Xuhui Meng

4.7k total citations · 5 hit papers
35 papers, 2.8k citations indexed

About

Xuhui Meng is a scholar working on Statistical and Nonlinear Physics, Computational Mechanics and Aerospace Engineering. According to data from OpenAlex, Xuhui Meng has authored 35 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Statistical and Nonlinear Physics, 14 papers in Computational Mechanics and 12 papers in Aerospace Engineering. Recurrent topics in Xuhui Meng's work include Model Reduction and Neural Networks (19 papers), Nuclear Engineering Thermal-Hydraulics (10 papers) and Lattice Boltzmann Simulation Studies (10 papers). Xuhui Meng is often cited by papers focused on Model Reduction and Neural Networks (19 papers), Nuclear Engineering Thermal-Hydraulics (10 papers) and Lattice Boltzmann Simulation Studies (10 papers). Xuhui Meng collaborates with scholars based in China, United States and Germany. Xuhui Meng's co-authors include George Em Karniadakis, Liu Yang, Zhen Li, Lu Lu, Dongkun Zhang, Zongren Zou, Zhaoli Guo, Apostolos F. Psaros, Ling Guo and Qin Lou and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of Computational Physics.

In The Last Decade

Xuhui Meng

29 papers receiving 2.7k citations

Hit Papers

B-PINNs: Bayesian physics-informed neural networks for fo... 2019 2026 2021 2023 2020 2019 2022 2020 2023 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data
    2020 658 citations Xuhui Meng, George Em Karniadakis et al. Journal of Computational Physics profile →
  2. A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems
    2019 420 citations Xuhui Meng, George Em Karniadakis Journal of Computational Physics profile →
  3. Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems
    2022 388 citations Lu Lu, Xuhui Meng et al. Computer Methods in Applied Mechanics and Engineering profile →
  4. PPINN: Parareal physics-informed neural network for time-dependent PDEs
    2020 388 citations Xuhui Meng, Zhen Li et al. Computer Methods in Applied Mechanics and Engineering profile →
  5. Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons
    2023 215 citations Apostolos F. Psaros, Xuhui Meng et al. Journal of Computational Physics profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xuhui Meng China 18 1.7k 862 506 462 415 35 2.8k
Ameya D. Jagtap United States 15 2.6k 1.5× 1.3k 1.5× 559 1.1× 618 1.3× 309 0.7× 30 3.5k
Zhiping Mao United States 18 1.6k 0.9× 927 1.1× 354 0.7× 436 0.9× 208 0.5× 37 3.1k
Shengze Cai China 17 2.1k 1.2× 1.4k 1.6× 461 0.9× 647 1.4× 213 0.5× 44 3.5k
Zhicheng Wang China 9 1.1k 0.6× 533 0.6× 300 0.6× 318 0.7× 139 0.3× 25 2.0k
Benjamin Peherstorfer United States 22 1.6k 0.9× 732 0.8× 287 0.6× 427 0.9× 1.3k 3.1× 63 2.8k
Andrea Manzoni Italy 32 2.2k 1.3× 1.5k 1.7× 165 0.3× 338 0.7× 906 2.2× 124 3.7k
Dunhui Xiao China 29 1.1k 0.6× 773 0.9× 147 0.3× 338 0.7× 353 0.9× 68 2.2k
Tan Bui–Thanh United States 20 965 0.6× 806 0.9× 239 0.5× 197 0.4× 692 1.7× 58 2.0k
Minglang Yin United States 9 947 0.6× 483 0.6× 246 0.5× 262 0.6× 136 0.3× 14 1.6k
Ehsan Haghighat United States 19 1.0k 0.6× 400 0.5× 226 0.4× 208 0.5× 171 0.4× 41 2.1k

Countries citing papers authored by Xuhui Meng

Since Specialization
Citations

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

Fields of papers citing papers by Xuhui Meng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xuhui Meng

