Yu Yang

1.1k total citations
60 papers, 836 citations indexed

About

Yu Yang is a scholar working on Public Health, Environmental and Occupational Health, Genetics and Modeling and Simulation. According to data from OpenAlex, Yu Yang has authored 60 papers receiving a total of 836 indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Public Health, Environmental and Occupational Health, 37 papers in Genetics and 31 papers in Modeling and Simulation. Recurrent topics in Yu Yang's work include Mathematical and Theoretical Epidemiology and Ecology Models (49 papers), Evolution and Genetic Dynamics (37 papers) and COVID-19 epidemiological studies (14 papers). Yu Yang is often cited by papers focused on Mathematical and Theoretical Epidemiology and Ecology Models (49 papers), Evolution and Genetic Dynamics (37 papers) and COVID-19 epidemiological studies (14 papers). Yu Yang collaborates with scholars based in China, Australia and Taiwan. Yu Yang's co-authors include Shigui Ruan, Lan Zou, C. Connell McCluskey, Dongmei Xiao, Tonghua Zhang, Yancong Xu, Cheng-Hsiung Hsu, Liguang Xu, Shengliang Zhang and Hongqiang Yang and has published in prestigious journals such as Fertility and Sterility, Journal of Mathematical Analysis and Applications and Chaos Solitons & Fractals.

In The Last Decade

Yu Yang

53 papers receiving 798 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yu Yang China 16 722 491 480 81 58 60 836
Cruz Vargas‐De‐León Mexico 16 862 1.2× 357 0.7× 696 1.4× 73 0.9× 59 1.0× 69 1.2k
Xiangyun Shi China 17 552 0.8× 355 0.7× 298 0.6× 68 0.8× 79 1.4× 50 728
Gang Huang China 17 1.1k 1.6× 747 1.5× 819 1.7× 117 1.4× 135 2.3× 45 1.3k
Abdessamad Tridane United Arab Emirates 14 532 0.7× 255 0.5× 476 1.0× 48 0.6× 28 0.5× 70 803
Yoichi Enatsu Japan 14 619 0.9× 412 0.8× 476 1.0× 41 0.5× 38 0.7× 33 720
Prashant K. Srivastava India 14 491 0.7× 241 0.5× 429 0.9× 32 0.4× 39 0.7× 62 679
Hongying Shu China 17 1.1k 1.6× 766 1.6× 602 1.3× 224 2.8× 101 1.7× 45 1.3k
Noura Yousfi Morocco 24 1.4k 1.9× 683 1.4× 1.2k 2.5× 145 1.8× 62 1.1× 94 1.7k
Xia Wang China 19 743 1.0× 422 0.9× 407 0.8× 145 1.8× 80 1.4× 70 993
Junyuan Yang China 17 723 1.0× 366 0.7× 616 1.3× 19 0.2× 58 1.0× 101 996

