Kai Fu

530 total citations
21 papers, 130 citations indexed

About

Kai Fu is a scholar working on Numerical Analysis, Computational Mechanics and Global and Planetary Change. According to data from OpenAlex, Kai Fu has authored 21 papers receiving a total of 130 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Numerical Analysis, 7 papers in Computational Mechanics and 7 papers in Global and Planetary Change. Recurrent topics in Kai Fu's work include Differential Equations and Numerical Methods (6 papers), Atmospheric aerosols and clouds (5 papers) and Computational Fluid Dynamics and Aerodynamics (5 papers). Kai Fu is often cited by papers focused on Differential Equations and Numerical Methods (6 papers), Atmospheric aerosols and clouds (5 papers) and Computational Fluid Dynamics and Aerodynamics (5 papers). Kai Fu collaborates with scholars based in China, Canada and South Korea. Kai Fu's co-authors include Dong Liang, Meiqin Wang, Xianqing Lv, Shusen Xie, Yilei Shi, L. Sun, Wenqia Wang, Wei Wang, Jicai Zhang and Ning Li and has published in prestigious journals such as Journal of Computational Physics, Atmospheric Environment and SIAM Journal on Scientific Computing.

In The Last Decade

Kai Fu

20 papers receiving 126 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kai Fu China	8	51	45	24	22	19	21	130
Donsub Rim United States	8	19 0.4×	41 0.9×	58 2.4×	11 0.5×	1 0.1×	16	208
Dmitry Kovalev Russia	7	13 0.3×	60 1.3×	56 2.3×	8 0.4×		26	165
Andrew T. T. McRae United Kingdom	8	18 0.4×	86 1.9×	18 0.8×	12 0.5×		13	224
Wenbin Li China	8	8 0.2×	21 0.5×	16 0.7×	16 0.7×	3 0.2×	24	232
Ravshan Ashurov Uzbekistan	10	144 2.8×	5 0.1×	7 0.3×	25 1.1×	153 8.1×	86	429
Fredrik Lindgren Sweden	8	27 0.5×	54 1.2×	1 0.0×	4 0.2×	12 0.6×	12	223
D. Pomeroy United States	5	9 0.2×	18 0.4×	2 0.1×	13 0.6×	13 0.7×	6	147
Alessio Spantini United States	5	6 0.1×	10 0.2×	75 3.1×	5 0.2×	1 0.1×	6	152
Christian Pelties Germany	9	12 0.2×	64 1.4×	47 2.0×	4 0.2×		16	438
Vincent A. Barker Denmark	4	15 0.3×	34 0.8×	3 0.1×	4 0.2×	3 0.2×	7	74

Countries citing papers authored by Kai Fu

Since Specialization

Citations

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

Fields of papers citing papers by Kai Fu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kai Fu

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

All Works

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20 of 20 papers shown

Yue, Zhen, et al.. (2024). Numerical discretization of a Darcy–Forchheimer flow with variable density and heat transfer. Journal of Computational and Applied Mathematics. 457. 116252–116252. 1 indexed citations

Fu, Kai, et al.. (2023). Positivity preserving temporal second-order spatial fourth-order conservative characteristic methods for convection dominated diffusion equations. Computers & Mathematics with Applications. 149. 190–202. 2 indexed citations

Fu, Kai, et al.. (2023). Error estimates of high-order compact finite difference schemes for the nonlinear abcd s systems. IMA Journal of Numerical Analysis. 44(5). 2959–2996.

Fu, Kai, et al.. (2022). Positive and Conservative Characteristic Block-Centered Finite Difference Methods for Convection Dominated Diffusion Equations. Advances in Applied Mathematics and Mechanics. 14(5). 1087–1110. 2 indexed citations

Liu, Yongzhi, et al.. (2022). Advancing parameter estimation with Characteristic Finite Difference Method (CFDM) for a marine ecosystem model by assimilating satellite observations: Spatial distributions. Frontiers in Marine Science. 9. 1 indexed citations

Fu, Kai, et al.. (2022). A Method Using the Huber Function for Inversion of Tidal Open Boundary Conditions of the M2 Constituent in the Bohai and Yellow Seas. Journal of Atmospheric and Oceanic Technology. 40(1). 113–127. 1 indexed citations

Shi, Yilei, Shusen Xie, Dong Liang, & Kai Fu. (2021). High Order Compact Block-Centered Finite Difference Schemes for Elliptic and Parabolic Problems. Journal of Scientific Computing. 87(3). 14 indexed citations

Cui, Tingting, Shiyao Chen, Kai Fu, Meiqin Wang, & Keting Jia. (2020). New automatic tool for finding impossible differentials and zero-correlation linear approximations. Science China Information Sciences. 64(2). 7 indexed citations

Fu, Kai & Dong Liang. (2019). A Mass-Conservative Temporal Second Order and Spatial Fourth Order Characteristic Finite Volume Method for Atmospheric Pollution Advection Diffusion Problems. SIAM Journal on Scientific Computing. 41(6). B1178–B1210. 14 indexed citations

10.

Lv, Xianqing, et al.. (2018). A Study of the Transport of Marine Pollutants Using Adjoint Method of Data Assimilation with Method of Characteristics. Advances in Mathematical Physics. 2018. 1–14. 3 indexed citations

11.

Fu, Kai, et al.. (2018). CIP Method of Characteristics for the Solution of Tide Wave Equations. Advances in Mathematical Physics. 2018. 1–10. 2 indexed citations

12.

Li, Ning, Yongzhi Liu, Xianqing Lv, Jicai Zhang, & Kai Fu. (2017). The High Order Conservative Method for the Parameters Estimation in a PM_2.5 Transport Adjoint Model. Advances in Meteorology. 2017. 1–13. 11 indexed citations

13.

Fu, Kai & Dong Liang. (2017). The Time Second Order Mass Conservative Characteristic FDM for Advection–Diffusion Equations in High Dimensions. Journal of Scientific Computing. 73(1). 26–49. 15 indexed citations

14.

Fu, Kai, et al.. (2017). Application of Adjoint Data Assimilation Method to Atmospheric Aerosol Transport Problems. Advances in Mathematical Physics. 2017. 1–14. 3 indexed citations

15.

Fu, Kai, L. Sun, & Meiqin Wang. (2016). New integral attacks on SIMON. IET Information Security. 11(5). 277–286. 8 indexed citations

16.

Fu, Kai, et al.. (2015). Linear cryptanalysis of reduced-round SPECK. Information Processing Letters. 116(3). 259–266. 8 indexed citations

17.

Fu, Kai & Dong Liang. (2015). The conservative characteristic FD methods for atmospheric aerosol transport problems. Journal of Computational Physics. 305. 494–520. 23 indexed citations

18.

Cui, Ming, et al.. (2013). Numerical analysis of the second-order characteristic FEM for nonlinear aerosol dynamic equations. Journal of Computational and Applied Mathematics. 261. 48–61. 3 indexed citations

19.

Fu, Kai, et al.. (2012). Multi-component atmospheric aerosols prediction by a multi-functional MC-HDMR approach. Atmospheric Research. 113. 43–56. 4 indexed citations

20.

Chen, Xin, Jian Zhao, Kai Fu, & Ying Chang. (2012). Refactoring of Mechanical Model Simulation Software Based on Component Technology. Advanced materials research. 466-467. 1145–1149. 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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