Olga Mula Hernández

RESEARCH PROFILE

Olga Mula is an Associate Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e). She leads a group on Data-Driven Computational Science which is part of the Center for Analysis, Scientific Computing and Applications (CASA). The overarching goal of the group is to build a cohesive theory to optimally combine data of different nature in order to solve seemingly different problems in a systematic way. Examples of types of data to be used can be sensor measurements, PDE models, or time series data. This activity is very much intertwined with understanding the merits and limitations of what we commonly call artificial intelligence. This research is highly interdisciplinary, and spans the range from numerical mathematics, information theory and learning to different applications such as blood flows, air pollution, nuclear physics, and epidemiology. Olga's mathematical areas of expertise include inverse problems, numerical analysis of PDEs, approximation and learning algorithms (model reduction, neural networks). Current research works focus on forward and inverse problems for transport dominated phenomena, and numerical optimal transport.

ACADEMIC BACKGROUND

Olga Mula obtained in 2011 a double master's degree from Ecole Polytechnique (Palaiseau, France), and Universidad Politecnica (Madrid, Spain). After earning her PhD in Applied Mathematics from Sorbonne University in 2014, she spent one year at RWTH Aachen University as a postdoctoral fellow. Before joining TU/e on February 2022, she worked for six years as an Associate Professor in Applied Mathematics at Paris Dauphine University.

Ancillary Activities

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