Sara Hahner

Scientist for Machine Learning
Research, Earth System Modelling, Innovation Platform

Summary:

Sara Hahner is a machine learning scientist working on representing the earth system components in the data-driven weather forecasting system at ECMWF. 

She has a scientific background in applied mathematics and has studied machine learning applications in other domains, for example, the representation learning for 3D surface meshes and the postprocessing of car crash simulations.

Professional interests:
  • Machine Learning for Earth System Modelling
  • Representing different components in an Earth system model
  • Data-driven ocean, sea ice, and wave modelling
Career background:
  • since 2024: Scientist for Machine Learning at ECMWF
  • Ph.D (Dr. rer. nat.) Mathematics, University of Bonn, Germany (2024). Thesis on "Low-dimensional Representations for Diverse Collections of 3D Surface Meshes" (supervised by Jochen Garcke)
  • 2020 - 2024: Machine Learning Scientist, Fraunhofer Scientific Computing and Algorithms Institute (SCAI) in Sankt Augustin, Germany
  • 2022: Research Internship, École Polytechnique, France. Visiting research group of Maks Ovsjanikov
  • M.Sc. Computer Science, University of Bonn, Germany (2019). Major: Intelligent Systems, Thesis on "Analyzing and Predicting Simulation Results using Oriented Bounding Boxes and Recurrent Neural Networks"
  • B.Sc. Mathematics, University of Bonn, Germany (2017). Major: Numerical Analysis, Minor: Computer Science, Thesis on "Analysis of an Inverse Mapping of Nonlinear Dimensionality Reductions with Application on Simulation Data"