Qian Guo

829 total citations
50 papers, 611 citations indexed

About

Qian Guo is a scholar working on Finance, Modeling and Simulation and Numerical Analysis. According to data from OpenAlex, Qian Guo has authored 50 papers receiving a total of 611 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Finance, 20 papers in Modeling and Simulation and 14 papers in Numerical Analysis. Recurrent topics in Qian Guo's work include Stochastic processes and financial applications (24 papers), Mathematical Biology Tumor Growth (13 papers) and Differential Equations and Numerical Methods (11 papers). Qian Guo is often cited by papers focused on Stochastic processes and financial applications (24 papers), Mathematical Biology Tumor Growth (13 papers) and Differential Equations and Numerical Methods (11 papers). Qian Guo collaborates with scholars based in China, United Kingdom and Japan. Qian Guo's co-authors include Youshan Tao, Xuerong Mao, Kazuyuki Aihara, Ji‐Huan He, Yuqin Wan, Rong‐Xian Yue, Wei Liu, Changpin Li, Weihua Deng and Norio Yoshida and has published in prestigious journals such as Fuel, Applied Mathematics and Computation and SIAM Journal on Control and Optimization.

In The Last Decade

Qian Guo

46 papers receiving 568 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qian Guo China 14 308 162 153 90 68 50 611
Marco Di Francesco Italy 20 613 2.0× 119 0.7× 38 0.2× 106 1.2× 199 2.9× 49 1.3k
Adam Bobrowski Poland 14 118 0.4× 70 0.4× 37 0.2× 62 0.7× 84 1.2× 72 616
Sérgio Adriani David Brazil 16 205 0.7× 72 0.4× 46 0.3× 103 1.1× 69 1.0× 45 603
Xiaohua Ding China 13 237 0.8× 119 0.7× 284 1.9× 87 1.0× 30 0.4× 67 528
Edson Pindza South Africa 16 446 1.4× 70 0.4× 204 1.3× 145 1.6× 45 0.7× 67 807
Qimin Zhang China 17 418 1.4× 154 1.0× 27 0.2× 149 1.7× 53 0.8× 153 1.1k
Alexander S. Bratus Russia 12 136 0.4× 37 0.2× 35 0.2× 47 0.5× 84 1.2× 66 440
Ovide Arino France 18 290 0.9× 16 0.1× 159 1.0× 37 0.4× 172 2.5× 50 1.1k
Sotirios Sabanis United Kingdom 12 153 0.5× 428 2.6× 107 0.7× 46 0.5× 39 0.6× 29 764
Marianito R. Rodrigo Australia 11 105 0.3× 138 0.9× 74 0.5× 39 0.4× 6 0.1× 46 414

Countries citing papers authored by Qian Guo

Since Specialization
Citations

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

Fields of papers citing papers by Qian Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qian Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Qian Guo. A scholar is included among the top collaborators of Qian Guo 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 Qian Guo. Qian Guo 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.
Guo, Qian, et al.. (2025). Euler–Maruyama scheme for delay-type stochastic McKean–Vlasov equations driven by fractional Brownian motion. Communications in Nonlinear Science and Numerical Simulation. 149. 108927–108927.
2.
Guo, Qian, et al.. (2024). Convergence analysis of an explicit method and its random batch approximation for the McKean–Vlasov equations with non-globally Lipschitz conditions. ESAIM. Mathematical modelling and numerical analysis. 58(2). 639–671. 1 indexed citations
3.
Guo, Qian, et al.. (2023). Strong convergence of an explicit numerical approximation for n-dimensional superlinear SDEs with positive solutions. Mathematics and Computers in Simulation. 216. 198–212. 1 indexed citations
4.
Hu, Junhao, et al.. (2023). Multiple-delay stochastic McKean-Vlasov equations with Hölder diffusion coefficients and their numerical schemes. Discrete and Continuous Dynamical Systems - S. 16(5). 1080–1110. 1 indexed citations
5.
Guo, Qian, et al.. (2023). Truncated Euler–Maruyama method for stochastic differential equations driven by fractional Brownian motion with super-linear drift coefficient. International Journal of Computer Mathematics. 100(12). 2184–2195. 2 indexed citations
6.
He, Jie, et al.. (2023). Spectral Collocation Method for Stochastic Differential Equations Driven by Fractional Brownian Motion. Fluctuation and Noise Letters. 22(3). 3 indexed citations
7.
8.
Guo, Qian, et al.. (2021). The truncated Milstein method for super-linear stochastic differential equations with Markovian switching. Discrete and Continuous Dynamical Systems - B. 27(7). 3663–3663. 1 indexed citations
9.
Gao, Yan, et al.. (2018). The partially truncated Euler–Maruyama method for nonlinear pantograph stochastic differential equations. Applied Mathematics and Computation. 346. 109–126. 7 indexed citations
10.
Guo, Qian, Xuerong Mao, & Rong‐Xian Yue. (2017). The truncated Euler–Maruyama method for stochastic differential delay equations. Numerical Algorithms. 78(2). 599–624. 32 indexed citations
11.
Guo, Qian, et al.. (2017). Multi-level Monte Carlo methods with the truncated Euler–Maruyama scheme for stochastic differential equations. International Journal of Computer Mathematics. 95(9). 1715–1726. 1 indexed citations
12.
Guo, Qian, et al.. (2015). Asymptotic mean-square stability of explicit Runge–Kutta Maruyama methods for stochastic delay differential equations. Journal of Computational and Applied Mathematics. 296. 427–442. 3 indexed citations
13.
Guo, Qian, et al.. (2014). The Semimartingale Approach to Almost Sure Stability Analysis of a Two-Stage Numerical Method for Stochastic Delay Differential Equation. Abstract and Applied Analysis. 2014. 1–7. 1 indexed citations
14.
Guo, Qian, et al.. (2014). Almost Sure andLpConvergence of Split-Step Backward Euler Method for Stochastic Delay Differential Equation. Abstract and Applied Analysis. 2014. 1–7. 2 indexed citations
15.
Guo, Qian. (2013). A Split-step $\theta$-Milstein Method for Linear Stochastic Delay Differential Equations. Journal of Information and Computational Science. 10(5). 1261–1273. 1 indexed citations
16.
Tao, Youshan, Qian Guo, & Kazuyuki Aihara. (2013). A partial differential equation model and its reduction to an ordinary differential equation model for prostate tumor growth under intermittent hormone therapy. Journal of Mathematical Biology. 69(4). 817–838. 19 indexed citations
17.
Tao, Youshan, Qian Guo, & Kazuyuki Aihara. (2009). A MODEL AT THE MACROSCOPIC SCALE OF PROSTATE TUMOR GROWTH UNDER INTERMITTENT ANDROGEN SUPPRESSION. Mathematical Models and Methods in Applied Sciences. 19(12). 2177–2201. 20 indexed citations
18.
Tao, Youshan & Qian Guo. (2008). A mathematical model of combined therapies against cancer using viruses and inhibitors. Science in China Series A Mathematics. 51(12). 2315–2329. 3 indexed citations
19.
Tao, Youshan & Qian Guo. (2005). The competitive dynamics between tumor cells, a replication-competent virus and an immune response. Journal of Mathematical Biology. 51(1). 37–74. 42 indexed citations
20.
He, Ji‐Huan, Yuqin Wan, & Qian Guo. (2004). An iteration formulation for normalized diode characteristics: Letters to the Editor. International Journal of Circuit Theory and Applications. 32(6). 629–632. 13 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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