Sarah Segel
Adresse
Welfengarten 1
30167 Hannover
Gebäude
Raum
Sarah Segel
Adresse
Welfengarten 1
30167 Hannover
Gebäude
Raum

I am a PhD candidate interested in the intersection of automated machine learning (AutoML) and interpretable machine learning. 

I received my master’s degree in Physics at TU Dresden in 2016. After working on the application of machine learning to different problems in the industry for a few years, I started my PhD at Leibniz University under the supervision of Prof. Marius Lindauer in October 2022.

Research Interests

  • Automated machine learning 
  • Interpretable machine learning 

Curriculum Vitae

  • Working Experience

    2022 - Present
    Doctoral Researcher, Leibniz University Hannover

    2018 - 2022
    Data
    Scientist, OSP (Otto Group Solution Provider) GmbH

    2017 - 2018
    Data
    Scientist, Know-Center GmbH

  • Education

    2022 - Present
    PhD Student, Leibniz University Hannover

    2015 - 2018
    Master of Science, Physics, TU Dresden

    2012 - 2015
    Bachelor of Science, Physics, TU Dresden

Publications

Zeige Ergebnisse 1 - 2 von 2

2023


Segel, S., Graf, H., Tornede, A., Bischl, B., & Lindauer, M. (2023). Symbolic Explanations for Hyperparameter Optimization. In AutoML Conference 2023 PMLR. Vorabveröffentlichung online. https://openreview.net/forum?id=JQwAc91sg_x
Tornede, A., Deng, D., Eimer, T., Giovanelli, J., Mohan, A., Ruhkopf, T., Segel, S., Theodorakopoulos, D., Tornede, T., Wachsmuth, H., & Lindauer, M. (2023). AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks. Vorabveröffentlichung online. https://doi.org/10.48550/arXiv.2306.08107