I am a postdoctoral researcher (postdoc) at the Chair for the Methods of Machine Learning at the University of Tübingen, advised by Philipp Hennig. Before that, I did my Ph.D. in the same group as part of the IMPRS-IS (International Max Planck Research School for Intelligent Systems). I am working on more user-friendly training methods for machine learning. My work aims at riding the field of deep learning of annoying hyperparameters and thus automate the training of deep neural networks.

Prior to joining the IMPRS-IS, I studied Simulation Technology (B.Sc. and M.Sc.) and Industrial and Applied Mathematics (M.Sc) at the University of Stuttgart and the Technische Universiteit Eindhoven respectively. My Master’s thesis was on constructing preconditioners for Toeplitz matrices. This project was done at ASML (Eindhoven), a company developing lithography system for the semiconductor industry.

  • Deep Learning
  • Training Algorithms
  • Stochastic Optimization
  • Benchmarking
  • Artificial Intelligence
  • Postdoctoral Researcher, 2022 -

    University of Tübingen

  • Ph.D. in Computer Science, 2017 - 2022

    University of Tübingen & MPI-IS, IMPRS-IS fellow

  • M.Sc. in Industrial and Applied Mathematics, 2015 - 2016

    TU/e Eindhoven

  • M.Sc. in Simulation Technology, 2015 - 2016

    University of Stuttgart

  • B.Sc. in Simulation Technology, 2011 - 2015

    University of Stuttgart