This figure shows the co-authorship network connecting the top 25 collaborators of Xuhui Meng. A scholar is included among the top collaborators of Xuhui Meng 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 Xuhui Meng. Xuhui Meng 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.
2.
Zhang, Chuang, et al.. (2025). Monte Carlo physics-informed neural networks for multiscale heat conduction via phonon Boltzmann transport equation. Journal of Computational Physics. 542. 114364–114364. 1 indexed citations
3.
Zou, Zongren, Xuhui Meng, & George Em Karniadakis. (2024). Correcting model misspecification in physics-informed neural networks (PINNs). Journal of Computational Physics. 505. 112918–112918. 31 indexed citations
4.
Zou, Zongren, Xuhui Meng, & George Em Karniadakis. (2024). Uncertainty quantification for noisy inputs–outputs in physics-informed neural networks and neural operators. Computer Methods in Applied Mechanics and Engineering. 433. 117479–117479. 16 indexed citations
5.
Guo, Ziyuan, et al.. (2023). A Comparative Study on Deep Learning Models for COVID-19 Forecast. Healthcare. 11(17). 2400–2400.
6.
Meng, Xuhui. (2023). Variational inference in neural functional prior using normalizing flows: application to differential equation and operator learning problems. Applied Mathematics and Mechanics. 44(7). 1111–1124. 3 indexed citations
7.
Meng, Xuhui, et al.. (2023). Physics-informed neural networks for predicting gas flow dynamics and unknown parameters in diesel engines. Scientific Reports. 13(1). 13683–13683. 18 indexed citations
8.
Psaros, Apostolos F., Xuhui Meng, Zongren Zou, Ling Guo, & George Em Karniadakis. (2023). Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons. Journal of Computational Physics. 477. 111902–111902. 215 indexed citations breakdown →
9.
Mohammadi, Ali, et al.. (2023). Deep neural operator for learning transient response of interpenetrating phase composites subject to dynamic loading. Computational Mechanics. 72(3). 563–576. 12 indexed citations
10.
Linka, Kevin, Amelie Schäfer, Xuhui Meng, et al.. (2022). Bayesian Physics Informed Neural Networks for real-world nonlinear dynamical systems. Computer Methods in Applied Mechanics and Engineering. 402. 115346–115346. 104 indexed citations
11.
Lu, Lu, et al.. (2022). Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems. Computer Methods in Applied Mechanics and Engineering. 393. 114823–114823. 388 indexed citations breakdown →
12.
Shi, Xiaodan, Xin Zhang, Jintao Zhang, et al.. (2021). Eef2k is not required for fertility in male mice. Translational Andrology and Urology. 10(5). 1988–1999. 5 indexed citations
13.
Lou, Qin, Xuhui Meng, & George Em Karniadakis. (2020). Physics-informed neural networks for solving forward and inverse flow problems via the Boltzmann-BGK formulation. arXiv (Cornell University). 121 indexed citations
14.
Wang, Liang, Shi Tao, Xuhui Meng, Kai Zhang, & Gui Lu. (2020). Discrete effects on boundary conditions of the lattice Boltzmann method for fluid flows with curved no-slip walls. Physical review. E. 101(6). 63307–63307. 10 indexed citations
15.
Meng, Xuhui, Haoran Sun, Zhaoli Guo, & Xiaofan Yang. (2020). A multiscale study of density-driven flow with dissolution in porous media. Advances in Water Resources. 142. 103640–103640. 7 indexed citations
16.
Meng, Xuhui & George Em Karniadakis. (2019). A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems. Journal of Computational Physics. 401. 109020–109020. 420 indexed citations breakdown →
17.
Meng, Xuhui, Liang Wang, Xiaofan Yang, & Zhaoli Guo. (2018). Preconditioned multiple-relaxation-time lattice Boltzmann equation model for incompressible flow in porous media. Physical review. E. 98(5). 10 indexed citations
18.
Wang, Peng, et al.. (2018). Uncertainty quantification on the macroscopic properties of heterogeneous porous media. Physical review. E. 98(3). 9 indexed citations
19.
Meng, Xuhui & Zhaoli Guo. (2016). Boundary scheme for linear heterogeneous surface reactions in the lattice Boltzmann method. Physical review. E. 94(5). 53307–53307. 22 indexed citations
20.
Meng, Xuhui & Zhaoli Guo. (2015). Multiple-relaxation-time lattice Boltzmann model for incompressible miscible flow with large viscosity ratio and high Péclet number. Physical Review E. 92(4). 43305–43305. 50 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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