Minh Nguyen
Research interests
My research focuses on differentiable physics approaches for ocean modeling. Using a combination of numerical methods and data-driven ML, I develop techniques for gradient-based optimization in realistic ocean models. Applications include data assimilation, parameter tuning and parametrization learning. I am working on the EDITO ModelLab, an EU project aiming to create digital twins of the ocean.
2023 - Present: Postdoc reseacher in Model-driven Machine Learning for Climate and Earth Science.
2016 - 2023: PhD in Mathematics and Physics, Chair of Computational Science and Simulation Technology, Leibniz Universität Hannover.
- V.M. Nguyen-Thanh, L.T.K. Nguyen, X. Zhuang, T. Rabczuk. A surrogate model for computational homogenization of elastostatics at finite strain using the HDMR-based neural network approximator. International Journal for Numerical Methods in Engineering, Jun 2020, https://doi.org/10.1002/nme.6493
- E. Samaniego, C. Anitescu, S. Goswami, V.M. Nguyen-Thanh, H. Guo, K. Hamdia, X. Zhuang, T. Rabczuk. An energy approach to the solution of partial differential equations in computational mechanics via machine learning: Concepts, implementation, and applications. Computer Methods in Applied Mechanics and Engineering, Apr 2020 (362), https://doi.org/10.1016/j.cma.2019.112790