on Automatic Control.

In The Last Decade

Qing Gao

173 papers receiving 2.4k citations

Hit Papers

Shaping program repair space with existing patches and si... 2018 2026 2020 2023 2018 50 100 150 200
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. Shaping program repair space with existing patches and similar code
    2018 218 citations Qing Gao et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Qing Gao China 24 794 486 402 371 328 196 2.4k
Arun K. Misra Canada 39 2.0k 2.5× 358 0.7× 380 0.9× 521 1.4× 304 0.9× 353 5.5k
J. David Powell United States 29 772 1.0× 476 1.0× 267 0.7× 214 0.6× 139 0.4× 174 3.1k
Michael Feldman Israel 20 1.1k 1.3× 616 1.3× 732 1.8× 393 1.1× 94 0.3× 41 3.2k
Andrzej Napieralski Poland 19 185 0.2× 87 0.2× 426 1.1× 133 0.4× 248 0.8× 416 2.0k
S. Bittanti Italy 34 2.7k 3.4× 457 0.9× 634 1.6× 58 0.2× 278 0.8× 261 4.4k
Martin Arnold Germany 22 1.1k 1.4× 38 0.1× 565 1.4× 231 0.6× 49 0.1× 95 2.0k
Dave Powell United States 6 1.4k 1.8× 170 0.3× 458 1.1× 78 0.2× 287 0.9× 12 2.5k
David A. Lowther Canada 31 839 1.1× 333 0.7× 1.0k 2.6× 472 1.3× 48 0.1× 243 3.4k
Masahiro Ono United States 23 612 0.8× 329 0.7× 102 0.3× 34 0.1× 170 0.5× 99 2.3k
Jun Liu China 27 1.4k 1.8× 312 0.6× 112 0.3× 44 0.1× 887 2.7× 235 2.9k

Countries citing papers authored by Qing Gao

Since Specialization
Citations

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

Fields of papers citing papers by Qing Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qing Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Qing Gao. A scholar is included among the top collaborators of Qing 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 Qing Gao. Qing 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
1.
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Gao, Qing, et al.. (2025). Robust Fuzzy Control of Network-Type Re-Entrant Manufacturing Systems With Communication Delays. IEEE Transactions on Circuits and Systems I Regular Papers. 72(11). 7389–7400. 3 indexed citations
3.
Xu, Shengjie, Ming Yang, Jingwei Zhang, et al.. (2025). Controllable and continuous quantum phase transitions in intrinsic magnetic topological insulators. Physical review. B.. 112(4). 1 indexed citations
4.
Gao, Qing, Shuai Han, Zhao Li, et al.. (2025). Laser-Induced Synthesis of ZnO/Graphene Composites with a Porous Structure for Supercapacitors. ACS Applied Nano Materials. 8(23). 11906–11918. 1 indexed citations
5.
Wang, Ruizhi, et al.. (2024). Predicting the impact depolarization behavior of PZT-5H based on machine learning. Measurement. 240. 115625–115625. 2 indexed citations
6.
Wu, Zhengtian, et al.. (2024). Multi-robot dynamic path planning with priority based on simulated annealing. Journal of the Franklin Institute. 362(1). 107396–107396. 2 indexed citations
7.
Wang, Wei, et al.. (2024). Distributed Privacy-Preserving Optimization With Accumulated Noise in ADMM. IEEE Transactions on Cybernetics. 54(12). 7717–7727. 1 indexed citations
8.
9.
Zheng, Jin, Qing Gao, Maciej Ogorzałek, Jinhu Lü, & Yue Deng. (2024). A Quantum Spatial Graph Convolutional Neural Network Model on Quantum Circuits. IEEE Transactions on Neural Networks and Learning Systems. 36(3). 5706–5720. 9 indexed citations
10.
Li, Yue, Qing Gao, Ruohan Yang, & Hao Liu. (2023). Finite-time formation control of nonaffine nonlinear systems under directed communication interactions. Journal of the Franklin Institute. 360(11). 7180–7205. 4 indexed citations
11.
Liu, Jiwen, et al.. (2023). Hot Deformation Behavior and Processing Maps of 26CrMo7S Steel Used in Oil Exploration. Materials. 16(21). 7056–7056. 1 indexed citations
12.
Gao, Qing, et al.. (2023). Robust H∞ synchronization for parabolic complex networks with coupling time-varying delays. Journal of the Franklin Institute. 361(3). 1347–1358. 6 indexed citations
13.
Gao, Qing, et al.. (2023). A Subgraph-Based Hierarchical Q-Learning Approach to Optimal Resource Scheduling for Complex Industrial Networks. IEEE Transactions on Circuits and Systems I Regular Papers. 71(5). 2146–2156. 6 indexed citations
14.
Zheng, Jin, et al.. (2022). Design of a quantum convolutional neural network on quantum circuits. Journal of the Franklin Institute. 360(17). 13761–13777. 13 indexed citations
15.
Deng, Zhao, et al.. (2017). The metal nanoparticle-induced inflammatory response is regulated by SIRT1 through NF-κB deacetylation in aseptic loosening. SHILAP Revista de lepidopterología. 2 indexed citations
16.
Gao, Qing. (2013). The Study on Whole-Process Evaluation System for Graduation Design of Engineering Undergraduates. Research and Exploration in Laboratory.
17.
Zhao, Yongxiang, et al.. (2009). Density Evolution of the Surface Short Fatigue Cracks of 1Cr18Ni9Ti Pipe-Weld Metal. Journal of Material Science and Technology. 18(3). 266–270. 3 indexed citations
18.
Gao, Qing. (2007). Finite Element Analysis of Thermal Residual Stresses Fields in Diamond Films/Si Substrate. Rengong jingti xuebao. 1 indexed citations
19.
Gao, Qing. (2005). EFFECT OF LOAD FREQUENCY ON FATIGUE BEHAVIOR OF MATERIAL IN ULTRASONIC FATIGUE TESTING. Physical Testing and Chemical Analysis. 5 indexed citations
20.
Gao, Qing. (2004). On Ultra-long Life Fatigue Behavior of 50~# Axle Steel under Ultrasonic Frequency. Zhongguo tiedao kexue. 4 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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