Research output per year
Research output per year
Personal profile
Personal profile
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.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
PhD
Award Date: 28 Jun 2017
Bachelor
Award Date: 1 Jul 2013
Artificial Intelligence Expert
- Deep Learning
- Traditional Machine Learning
- Smart and Service Industry
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems
Kast, M., Guo, M. & Hesthaven, J. S., Jun 2020, In: Computer methods in applied mechanics and engineering. 364, 112947.Research output: Contribution to journal › Article › Academic › peer-review
27 Citations (Scopus) -
Reduced order modeling for nonlinear structural analysis using Gaussian process regression
Guo, M. & Hesthaven, J. S., Nov 2018, In: Computer methods in applied mechanics and engineering. 341, p. 807-826Research output: Contribution to journal › Article › Academic › peer-review
135 Citations (Scopus) -
Data-driven reduced order modeling for time-dependent problems
Guo, M. & Hesthaven, J. S., Mar 2019, In: Computer methods in applied mechanics and engineering. 345, p. 75-99Research output: Contribution to journal › Article › Academic › peer-review
131 Citations (Scopus) -
Model order reduction for large-scale structures with local nonlinearities
Zhang, Z., Guo, M. & Hesthaven, J. S., Aug 2019, In: Computer methods in applied mechanics and engineering. 353, p. 491-515Research output: Contribution to journal › Article › Academic › peer-review
10 Citations (Scopus) -
Multi-fidelity surrogate modeling using long short-term memory networks
Conti, P., Guo, M., Manzoni, A. & Hesthaven, J. S., 1 Feb 2023, In: Computer methods in applied mechanics and engineering. 404, 22 p., 115811.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile5 Citations (Scopus)50 Downloads (Pure)
Activities
- 2 Invited talk
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Bayesian methods for data-driven reduced order modeling in simulation science
Mengwu Guo (Invited speaker)
Jun 2021Activity: Talk or presentation › Invited talk
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Bayesian methods of non-intrusive model order reduction
Mengwu Guo (Speaker)
12 May 2021Activity: Talk or presentation › Invited talk