Junchan Zhao

532 total citations
27 papers, 421 citations indexed

About

Junchan Zhao is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics and Economics and Econometrics. According to data from OpenAlex, Junchan Zhao has authored 27 papers receiving a total of 421 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Networks and Communications, 20 papers in Statistical and Nonlinear Physics and 5 papers in Economics and Econometrics. Recurrent topics in Junchan Zhao's work include Nonlinear Dynamics and Pattern Formation (18 papers), Neural Networks Stability and Synchronization (17 papers) and stochastic dynamics and bifurcation (11 papers). Junchan Zhao is often cited by papers focused on Nonlinear Dynamics and Pattern Formation (18 papers), Neural Networks Stability and Synchronization (17 papers) and stochastic dynamics and bifurcation (11 papers). Junchan Zhao collaborates with scholars based in China, France and United States. Junchan Zhao's co-authors include Qunjiao Zhang, Jun-an Lu, Jinhu Lü, Xiaoqun Wu, Zhong‐Ping Jiang, Qin Li, M. A. Aziz-Alaoui, Cyrille Bertelle, Yisi Wang and Wei Xiang and has published in prestigious journals such as Scientific Reports, Journal of the Franklin Institute and Physica A Statistical Mechanics and its Applications.

In The Last Decade

Junchan Zhao

25 papers receiving 394 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Junchan Zhao China	11	337	298	29	25	22	27	421
Juan Gonzalo Barajas-Ramírez Mexico	9	204 0.6×	229 0.8×	16 0.6×	22 0.9×	26 1.2×	34	325
Volodymyr Lynnyk Czechia	11	217 0.6×	171 0.6×	20 0.7×	40 1.6×	17 0.8×	44	302
Shuaibing Zhu China	11	288 0.9×	196 0.7×	36 1.2×	36 1.4×	50 2.3×	21	367
Qunjiao Zhang China	15	662 2.0×	548 1.8×	46 1.6×	39 1.6×	26 1.2×	36	767
D.A. Miller United States	11	160 0.5×	255 0.9×	33 1.1×	13 0.5×	27 1.2×	31	345
Haijun Jiang China	11	278 0.8×	208 0.7×	112 3.9×	24 1.0×	12 0.5×	33	347
Rafig Agaev Russia	7	144 0.4×	65 0.2×	26 0.9×	35 1.4×	9 0.4×	19	238
Mansour E. Ahmed Egypt	9	292 0.9×	370 1.2×	25 0.9×	18 0.7×	13 0.6×	13	394
Banlue Srisuchinwong Thailand	11	240 0.7×	357 1.2×	55 1.9×	5 0.2×	16 0.7×	51	436
Feng Ru-peng China	5	316 0.9×	367 1.2×	33 1.1×	15 0.6×	4 0.2×	9	382

Countries citing papers authored by Junchan Zhao

Since Specialization

Citations

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

Fields of papers citing papers by Junchan Zhao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junchan Zhao

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wu, Xiaoqun, et al.. (2025). Human prophylaxis-driven cooperative spreading between information and epidemics in duplex networks. Chaos An Interdisciplinary Journal of Nonlinear Science. 35(3). 1 indexed citations

Wang, Yue, Jie Gao, Junchan Zhao, & Xingyu Wu. (2025). Event-triggered predefined-time tracking control for high-order nonlinear systems with time-varying actuator failures and uncertain disturbances. Engineering Applications of Artificial Intelligence. 148. 110368–110368.

Gao, Jie & Junchan Zhao. (2022). Fixed-Time Synchronization of Complex Networks via Intermittent Control Without Sign Function. Journal of Systems Science and Complexity. 35(5). 1748–1760. 4 indexed citations

Xiang, Wei, et al.. (2022). Identifying influential spreaders in complex networks for disease spread and control. Scientific Reports. 12(1). 5550–5550. 28 indexed citations

Zhao, Junchan, et al.. (2021). Financial risk propagation between Chinese and American stock markets based on multilayer networks. Physica A Statistical Mechanics and its Applications. 586. 126445–126445. 11 indexed citations

Wu, Xiaoqun, et al.. (2021). Synchronizability of two-layer correlation networks. Chaos An Interdisciplinary Journal of Nonlinear Science. 31(10). 103124–103124. 5 indexed citations

Zhao, Junchan, et al.. (2020). The impact of trade war on Shanghai stock exchange industry based on Granger causality network. Acta Physica Sinica. 70(7). 78901–78901. 1 indexed citations

Aziz-Alaoui, M. A., et al.. (2019). The behavior of Tutte polynomials of graphs under five graph operations and its applications. Applied Mathematics and Computation. 363. 124641–124641. 2 indexed citations

Zhao, Junchan, et al.. (2017). Generalized Synchronization and System Parameters Identification Between Two Different Complex Networks. ACTA AUTOMATICA SINICA. 43(4). 595–603. 1 indexed citations

10.

Zhao, Junchan, et al.. (2016). Sinusoidal disturbance induced topology identification of Hindmarsh-Rose neural networks. Science China Information Sciences. 59(11). 10 indexed citations

11.

Zhao, Junchan. (2013). Explosive synchronization of complex networks with different chaotic oscillators. Chinese Physics B. 22(6). 60506–60506. 8 indexed citations

12.

Zhang, Qunjiao & Junchan Zhao. (2012). Novel criteria for exponential synchronization of inner time-varying complex networks with coupling delay. Chinese Physics B. 21(4). 40502–40502. 8 indexed citations

13.

Zhang, Qunjiao & Junchan Zhao. (2011). Projective and lag synchronization between general complex networks via impulsive control. Nonlinear Dynamics. 67(4). 2519–2525. 65 indexed citations

14.

Liu, Jie, et al.. (2011). Prediction-control based feedback control of a fractional order unified chaotic system. 37. 2093–2097. 6 indexed citations

15.

Tang, Qiang, et al.. (2011). DETECTING CHAOS TIME SERIES VIA COMPLEX NETWORK FEATURE. Modern Physics Letters B. 25(23). 1889–1896. 5 indexed citations

16.

Zhao, Junchan, Jun-an Lu, & Xiaoqun Wu. (2010). Pinning control of general complex dynamical networks with optimization. Science China Information Sciences. 53(4). 813–822. 25 indexed citations

17.

Zhao, Junchan, Qin Li, Jun-an Lu, & Zhong‐Ping Jiang. (2010). Topology identification of complex dynamical networks. Chaos An Interdisciplinary Journal of Nonlinear Science. 20(2). 23119–23119. 48 indexed citations

18.

Zhao, Junchan, Qin Li, Jun-an Lu, & Zhong‐Ping Jiang. (2009). Robust synchronization of weighted complex dynamical networks. TU/e Research Portal. 50. 1708–1713.

19.

Zhang, Qunjiao, Jun-an Lu, & Junchan Zhao. (2009). Impulsive synchronization of general continuous and discrete-time complex dynamical networks. Communications in Nonlinear Science and Numerical Simulation. 15(4). 1063–1070. 49 indexed citations

20.

Zhao, Junchan & Jinhu Lü. (2006). Using sampled-data feedback control and linear feedback synchronization in a new hyperchaotic system. Chaos Solitons & Fractals. 35(2). 376–382. 54 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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