Xiaoliang Wan

2.6k total citations
50 papers, 1.8k citations indexed

About

Xiaoliang Wan is a scholar working on Statistics, Probability and Uncertainty, Statistical and Nonlinear Physics and Computational Mechanics. According to data from OpenAlex, Xiaoliang Wan has authored 50 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Statistics, Probability and Uncertainty, 19 papers in Statistical and Nonlinear Physics and 16 papers in Computational Mechanics. Recurrent topics in Xiaoliang Wan's work include Probabilistic and Robust Engineering Design (34 papers), Model Reduction and Neural Networks (17 papers) and Wind and Air Flow Studies (11 papers). Xiaoliang Wan is often cited by papers focused on Probabilistic and Robust Engineering Design (34 papers), Model Reduction and Neural Networks (17 papers) and Wind and Air Flow Studies (11 papers). Xiaoliang Wan collaborates with scholars based in United States, China and Italy. Xiaoliang Wan's co-authors include George Em Karniadakis, Jasmine Foo, Chao Yang, Daniele Venturi, Sumanta Acharya, Qifeng Liao, Hessam Babaee, B. L. Rozovskiĭ, Guang Lin and Dongbin Xiu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Fluid Mechanics and Journal of Computational Physics.

In The Last Decade

Xiaoliang Wan

46 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaoliang Wan United States 18 1.3k 563 494 430 408 50 1.8k
Clayton Webster United States 16 1.3k 1.0× 396 0.7× 374 0.8× 500 1.2× 271 0.7× 45 1.8k
Omar M. Knio United States 17 1.8k 1.4× 444 0.8× 691 1.4× 589 1.4× 547 1.3× 25 2.3k
Paul G. Constantine United States 22 871 0.6× 409 0.7× 226 0.5× 391 0.9× 197 0.5× 54 1.6k
Alireza Doostan United States 28 1.7k 1.3× 648 1.2× 336 0.7× 452 1.1× 873 2.1× 91 2.7k
Lionel Mathelin France 15 585 0.4× 328 0.6× 379 0.8× 545 1.3× 175 0.4× 40 1.1k
Phaedon‐Stelios Koutsourelakis Germany 21 1.3k 1.0× 583 1.0× 206 0.4× 255 0.6× 961 2.4× 56 2.5k
Didier Lucor France 24 895 0.7× 355 0.6× 833 1.7× 893 2.1× 245 0.6× 90 2.0k
Géraud Blatman France 8 1.9k 1.4× 262 0.5× 441 0.9× 100 0.2× 1.1k 2.6× 13 2.2k
Serhat Hosder United States 21 1.4k 1.0× 177 0.3× 587 1.2× 912 2.1× 263 0.6× 114 2.0k
Houman Owhadi United States 22 935 0.7× 630 1.1× 177 0.4× 704 1.6× 329 0.8× 102 2.5k

Countries citing papers authored by Xiaoliang Wan

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoliang Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoliang Wan

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoliang Wan. A scholar is included among the top collaborators of Xiaoliang Wan 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 Xiaoliang Wan. Xiaoliang Wan 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.
Liao, Qifeng, et al.. (2025). Adaptive Deep Density Approximation for Stochastic Dynamical Systems. Journal of Scientific Computing. 102(3). 1 indexed citations
2.
Liang, Jun‐Hong, et al.. (2024). The K‐Profile Parameterization Augmented by Deep Neural Networks (KPP_DNN) in the General Ocean Turbulence Model (GOTM). Journal of Advances in Modeling Earth Systems. 16(9). 4 indexed citations
3.
Wan, Xiaoliang, et al.. (2023). Adaptive Deep Density Approximation for Fractional Fokker–Planck Equations. Journal of Scientific Computing. 97(3). 1 indexed citations
4.
Liang, Jun‐Hong, et al.. (2022). Exploring the use of machine learning to parameterize vertical mixing in the ocean surface boundary layer. Ocean Modelling. 176. 102059–102059. 12 indexed citations
5.
Wan, Xiaoliang, et al.. (2021). A Minimum Action Method for Dynamical Systems with Constant Time Delays. SIAM Journal on Scientific Computing. 43(1). A541–A565. 3 indexed citations
6.
Wan, Xiaoliang & Shuangqing Wei. (2020). Coupling the reduced-order model and the generative model for an importance sampling estimator. Journal of Computational Physics. 408. 109281–109281. 8 indexed citations
7.
Wan, Xiaoliang & Haijun Yu. (2019). NUMERICAL APPROXIMATION OF ELLIPTIC PROBLEMS WITH LOG-NORMAL RANDOM COEFFICIENTS. International Journal for Uncertainty Quantification. 9(2). 161–186.
8.
Liang, Jun‐Hong, Xiaoliang Wan, Kenneth A. Rose, Peter P. Sullivan, & James C. McWilliams. (2018). Horizontal Dispersion of Buoyant Materials in the Ocean Surface Boundary Layer. Journal of Physical Oceanography. 48(9). 2103–2125. 27 indexed citations
9.
Wan, Xiaoliang, et al.. (2014). Adaptive multi-element polynomial chaos with discrete measure: Algorithms and application to SPDEs. Applied Numerical Mathematics. 90. 91–110. 17 indexed citations
10.
Wan, Xiaoliang & Guang Lin. (2013). Hybrid parallel computing of minimum action method. Parallel Computing. 39(10). 638–651. 8 indexed citations
11.
Babaee, Hessam, Xiaoliang Wan, & Sumanta Acharya. (2013). Effect of Uncertainty in Blowing Ratio on Film Cooling Effectiveness. Civil War Book Review. 1 indexed citations
12.
Lin, Guang, Marcelo Elizondo, Shuai Lu, & Xiaoliang Wan. (2013). UNCERTAINTY QUANTIFICATION IN DYNAMIC SIMULATIONS OF LARGE-SCALE POWER SYSTEM MODELS USING THE HIGH-ORDER PROBABILISTIC COLLOCATION METHOD ON SPARSE GRIDS. International Journal for Uncertainty Quantification. 4(3). 185–204. 18 indexed citations
13.
Wan, Xiaoliang. (2011). An adaptive high-order minimum action method. Journal of Computational Physics. 230(24). 8669–8682. 14 indexed citations
14.
Wan, Xiaoliang. (2010). A note on stochastic elliptic models. Computer Methods in Applied Mechanics and Engineering. 199(45-48). 2987–2995. 6 indexed citations
15.
Wan, Xiaoliang & George Em Karniadakis. (2009). Error Control in Multi-Element Generalized Polynomial Chaos Methodfor EllipticProblemswith Random Coefficients. 3 indexed citations
16.
Wan, Xiaoliang & George Em Karniadakis. (2009). Solving elliptic problems with non-Gaussian spatially-dependent random coefficients. Computer Methods in Applied Mechanics and Engineering. 198(21-26). 1985–1995. 32 indexed citations
17.
Foo, Jasmine, Xiaoliang Wan, & George Em Karniadakis. (2008). The multi-element probabilistic collocation method (ME-PCM): Error analysis and applications. Journal of Computational Physics. 227(22). 9572–9595. 168 indexed citations
18.
Wan, Xiaoliang & George Em Karniadakis. (2006). A sharp error estimate for the fast Gauss transform. Journal of Computational Physics. 219(1). 7–12. 16 indexed citations
19.
Venturi, Daniele, Xiaoliang Wan, & George Em Karniadakis. (2005). Stochastic Thermal Convection. Bulletin of the American Physical Society. 58.
20.
Wan, Xiaoliang & George Em Karniadakis. (2005). Simulation of Heat Transfer With Uncertainty. 947–954. 2 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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