Maria Veiga is an applied mathematician and educator who develops data-driven methods for the natural sciences and engineering, alongside traditional numerical techniques for computational fluid dynamics. She is currently Assistant Professor of Mathematics (Tenure Track) at The Ohio State University, a position she assumed in 2023 after roles at the University of Michigan and MIDAS. Her research spans numerical methods and the application of machine learning to scientific problems, including high-order schemes for nonlinear hyperbolic PDEs with astrophysical applications. She teaches courses such as Mathematical Foundations of Machine Learning and Numerical Methods for Engineers, combining rigorous theory with practical computation. With a PhD from the University of Zurich in applied mathematics/computational science and a solid foundation from Imperial College London, she brings an international, interdisciplinary perspective to cross-cutting data-driven science.
11 years of coding experience
2 years of employment as a software developer
Computational Science and Engineering, Mathematics and Computer Science, Computational Science and Engineering, Mathematics and Computer Science at Eidgenössische Technische Hochschule Zürich
Pure Mathematics, Mathematics, 2.1, Pure Mathematics, Mathematics, 2.1 at Imperial College London
PhD Student, Applied mathematics / Computational Science, PhD Student, Applied mathematics / Computational Science at University of Zurich
Contributions:27 commits, 21 pushes, 1 branch in 3 months
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