Shumo Cui

1.3k total citations · 1 hit paper
20 papers, 899 citations indexed

About

Shumo Cui is a scholar working on Computational Mechanics, Control and Systems Engineering and Automotive Engineering. According to data from OpenAlex, Shumo Cui has authored 20 papers receiving a total of 899 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computational Mechanics, 6 papers in Control and Systems Engineering and 5 papers in Automotive Engineering. Recurrent topics in Shumo Cui's work include Computational Fluid Dynamics and Aerodynamics (9 papers), Traffic control and management (6 papers) and Advanced Numerical Methods in Computational Mathematics (6 papers). Shumo Cui is often cited by papers focused on Computational Fluid Dynamics and Aerodynamics (9 papers), Traffic control and management (6 papers) and Advanced Numerical Methods in Computational Mathematics (6 papers). Shumo Cui collaborates with scholars based in China, United States and Netherlands. Shumo Cui's co-authors include Raphael Stern, Benjamin Seibold, Daniel B. Work, Rahul Bhadani, Matt Bunting, Jonathan Sprinkle, Benedetto Piccoli, Maria Laura Delle Monache, Nathaniel Hamilton and Miles Churchill and has published in prestigious journals such as Journal of Computational Physics, Mathematics of Computation and SIAM Journal on Numerical Analysis.

In The Last Decade

Shumo Cui

17 papers receiving 863 citations

Hit Papers

Dissipation of stop-and-go waves via control of autonomou... 2018 2026 2020 2023 2018 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shumo Cui China 8 594 424 313 186 172 20 899
Manuel Soler Spain 17 114 0.2× 156 0.4× 43 0.1× 27 0.1× 24 0.1× 69 936
Venkatesan Kanagaraj India 14 503 0.8× 242 0.6× 263 0.8× 230 1.2× 9 0.1× 25 702
Olli‐Pekka Tossavainen United States 9 304 0.5× 49 0.1× 279 0.9× 341 1.8× 22 0.1× 11 533
Mohcine Chraibi Germany 18 384 0.6× 48 0.1× 322 1.0× 132 0.7× 31 0.2× 60 1.0k
Guanghan Peng China 28 2.7k 4.5× 576 1.4× 1.8k 5.7× 1.3k 6.8× 63 0.4× 96 2.8k
Ping Yi China 16 169 0.3× 30 0.1× 133 0.4× 119 0.6× 50 0.3× 48 924
Feng Sun China 12 126 0.2× 89 0.2× 89 0.3× 95 0.5× 25 0.1× 51 486
Hok K. Ng United States 15 126 0.2× 219 0.5× 42 0.1× 17 0.1× 16 0.1× 51 784
Hanwool Woo Japan 14 114 0.2× 199 0.5× 9 0.0× 75 0.4× 13 0.1× 57 511
Yiyuan Zhao United States 17 200 0.3× 109 0.3× 5 0.0× 23 0.1× 71 0.4× 94 1.2k

Countries citing papers authored by Shumo Cui

Since Specialization
Citations

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

Fields of papers citing papers by Shumo Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shumo Cui

This figure shows the co-authorship network connecting the top 25 collaborators of Shumo Cui. A scholar is included among the top collaborators of Shumo Cui 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 Shumo Cui. Shumo Cui 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.
Cui, Shumo, et al.. (2025). Robust DG schemes on unstructured triangular meshes: Oscillation elimination and bound preservation via optimal convex decomposition. Journal of Computational Physics. 526. 113769–113769. 2 indexed citations
2.
3.
Bian, Yuanzhi, et al.. (2024). Ideal comfort ellipses and comfort dynamics model for mitigating motion sickness in battery electric vehicle. Vehicle System Dynamics. 64(2). 440–456. 3 indexed citations
4.
Cui, Shumo, et al.. (2024). Bound-Preserving Framework for Central-Upwind Schemes for General Hyperbolic Conservation Laws. SIAM Journal on Scientific Computing. 46(5). A2899–A2924.
5.
Cui, Shumo, et al.. (2024). A Study on the Current Status and Future Prospects of EV Automotive Market. 1(2). 2 indexed citations
6.
Cui, Shumo, et al.. (2024). On Optimal Cell Average Decomposition for High-Order Bound-Preserving Schemes of Hyperbolic Conservation Laws. SIAM Journal on Numerical Analysis. 62(2). 775–810. 11 indexed citations
7.
Chen, Wei, et al.. (2024). Bound-preserving OEDG schemes for Aw–Rascle–Zhang traffic models on networks. Journal of Computational Physics. 520. 113507–113507. 2 indexed citations
8.
Cui, Shumo, et al.. (2023). Is the classic convex decomposition optimal for bound-preserving schemes in multiple dimensions?. Journal of Computational Physics. 476. 111882–111882. 13 indexed citations
9.
Wang, Chenxi, Alina Chertock, Shumo Cui, Alexander Kurganov, & Zhen Zhang. (2023). A diffuse-domain-based numerical method for a chemotaxis-fluid model. Mathematical Models and Methods in Applied Sciences. 33(2). 341–375. 2 indexed citations
10.
Wu, Fangyu, Raphael Stern, Shumo Cui, et al.. (2019). Tracking vehicle trajectories and fuel rates in phantom traffic jams: Methodology and data. Transportation Research Part C Emerging Technologies. 99. 82–109. 50 indexed citations
11.
Bhadani, Rahul, Matt Bunting, Benjamin Seibold, et al.. (2019). Real-time distance estimation and filtering of vehicle headways for smoothing of traffic waves. 280–290. 7 indexed citations
12.
Stern, Raphael, Shumo Cui, Maria Laura Delle Monache, et al.. (2018). Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments. Transportation Research Part C Emerging Technologies. 89. 205–221. 536 indexed citations breakdown →
13.
Chertock, Alina, et al.. (2018). Well-balanced schemes for the Euler equations with gravitation: Conservative formulation using global fluxes. Journal of Computational Physics. 358. 36–52. 54 indexed citations
14.
Chertock, Alina, Shumo Cui, & Alexander Kurganov. (2017). Hybrid Finite-Volume-Particle Method for Dusty Gas Flows. French digital mathematics library (Numdam). 3. 139–180. 3 indexed citations
15.
Cui, Shumo, Benjamin Seibold, Raphael Stern, & Daniel B. Work. (2017). Stabilizing traffic flow via a single autonomous vehicle: Possibilities and limitations. 1336–1341. 103 indexed citations
16.
Stern, Raphael, Daniel B. Work, Shumo Cui, et al.. (2016). WiP Abstract: Stabilizing Traffic with a Single Autonomous Vehicle. 1–1.
17.
Cui, Shumo, et al.. (2016). Transition from Manual to Automated Pavement Distress Data Collection and Performance Modelling in the Pavement Management System. 3 indexed citations
18.
Chertock, Alina, et al.. (2015). Well‐balanced positivity preserving central‐upwind scheme for the shallow water system with friction terms. International Journal for Numerical Methods in Fluids. 78(6). 355–383. 69 indexed citations
19.
Chertock, Alina, et al.. (2015). Steady State and Sign Preserving Semi-Implicit Runge--Kutta Methods for ODEs with Stiff Damping Term. SIAM Journal on Numerical Analysis. 53(4). 2008–2029. 38 indexed citations
20.
Cui, Shumo, Alexander Kurganov, & Alexei A. Medovikov. (2014). Particle methods for PDEs arising in financial modeling. Applied Numerical Mathematics. 93. 123–139. 1 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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