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dr. M. Guo (Mengwu)

Assistant Professor

About Me

Dr. Mengwu Guo is an Assistant Professor in Applied Mathematics at the University of Twente since February 2021. Before joining UT, Mengwu was a Postdoctoral Fellow in the Oden Institute for Computational Engineering and Sciences at The University of Texas at Austin. Prior to that, he was a Postdoctoral Researcher in the Institute of Mathematics at Ecole Polytechnique Fédérale de Lausanne (EPFL). Before his postdoctoral positions, Mengwu received his B.E. and Ph.D. degrees in Civil Engineering with honors from Tsinghua University (Beijing, China) in 2013 and 2017, respectively.

Mengwu has been dedicated to the development of high-performance numerical methods towards real-world engineering applications, and his current research interests include data-driven modeling, model order reduction, uncertainty quantification, and the use of machine learning in computational engineering and sciences.

Research

Dr. Mengwu Guo's research interests span several areas of computational sciences and engineering including model order reduction, data-driven modeling, uncertainty quantification, and scientific machine learning. With an interdisciplinary background between engineering sciences and computational mathematics, Mengwu has been dedicated to the development of high-performance numerical methods towards real-world engineering applications.

Publications

Recent
Guo, M., McQuarrie, S. A., & Willcox, K. E. (Accepted/In press). Bayesian operator inference for the reduced order modeling of time-dependent problems. Abstract from SIMAI 2020+21, Italy.
Guo, M., Hesthaven, J. S., Kast, M., McQuarrie, S. A., & Willcox, K. E. (Accepted/In press). Bayesian methods for non-intrusive reduced order modeling. Abstract from Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering and Technology (MMLDT-CSET) Conference, San Diego, United States.
Guo, M., & Haghighat, E. (Accepted/In press). Bounding discretization errors of physics-informed neural network solutions in elasticity. Abstract from 16th U.S. National Congress on Computational Mechanics, United States.
Guo, M., McQuarrie, S. A., & Willcox, K. E. (2021). A Bayesian formulation of operator inference for non-intrusive reduced order modeling. Abstract from SIAM Conference on Computational Science and Engineering 2021, United States.
Kast, M. , Guo, M., & Hesthaven, J. S. (2020). A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems. Computer methods in applied mechanics and engineering. https://doi.org/10.1016/j.cma.2020.112947
Yu, J., Yan, C. , & Guo, M. (2019). Non-intrusive reduced-order modeling for fluid problems: A brief review. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 233(16), 5896-5912. https://doi.org/10.1177/0954410019890721
Zhang, Z. , Guo, M., & Hesthaven, J. S. (2019). Model order reduction for large-scale structures with local nonlinearities. Computer methods in applied mechanics and engineering, 353, 491-515. https://doi.org/10.1016/j.cma.2019.04.042
Guo, M., & Hesthaven, J. S. (2019). Data-driven reduced order modeling for time-dependent problems. Computer methods in applied mechanics and engineering, 345, 75-99. https://doi.org/10.1016/j.cma.2018.10.029
Guo, M., & Hesthaven, J. S. (2018). Reduced order modeling for nonlinear structural analysis using Gaussian process regression. Computer methods in applied mechanics and engineering, 341, 807-826. https://doi.org/10.1016/j.cma.2018.07.017
Guo, M., & Zhong, H. (2017). 两种严格界面向目标误差估计方法的等价性. Qinghua Daxue Xuebao/Journal of Tsinghua University, 57(4), 362-368. https://doi.org/10.16511/j.cnki.qhdxxb.2017.25.005
Guo, M., & Zhong, H. (2016). Weak form quadrature solution of 2mth-order Fredholm integro-differential equations. International journal of computer mathematics, 93(10), 1650-1664. https://doi.org/10.1080/00207160.2015.1070839

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Contact Details

Visiting Address

University of Twente
Drienerlolaan 5
7522 NB Enschede
The Netherlands

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Mailing Address

University of Twente
P.O. Box 217
7500 AE Enschede
The Netherlands

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