Countries citing papers authored by Yu Yang

Since Specialization
Citations

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

Fields of papers citing papers by Yu Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yu Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Yu Yang. A scholar is included among the top collaborators of Yu Yang 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 Yu Yang. Yu Yang 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.
Yang, Yu & Lan Zou. (2025). Dynamical analysis of a latent HIV infection model with general incidence and multiple delays. Chaos An Interdisciplinary Journal of Nonlinear Science. 35(9).
2.
3.
Yang, Yu, et al.. (2022). A note on the propagation dynamics in a nonlocal dispersal HIV infection model. Proceedings of the American Mathematical Society. 150(11). 4867–4877. 1 indexed citations
4.
Yang, Yu, et al.. (2021). A Diffusive Sveir Epidemic Model with Time Delay and General Incidence. Acta Mathematica Scientia. 41(4). 1385–1404. 2 indexed citations
5.
Jiang, Xiaoyu, Yu Yang, Fanwei Meng, & Yancong Xu. (2020). MODELLING THE DYNAMICS OF AVIAN INFLUENZA WITH NONLINEAR RECOVERY RATE AND PSYCHOLOGICAL EFFECT. Journal of Applied Analysis & Computation. 10(3). 1170–1192. 2 indexed citations
6.
Xu, Yancong, Yu Yang, Fanwei Meng, & Pei Yu. (2020). Modeling and analysis of recurrent autoimmune disease. Nonlinear Analysis Real World Applications. 54. 103109–103109. 8 indexed citations
7.
Yang, Yu, et al.. (2019). Threshold dynamics of a diffusive SIRI model with nonlinear incidence rate. Journal of Mathematical Analysis and Applications. 478(2). 874–896. 25 indexed citations
8.
Zhang, Shengliang, Hongqiang Yang, & Yu Yang. (2018). A multiquadric quasi-interpolations method for CEV option pricing model. Journal of Computational and Applied Mathematics. 347. 1–11. 31 indexed citations
9.
Yang, Yu, et al.. (2018). Global dynamics of a reaction–diffusion waterborne pathogen model with general incidence rate. Journal of Mathematical Analysis and Applications. 466(1). 835–859. 24 indexed citations
10.
Puscheck, Elizabeth E., Alan Bolnick, Awoniyi O. Awonuga, et al.. (2018). Why AMPK agonists not known to be stressors may surprisingly contribute to miscarriage or hinder IVF/ART. Journal of Assisted Reproduction and Genetics. 35(8). 1359–1366. 9 indexed citations
11.
Yang, Yu, et al.. (2017). Global stability of a discrete multigroup SIR model with nonlinear incidence rate. Mathematical Methods in the Applied Sciences. 40(14). 5370–5379. 15 indexed citations
12.
Yang, Yu, Alan Bolnick, Quan-Wen Li, et al.. (2017). Blastocyst-Derived Stem Cell Populations under Stress: Impact of Nutrition and Metabolism on Stem Cell Potency Loss and Miscarriage. Stem Cell Reviews and Reports. 13(4). 454–464. 10 indexed citations
13.
Zhang, Shengliang, Yu Yang, & Hongqiang Yang. (2017). A meshless symplectic algorithm for nonlinear wave equation using highly accurate RBFs quasi-interpolation. Applied Mathematics and Computation. 314. 110–120. 16 indexed citations
14.
Yang, Yu & Yancong Xu. (2016). Global stability of a diffusive and delayed virus dynamics model with Beddington–DeAngelis incidence function and CTL immune response. Computers & Mathematics with Applications. 71(4). 922–930. 25 indexed citations
15.
Yang, Yu, et al.. (2016). Global stability of a discrete virus dynamics model with Holling type‐II infection function. Mathematical Methods in the Applied Sciences. 39(8). 2078–2082. 14 indexed citations
16.
Yang, Yu, et al.. (2016). Nonstandard finite difference scheme for a diffusive within-host virus dynamics model with both virus-to-cell and cell-to-cell transmissions. Computers & Mathematics with Applications. 72(4). 1013–1020. 42 indexed citations
17.
Yang, Yu. (2015). Stability and Hopf bifurcation of a delayed virus infection model with Beddington–DeAngelis infection function and cytotoxic T‐lymphocyte immune response. Mathematical Methods in the Applied Sciences. 38(18). 5253–5263. 5 indexed citations
18.
Yang, Yu, Shigui Ruan, & Dongmei Xiao. (2015). Global stability of an age-structured virus dynamics model with Beddington-DeAngelis infection function. Mathematical Biosciences & Engineering. 12(4). 859–877. 38 indexed citations
19.
Yang, Yu, Lan Zou, & Shigui Ruan. (2015). Global dynamics of a delayed within-host viral infection model with both virus-to-cell and cell-to-cell transmissions. Mathematical Biosciences. 270(Pt B). 183–191. 146 indexed citations
20.
Yang, Yu. (2014). Global stability of VEISV propagation modeling for network worm attack. Applied Mathematical Modelling. 39(2). 776–780. 11 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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